# Petros Drineas

Associate Professor

Computer Science Department

Purdue University

## Contact Info

Email: drineas @ gmail.com

Physical address: 305 N University Street, West Lafayette, IN 47907, USA

## Education

Ph.D./M.Phil./M.Sc. in Computer Science (May 2003), Computer Science Department, Yale University

BS/M.Sc. in Computer Engineering (July 1997), Computer Engineering and Informatics Department, University of
Patras

## Research interests

Theory: Randomization in Numerical Linear Algebra (RandNLA).

Applications: Data mining, in particular the analysis of population genetics data.

Click here for my Google Scholar page.

## Teaching (at Purdue)

Fall 2017: CS59000-RND: Randomized Algorithms for Big Data Matrices

Spring 2017: CS182: Foundations of Computer Science

Fall 2016: CS59000-RND: Randomized Algorithms for Big Data Matrices

## Recent news

Jun '17: Our paper on "Fast Monte-Carlo Algorithms for Matrices II: Computing a low-rank approximation to a
matrix" was included in the list of classic papers for 2006 by Google Scholar.

Apr '17: Senior Program Committee member, Conference on Information and Knowledge Management (CIKM), Nov 6-10,
2017.

Mar '17: Our work on disproving Fallmerayer's hypothesis on the extinction of the medieval Peloponnesean Greeks
has now appeared in the European Journal of Human Genetics. Articles discussing this discovery have appeared in
multiple news venues (click here for a detailed article - in Greek - that appeared in the Greek newspaper To
Vima).

Jan '17: Editorial Board Member, SIAM Journal on Scientific Computing (SISC).

Jan '17: Editorial Board Member, Applied and Computational Harmonic Analysis (ACHA).

Dec '16: Click here for a review of the CRC Handbook of Big Data (co-edited with Peter Bühlmann, Michael Kane,
and Mark J. van der Laan) by Richard Samworth.

Nov '16: Following up on our April 2016 Workshop on Theoretical Foundations of Data Science (TFoDS), NSF
announces a new program to support institutes for Theoretical Foundations of Data Science. Read Tracy Kimbrel's
post at the Computing Community Consortium (CCC) explaining the TRIPODS program.

Oct '16: Our work on COGG (Correlation Optimization of Genetics and Geodemographics), a novel optimization
method to model genetic relationships with social factors such as castes, languages, occupation, etc. and
maximize their correlation with geography, was selected as a platform presentation at the 2016 Annual Meeting of
the American Society of Human Genetics.

Sep '16: Our work on structural convergence results for low-rank approximations from Block Krylov spaces (joint
with I. Ipsen, M. Magdon-Ismail, and E. Kontopoulou) is now available at ArXiv.

Jul '16: I taught a mini-course on RandNLA at the 26th Annual Summer Session of the Park City Math Institute
(PCMI) and the Institute for Advanced Study (IAS). The overall topic of the summer school is Mathematics of Data
and it ran from June 30 to July 20, 2016 in Midway, Utah.

Jun '16: Our review article (joint with M. W. Mahoney) on RandNLA (Randomized Numerical Linear Algebra) appeared
in the June 2016 issue of the Communications of the ACM (CACM).

Jun '16: Sixth Workshop on "Algorithms for Modern Massive Datasets" (June 21-24, 2016, at the University of
California Berkeley). Co-organizers: M. W. Mahoney and A. Shkolnik.

Apr'16: NSF-sponsored workshop (co-organizer: Xiaoming Huo) on "Theoretical Foundations of Data Science (TFoDS)"
(April 28-30, 2016, at Hilton Arlington).

Mar '16: The CRC Handbook of Big Data that I co-edited with Peter Bühlmann, Michael Kane, and Mark J. van der
Laan is now available!

Jan '16: Click here for the SIAM News article on the 2015 Gene Golub SIAM Summer School on the topic of
Randomized Numerical Linear Algebra (RandNLA).

## Student news

Nov '15: Congratulations to Srinivas Nambirajan for successfully defending his thesis.

May '15: Congratulations to Abhisek Kundu for successfully defending his thesis. Abhisek joined the Speech and
Biomedical Analytics Group in Xerox Research Center India as a Research Scientist in January 2016.

Apr '15: Congratulations to Saurabh Paul for successfully defending his thesis. Saurabh will join the Risk
Analytics team in PayPal as a Data Scientist in July 2015.

Apr '11: Congratulations to Christos Boutsidis for successfully defending his thesis. He was also awarded the
2011 Robert McNaughton Prize, given to an outstanding student in the computer science department. Christos
joined the Mathematical Sciences Department in IBM T.J. Watson as a Research Staff Member.

Sep '10: Congratulations to Jamey Lewis for successfully defending his thesis!

## Summer schools, (selected) tutorials, and talks

Oct '15: Click here for the slides from our invited mini-tutorial at the 2015 SIAM Conference on Applied Linear
Algebra on "Randomization in Numerical Linear Algebra: Theory and Practice" (with I. Ipsen and M. W.
Mahoney).

Jun '15: The 2015 Gene Golub SIAM Summer School (June 15 - 26, 2015) on the topic of Randomized Numerical Linear
Algebra (RandNLA) was held at the ancient site of Delphi (Δελφοί), a UNESCO World Cultural Heritage Site, in
Greece. Co-organizers: E. Gallopoulos, I. Ipsen, and M. W. Mahoney. Articles discussing the Summer School have
appeared in news venues.

(in Greek) Kathimerini, University of Patras Press Release, University of Patras Magazine (pages 3-4).

Sep '13: Click here for slides from my talk at the workshop on "Succinct Data Representations and Applications" under the auspices of the Theoretical Foundations of Big Data Analysis program at the Simons Institute for the Theory of Computing.

Sep '13: Click here for slides and video from my tutorial on RandNLA at the Big Data Bootcamp week under the auspices of the Theoretical Foundations of Big Data Analysis program at the Simons Institute for the Theory of Computing.

Sep '12: Talk at the MIT CSAIL seminar: click here for the slides.

Sep '12: Tutorial at the opening workshop of SAMSI's "Massive Datasets" 2012-2013 program (September 9-12, 2012). Click here for the slides of my talk.

Jun '12: Keynote talk at the SIAM Conference on Applied Linear Algebra (June 18-22, 2012); click here for the slides.

May '12: Keynote talk at the "From Data to Knowledge" workshop (UC Berkeley, May 7-11, 2012); click here for the slides.

Apr '12: Talk at the CMU Computer Science Theory Lunch: click here for the slides.

## Editorial boards and (selected) program committees

Jan '15: Editorial Board Member, SIAM Journal on Matrix Analysis and Applications (SIMAX).

Jul '14: Editorial Board Member, SIAM Journal on Scientific Computing, Special Issue for Software and Big
Data.

Feb '14: Editorial Board Member, Information and Inference: A Journal of the IMA.

Jun '14: Fifth Workshop on "Algorithms for Modern Massive Datasets" (June 17-20, 2014, at the University of
California Berkeley). Co-organizers: M. W. Mahoney, A. Shkolnik, R. Zadeh, and F. Perez.

Oct '13: Program Committee Member, 2014 ACM Symposium on Theory of Computing (May 31 - June 3, 2014).

May '13: Editorial Board Member, PLoS ONE.

Feb '13: Program Committee Member, 2014 ACM-SIAM Symposium on Discrete Algorithms (January 5-7, 2014).

Apr '13: Workshop on "Succinct Data Representations and Applications" (September 16-20, 2013, at University of
California Berkeley).

Jan '13: Vice Chair, 2013 IEEE International Conference on Data Mining (December 8-11, 2013).

Oct '12: Workshop on "Randomized Numerical Linear Algebra (RandNLA): Theory and Practice" (October 20, 2012,
Hyatt Regency, New Brunswick NJ, USA) held in conjunction with FOCS 2012. Co-organizers: H. Avron and C.
Boutsidis. Read this blog post (written by Ludwig Schmidt and edited by Michael Mitzenmacher) for a concise
summary of the workshop's talks.

Jul '12: Fourth Workshop on "Algorithms for Modern Massive Datasets" (July 10-13, 2012, at Stanford University).
Co-organizers: G. Carlsson, A. Shkolnik, and M. W. Mahoney. Click here for the slides of my talk.

May '11: NSF-sponsored workshop on "Algorithms in the Field (A8F)" (May 16-18, 2011, at DIMACS).

Jun '10: Third Workshop on "Algorithms for Modern Massive Datasets" (June 15-18, 2010, at Stanford University).
Co-organizers: G. Carlsson, L. H. Lim, and M. W. Mahoney.

Oct '09: Randomized Algorithms in Linear Algebra Minisymposia (parts I and II), under the auspices of the SIAM
Conference on Applied Linear Algebra.

## Other news

Jun '14: Our study on a maritime route of colonization of Europe, showing that island hopping was used by Near
Eastern migrants to reach Southern Europe, has appeared in the the Proceedings of the National Academy of
Sciences. Numerous news stories and blogs discuss our work:

(in English) Science, New Scientist, National Geographic, University of Washington HSNewsBeat, Popular
Archaeology, Phys Org, Phys Org News, EurekAlert, Science Daily, Science Codex, Science World Report,
Archeologie & Anthropology, Heritage Daily, Past Horizons, Archaeology, Science Newsline, Technology.org,
Dienekes' Anthropology Blog.

(in Greek) Ethnos, To Vima, Ta Nea, Real.gr, News.gr, E-kriti.gr, Kool News, Sigma Live, Polis Press, Yahoo!
Greece, Rodiaki, Go Thessaloniki, Nooz.

(in French) Le Figaro.

(in German) derStandard, Scinexx.

(in Italian) Le Scienze.

Sep '13: Harnessing the Petabyte: our new NSF IIS funded project investigates cloud computing and supercomputing
to analyze Big Data; click here for details.

May '13: Our study on ancient mtDNA from the Minoans appeared in Nature Communications. Many news stories and
blogs discuss our work (click here for a synopsis of the attention that our work generated, as reported by
Nature Communications):

- Rensselaer's press release: "DNA Analysis Unearths Origins of Minoans"

- University of Washington press release:"DNA analysis unearths origins of Minoans, the first major European
civilization"

- Nature News: "Minoan civilization was made in Europe"

- Dienekes Anthropology Blog: "mtDNA from Minoan Crete"

- BBC News: "DNA reveals origin of Greece's ancient Minoan culture"

- NBC News: "Mysterious Minoans really were Europeans, DNA finds"

- USA Today: "Europe's first civilization was home-grown"

- Scientific American: "Minoan civilization originated in Europe, not Egypt"

- Science World Report: "Europe's first advanced civilization was Minoan -- and it wasn't Egyptian"

- LiveScience: "Mysterious Minoans were European, DNA finds"

- Discovery Channel: "Mysterious Minoans were European, DNA finds"

- Discover Magazine: "Minoans, first advanced European civilization, originated from Europe, not Africa"

and, in Greek:

- Kathimerini

- Vima

- Proto Thema

- Nea Kriti

- in.gr

Feb '13: I will be a long-term participant of the "Theoretical Foundations of Big Data Analysis" program at the
Simons Institute for the Theory of Computing at the University of California Berkeley in the fall of 2013.

May '11: Ravi Kannan won the 2011 Knuth prize! Congratulations Ravi!

Oct '10: I have joined the National Science Foundation (NSF) as a Program Director at the Computing and
Communication Foundations (CCF) and the Information and Intelligent Systems (IIS) divisions in the Computer and
Information Science and Engineering (CISE) directorate.

Oct '10: Our work (co-authored with A. Javed, J. Lewis, and P. Paschou) on Ancestry Informative Markers (AIMs)
for Europeans (POPulation REference Sample - POPRES) and world-wide populations (Human Genome Diversity Panel -
HGDP) has appeared in PLoS One and the Journal of Medical Genetics, respectively.

- Supplementary material and lists of AIMs for the European populations.

- Supplementary material and lists of AIMs for the HGDP populations.

Jan '10: Our paper on "Random Walks in Time-Graphs" (joint work with U. Acer and A. Abouzeid) won the Best Paper
Award in MobiOpp 2010!

Jan '09: Our work on CUR Matrix Decompositions for Improved Data Analysis (with M. W. Mahoney) has appeared in
the Proceedings of the National Academy of Sciences.

## PhD/MS Students

- Agniva Chowdhury (PhD, 2nd year)
- Aritra Bose (PhD, 2nd year)
- Eugenia Kontopoulou (PhD, 2nd year)
- Chander Iyer (PhD, 4th year)
- Srinivas Nambirajan (PhD, graduated November 2015)
- Abhisek Kundu (PhD, graduated May 2015, joined the Speech and Biomedical Analytics Group in Xerox Research Center India as a Research Scientist in January 2016)
- Saurabh Paul (PhD, graduated May 2015, joined the Risk Analytics team in PayPal as a Data Scientist in July 2015.)
- Kiran Gilvaz (MS, now a Software Engineer at IBM)
- Christos Boutsidis (graduated May 2011, joined the Mathematical Sciences Department in IBM T.J. Watson as a Research Staff Member; Christos was awarded the 2011 Robert McNaughton Prize, given to an outstanding student in the computer science department)
- Jamey Lewis (PhD, graduated September 2010)
- Utku Gunay Acer (PhD, graduated August 2009, moved to the Maestro group at Inria Sophia-Antipolis)
- Asif Javed (graduated December 2008, moved to the Computational Biology group at the IBM T.J. Watson Research Center)
- Bugra Caskurlu (MS, graduated December 2006, now at West Virginia University)

## Publications

Available in ArXiv (under review or unpublished)

- Drineas, I. Ipsen, E. Kontopoulou, and M. Magdon-Ismail, Structural Convergenece Results for Low-Rank Approximations from Block Krylov Spaces, 2016.
- Boutsidis, P. Drineas, P. Kambadur, E. Kontopoulou, and A. Zouzias, A Qwanturank Algorithme for Approximating the Log Determinant of a Symmetric Positive Definite Matrix, 2016.
- Kundu, P. Drineas, and M. Magdon-Ismail, Recovering PCA from Hybrid-$(\ell_1,\ell_2)$ Sparse Sampling of Data Elements, 2016.
- Kundu and P. Drineas, A Note on Randomized Element-wise Matrix Sparsification, 2014.
- Boutsidis, M.W. Mahoney, and P. Drineas, An improved approximation algorithm for the column subset selection problem, 2013.
- Drineas and M.W. Mahoney, Effective Resistances, Statistical Leverage, and Applications to Linear Equation Solving, 2010.

- Fountoulakis, A. Kundu, E. Kontopoulou, and P. Drineas, A Randomized Rounding Algorithm for Sparse PCA, ACM Transactions on Knowledge Discovery from Data (TKDD), 11(3), pp. 1-26, 2017.
- Stamatoyannopoulos, A. Bose, A. Teodosiadis, F. Tsetsos, A. Plantinga, N. Psatha, N. Zogas, E. Yannaki, P. Zalloua, K. K. Kidd, B. L. Browning, J. Stamatoyannopoulos, P. Paschou, and P. Drineas, Genetics of the Peloponnesean Populations and the Theory of Extinction of the Medieval Peloponnesean Greeks, European Journal of Human Genetics (EJHG), 25(5), pp. 637-645, 2017.

- Iyer, H. Avron, G. Kollias, Y. Ineichen, C. Carothers, and P. Drineas, A Randomized Least Squares Solver for Terabyte-sized Dense Overdetermined Systems, Journal of Computational Science
- Iyer, C. Carothers, and P. Drineas, Randomized Sketching for Large-Scale Sparse Ridge Regression Problems, Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA16), held in conjunction with the 2016 International Conference on High Performance Computing, Networking, Storage and Analysis (SC16), 2016.
- J. Forde, A. S. Kanaan, J. Widomska, S. S. Padmanabhuni, E. Nespoli, J. Alexander, J. Rodriguez Arranz, S. Fan, R. Houssari, M. S. Nawaz, N. R. Zilhao, L. Pagliaroli, F. Rizzo, T. Aranyi, C. Barta, T. M. Boeckers, D. I. Boomsma, W. R. Buisman, J. K. Buitelaar, D. Cath, A. Dietrich, N. Driessen, P. Drineas, M. Dunlap, S. Gerasch, J. Glennon, B. Hengerer, O. A. van den Heuvel, C.e Jespersgaard, H. E. Moller, K. R. Müller-Vahl, T. Openneer, G. Poelmans, P. J. W. Pouwels, J. M. Scharf, H. Stefansson, Z. Tumer, D. Veltman, Y. D van der Werf, P. J. Hoekstra, A. Ludolph, and P. Paschou, TS-EUROTRAIN: A European-wide investigation and training network on the aetiology and pathophysiology of Gilles de la Tourette Syndrome, Frontiers in Neuroscience, 10, article 384, 2016.
- Tsetsos, S. S. Padmanabhuni, J. Alexander, I. Karagiannidis, M. Tsifintaris, A. Topaloudi, D. Mantzaris, M. Georgitsi, P. Drineas, and P. Paschou, Meta-analysis of Tourette Syndrome and Attention Deficit Hyperactivity Disorder provides support for a shared genetic basis, Frontiers in Neuroscience, 10, article 340, 2016.
- Clarkson, P. Drineas, M. Magdon-Ismail, M. W. Mahoney, X. Meng, and D. P. Woodruff, Faster Robust Linear Regression, SIAM Journal on Computing, 45(3), pp. 763-810, 2016.
- Paul, M. Magdon-Ismail, and P. Drineas, Feature Selection for Linear SVMs with Provable Guarantees, Pattern Recognition, 60, pp. 205-214, 2016.
- Mahoney and P. Drineas, RandNLA: Randomized Numerical Linear Algebra, Communications of the ACM (CACM), 59 (6), pp. 80-90, 2016.
- Alexander, O. Kalev, S. Mehrabian, L. Traykov, M. Raycheva, D. Kanakis, P. Drineas, M. I. Lutz, T. Ströbel, T. Penz, M. Schuster, C. Bock, I. Ferrer, P. Paschou, and G. G. Kovacs, Familial early-onset dementia with complex neuropathological phenotype and genomic background, Neurobiology of Aging, 42, pp. 199-204, 2016.
- Paul and P. Drineas, Feature Selection for Ridge Regression with Provable Guarantees, Neural Computation, MIT Press Journals, 28, pp. 716-742, 2016.
- W. Mahoney and P. Drineas, Structural Properties Underlying high-quality Randomized Numerical Linear Algebra algorithms, CRC Handbook on Big Data, pp. 137-154, 2016.
- Gallopoulos, P. Drineas, I. Ipsen, and M. W. Mahoney, RandNLA, Pythons, and the CUR for your Data problems, SIAM News, p. 7, February 2016.

- Iyer, H. Avron, G. Kollias, Y. Ineichen, C. Carothers, and P. Drineas, A Scalable Randomized Least Squares Solver for Dense Overdetermined Systems, Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA15), held in conjunction with the 2015 International Conference on High Performance Computing, Networking, Storage and Analysis (SC15), 2015.
- Kundu, P. Drineas, and M. Magdon-Ismail, Approximating Sparse PCA from Incomplete Data, Proc. of Neural Information Processing Systems (NIPS), 2015.
- Paul, M. Magdon-Ismail, and P. Drineas, Column Selection via Adaptive Sampling, Proc. of Neural Information Processing Systems (NIPS), 2015.
- Nguyen, P. Drineas, and T. Tran, Tensor Sparsification via a Bound on the Spectral Norm of Random Tensors, Information and Inference: A Journal of the IMA, 4(3), pp. 195-229, 2015.
- Paul, M. Magdon-Ismail, and P. Drineas, Feature Selection for Linear SVM with Provable Guarantees, Proc. of the 16th International Conference on Artificial Intelligence and Statistics (AISTATS) and Journal of Machine Learning Research: Workshops and Conference Proceedings 38, pp. 735-743, 2015.
- Boutsidis, A. Zouzias, M. W. Mahoney, and P. Drineas, Randomized Dimensionality Reduction for K-means Clustering, IEEE Transactions on Information Theory, 62(2), pp. 1045-1062, 2015.

- Paul and P. Drineas, Deterministic Feature Selection for Regularized Least Squares Classification, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), LNCS 8725, pp. 533-548, 2014.
- Saurabh, C. Boutsidis, M. Magdon-Ismail, and P. Drineas, Random Projections for Support Vector Machines, ACM Transactions on Knowledge Discovery from Data, 8(4):22, 2014.
- Paschou, P. Drineas, E. Yannaki, A. Razou, K. Kanaki, F. Tsetsos, S. Padmanabhuni, M. Michalodimitrakis, M. Renda, S. Pavlovic, A. Anagnostopoulos, J. Stamatoyannopoulos, K. K. Kidd, and G. Stamatoyannopoulos, Maritime route of colonization of Europe, Proceedings of the National Academy of Sciences, doi:10.1073/pnas.1320811111, 2014.
- Boutsidis, P. Drineas, and M. Magdon-Ismail, Near-Optimal Column-Based Matrix Reconstruction, SIAM Journal on Computing, 43(2), pp. 687-717, 2014.

- Boutsidis, P. Drineas, and M. Magdon-Ismail, Near-Optimal Coresets for Least-Squares Regression, IEEE Transactions on Information Theory, 59(10), 6880 - 6892, 2013.
- R. Hughey, P. Paschou, P. Drineas, D. Mastropaolo, D. M. Lotakis, P. A. Navas, M. Michalodimitrakis, J. A. Stamatoyannopoulos, and G. Stamatoyannopoulos, A European Population in Minoan Bronze Age Crete, Nature Communications, (4)1861 doi:10.1038/ncomms2871, 2013.
- Paul, C. Boutsidis, M. Magdon-Ismail, and P. Drineas, Random Projections for Support Vector Machines, Proc. of the 16th International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 498-506, 2013.
- Clarkson, P. Drineas, M. Magdon-Ismail, M. W. Mahoney, X. Meng, and D. P. Woodruff, The Fast Cauchy Transform and Faster Robust Linear Regression, Proc. of the 24th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2013.

- Drineas, M. Magdon-Ismail, M. W. Mahoney, and D. Woodruff, Fast Approximation of Matrix Coherence and Statistical Leverage, Journal of Machine Learning Research, 13, pp. 3475-3506 , 2012.
- Stathias, G. Sotiris, I. Karagiannidis, G. Bourikas, G. Martinis, D. Papazoglou, A. Tavridou, N. Papanas, E. Maltezos, M. Theodoridis, V. Vargemezis, V. Manolopoulos, W. C. Speed, J. R. Kidd, K. K. Kidd, P. Drineas, and P. Paschou, Exploring genomic structure differences and similarities between the Greek and European HapMap populations: implications for association studies, Annals of Human Genetics, 76(6), pp. 472-483, 2012.
- Drineas, M. Magdon-Ismail, M. W. Mahoney, and D. Woodruff, Fast Approximation of Matrix Coherence and Statistical Leverage, International Conference on Machine Learning (ICML), 2012.

- Kupp, H. Huang, P. Drineas, and Y. Makris, Improving Analog and RF Device Yield through Performance Calibration, IEEE Design and Test of Computers, 28(3), pp. 64-75, 2011.
- Kupp, H. Stratigopoulos, P. Drineas, and Y. Makris, On Proving the Efficiency of Alternative RF Tests, International Conference on Computer-Aided Design (ICCAD), pp. 762-767, 2011.
- Boutsidis, P. Drineas, and M. Magdon-Ismail, Sparse Features for PCA-Like Linear Regression, Proc. of Neural Information Processing Systems (NIPS), 2011.
- Boutsidis, P. Drineas, and M. Magdon-Ismail, Near-Optimal Column-Based Matrix Reconstruction, Proc. of the 52nd IEEE Symposium on Foundations of Computer Science (FOCS), 2011.
- Javed, P. Drineas, M. W. Mahoney, P. Paschou, Efficient genome-wide selection of PCA-correlated tSNPs for genotype imputation, Annals of Human Genetics, 75(6), pp. 707-722, 2011.
- Lewis, Z. Abas, C. Dadousis, D. Lykidis, P. Paschou, and P. Drineas, Tracing Cattle Breeds With Principal Components Analysis Ancestry Informative SNPs, PLoS ONE, 6(4): e18007, 2011.
- Acer, P. Drineas, and A. Abouzeid, Connectivity in Time-Graphs, Pervasive and Mobile Computing, 7, pp. 160-171, 2011.
- G. Sgourakis, M. Merced-Serrano, C. Boutsidis, P. Drineas, Z. Du, C. Wang, and A. E. Garcia, Atomic-level characterization of the ensemble of the Aβ(1-42) monomer in water using unbiased molecular dynamics simulations and spectral algorithms, Journal of Molecular Biology, 405(2), pp.570-583, 2011.
- Drineas, M. W. Mahoney, S. Muthukrishnan, and T. Sarlos, Faster Least Squares Approximation, Numerische Mathematik, 117(2), pp. 217-249, 2011.
- Tsourakakis, P. Drineas, E. Michelakis, I. Koutis, and C. Faloutsos, Spectral Counting of Triangles via Element-Wise Sparsification and Triangle-Based Link Recommendation, Journal of Social Network Analysis and Mining (SNAM), 1(2), pp. 75-81, 2011.
- Drineas and A. Zouzias, A note on element-wise matrix sparsification via a matrix-valued Bernstein inequality, Information Processing Letters, 111, pp. 385-389, 2011.

- Drineas and M. W. Mahoney, Effective Resistances, Statistical Leverage, and Applications to Linear Equation Solving, arXiv1005:3097, 2010.
- Paschou, J. Lewis, A. Javed, and P. Drineas, Ancestry Informative Markers for Fine-Scale Individual Assignment to Worldwide Populations, Journal of Medical Genetics, doi:10.1136/jmg.2010.078212, 2010.
- Drineas, J. Lewis, and P. Paschou, Inferring Geographic Coordinates of Origin for Europeans using Small Panels of Ancestry Informative Markers, PLoS ONE, 5(8):e11892, 2010.

- Acer, P. Drineas, and A. Abouzeid, Random walks in time-graphs, Proceedings of the Second International Workshop on Mobile Opportunistic Networking (MobiOpp), pp. 93-100, 2010.
- Boutsidis, A. Zouzias, and P. Drineas, Random Projections for k-means Clustering, Proc. of Neural Information Processing Systems (NIPS), 2010.
- Kupp, H. Huang, P. Drineas, and Y. Makris, Post-Production Performance Calibration in Analog/RF Devices, IEEE International Test Conference (ITC), 8.3.1-8.3.10, 2010.

- Boutsidis, M.W. Mahoney, and P. Drineas, Unsupervised Feature Selection for the k-means Clustering Problem, Proc. of Neural Information Processing Systems (NIPS), 2009.
- Boutsidis and P. Drineas, Random projections for the nonnegative least-squares problem, Linear Algebra and its Applications, 431, pp. 760-771, 2009.
- Dasgupta, P. Drineas, B. Harb, R. Kumar, and M. W. Mahoney, Sampling algorithms and coresets for lp regression, SIAM Journal on Computing, 38(5), pp. 2060-2078, 2009.
- W. Mahoney and P. Drineas, CUR matrix decompositions for improved data analysis, Proceedings of the National Academy of Sciences, 106(3), pp. 697-702, 2009.
- Tsourakakis, P. Drineas, E. Michelakis, I. Koutis, and C. Faloutsos, Spectral counting of triangles in power-law networks via element-wise sparsification, International Conference on Advances in Social Network Analysis and Mining (ASONAM), 2009.
- Boutsidis, M.W. Mahoney, and P. Drineas, An improved approximation algorithm for the column subset selection problem, Proc. of the 20th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 968-977, 2009.

- W. Mahoney, M. Maggioni, and P. Drineas, Tensor-CUR decompositions for tensor-based data, SIAM Journal on Matrix Analysis and Applications, 30(2), pp. 957-987, 2008.
- Drineas, M.W. Mahoney, and S. Muthukrishnan, Relative-error CUR matrix decompositions, SIAM Journal on Matrix Analysis and Applications, 30(2), pp. 844-881, 2008.
- Paschou, P. Drineas, J. Lewis, C. Nievergelt, D. Nickerson, J. Smith, P. Ridker, D. Chasman, R. Krauss, and E. Ziv, Tracing sub-structure in the European American population with PCA-informative markers, PLoS Genetics, 4(7), pp. 1-13, 2008.
- Boutsidis, M.W. Mahoney, and P. Drineas, Unsupervised feature selection for Principal Components Analysis, Proc. of the 14th Annual ACM Conference on Knowledge Discovery and Data Mining (KDD), pp. 61-69, 2008.
- Kupp, P. Drineas, M. Slamani, and Y. Makris, Confidence estimation in non-RF to RF correlation-based specification test compaction, Proc. of the 13th European Test Symposium (ETS), pp. 35-40, 2008.
- Dasgupta, P. Drineas, B. Harb, R. Kumar, and M. W. Mahoney, Sampling algorithms and coresets for lp regression, Proc. of the 19th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 932-941, 2008.

- Paschou, E. Ziv, E. Burchard, S. Choudhry, W. Rodriguez-Cintron, M. W. Mahoney, and P. Drineas, PCA-correlated SNPs for structure identification in worldwide human populations, PLOS Genetics, 3(9), pp. 1672-1686, 2007.
- Paschou, M. W. Mahoney, A. Javed, J. Kidd, A. Pakstis, S. Gu, K. Kidd, and P. Drineas, Intra- and inter-population genotype reconstruction from tagging SNPs, Genome Research, 17(1), pp. 96-107, 2007.
- Drineas and M. W. Mahoney, A randomized algorithm for a tensor-based generalization of the SVD, Linear Algebra and its Applications, 420, pp. 553-571, 2007.
- Drineas, M. W. Mahoney, and R. Kannan, Sampling sub-problems of heterogeneous max-cut problems and approximation algorithms, Random Structures and Algorithms,32(3), pp. 307-333, 2007.
- Dasgupta, P. Drineas, B. Harb, V. Josifovski, and M. Mahoney, Feature selection methods for text classification, Proc. of the 13th Annual ACM Conference on Knowledge Discovery and Data Mining (KDD), pp. 230-239, 2007.

2006

G.H. Golub, M.W. Mahoney, P. Drineas, and L.-H. Lim, MMDS 2006: bridging the gap between numerical linear algebra, theoretical computer science, and data applications, SIAM News, Oct 2006.

- Drineas, R. Kannan, and M. W. Mahoney, Fast monte carlo algorithms for matrices I: approximating matrix multiplication, SIAM Journal on Computing, 36(1), pp. 132-157, 2006.
- Drineas, R. Kannan, and M. W. Mahoney, Fast monte carlo algorithms for matrices II: computing a low rank approximation to a matrix, SIAM Journal on Computing, 36(1), pp. 158-183, 2006.
- Drineas, R. Kannan, and M. W. Mahoney, Fast monte carlo algorithms for matrices III: computing a compressed approximate matrix decomposition, SIAM Journal on Computing, 36(1), pp. 184-206, 2006.
- Almukhaizim, P. Drineas, and Y. Makris, Entropy-driven parity tree selection for low-overhead concurrent error detection in finite state machines, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 25(8), pp. 1547-1554, 2006.
- Drineas, M. W. Mahoney, and S. Muthukrishnan, Subspace sampling and relative error matrix approximation: column-based methods, Proc. of APPROX-RANDOM, pp. 316-326, 2006.
- Drineas, M. W. Mahoney, and S. Muthukrishnan, Subspace sampling and relative error matrix approximation: column-row-based methods, Proc. of the 14th Annual European Symposium on Algorithms (ESA), pp. 304-314, 2006.
- Drineas, M. W. Mahoney, and S. Muthukrishnan, Polynomial time algorithm for column-row based relative error low-rank matrix approximation, DIMACS Technical Report 2006-04, 2006.
- Drineas, A. Javed, M. Magdon-Ismail, G. Pandurangan, R. Virrankoski, and A. Savvides, Distance matrix reconstruction from incomplete distance information for sensor network localization, Proc. of the 3rd Annual IEEE Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), pp. 536-544, 2006.
- Drineas and M. W. Mahoney, Randomized algorithms for matrices and massive data sets, Proc. of the 32nd Annual Conference on Very Large Data Bases (VLDB), p. 1269, 2006.
- W. Mahoney, M. Maggioni, and P. Drineas, Tensor-CUR decompositions for tensor-based data, Proc. of the 12th Annual ACM Conference on Knowledge Discovery andData Mining (KDD), pp. 327-336, 2006.
- Drineas, M. W. Mahoney, and S. Muthukrishnan, Sampling algorithms for l2 regression and applications, Proc. of the 17th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 1127-1136, 2006.

- Drineas and M. W. Mahoney, On the Nystrom method for approximating a Gram matrix for improved kernel-based learning, Journal of Machine Learning Research 6, pp. 2153-2175, 2005.
- Almukhaizim, P. Drineas, and Y. Makris, Compaction-based concurrent error detection for digital circuits, Microelectronics Journal, 36(9), pp. 856-862, Elsevier, 2005.
- Freedman and P. Drineas, Energy minimization via graph cuts: settling what is possible, Proc. of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), pp. 939-946, 2005.
- Drineasand M. W. Mahoney, Approximating a Gram matrix for improved kernel-based learning, Proc. of the 18th Annual Symposium on Computational Learning Theory (COLT), pp. 323-337, 2005.
- Drineas, R. Kannan, and M. W. Mahoney, Sampling sub-problems of heterogeneous max-cut problems and approximation algorithms, Proc. of the 22nd Annual Symposium on Theoretical Aspects of Computer Science (STACS), Lecture Notes in ComputerScience 3404, pp. 57-68, 2005.

- Drineas, R. Kannan, A. Frieze, S. Vempala, and V. Vinay, Clustering of large graphs via the singular value decomposition, Machine Learning (56), pp. 9-33, 2004.
- Akcoglu, P. Drineas, and M. Kao, Fast universalization of investment strategies, SIAM Journal on Computing 34(1), pp. 1-22, 2004.
- Drineas, M. Krishnamoorthy, D. Sofka, and B. Yener, Studying E-mail graphs for intelligence monitoring and analysis in the absence of semantic information, Proc. of the Symposium on Intelligence and Security Informatics, Lecture Notes in Computer Science 3073, pp. 297-306, 2004.
- Drineas, Pass efficient algorithms for approximating large matrices, Mathematisches Forschungsinstitut Oberwolfach (MFO) Workshop on Approximation Algorithms for NP-Hard Problems, Oberwolfach, 2004.
- Almukhaizim, P. Drineas, and Y. Makris, Cost-driven selection of parity trees, Proc. of the IEEE VLSI Test Symposium (VTS), pp. 319-324, 2004.
- Almukhaizim, P. Drineas, and Y. Makris, Concurrent error detection for combinational and sequential logic via output compaction, Proc. of the IEEE International Symposium on Quality Electronic Design (ISQED), pp. 459-464, 2004.
- Almukhaizim, P. Drineas, and Y. Makris, On concurrent error detection with bounded latency in FSMs, Proc. of the IEEE Design Automation and Test in Europe Conference(DATE), pp. 596-601, 2004.

- Drineas and Y. Makris, SPaRe: selective partial replication for concurrent fault detection in FSMs, IEEE Transactions on Instrumentation and Measurement, 52(6), pp. 1729-1737, 2003.
- Drineas, E. Drinea, and P. Huggins, An experimental evaluation of a monte carlo algorithm for singular value decomposition, Y. Manolopoulos et. al. (Eds.): Revised Selected Papers from the 8th Panhellenic Conference on Informatics, Lecture Notes in Computer Science 2563, pp. 279-296, 2003.
- Drineas and R. Kannan, Pass efficient algorithms for approximating large matrices, Proc. of the 14th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 223-232, 2003.
- Almukhaizim, P. Drineas, and Y. Makris, On Compaction-based concurrent error detection, Proc. of the IEEE On-Line Test Symposium, pp. 157, 2003.
- Drineas and Y. Makris, Independent test sequence compaction through integer programming, Proc. of the IEEE International Conference on Computer Design (ICCD), pp. 380-386, 2003.
- Drineas and Y. Makris, Non-intrusive concurrent error detection in FSMs through State/Output compaction and monitoring via parity trees, Proc. of the Design Automation and Test in Europe Conference (DATE), pp. 1164-1165, 2003.
- Drineas and Y. Makris, SPaRe: selective partial replication for concurrent fault detection in FSMs, Proc. of the IEEE International Conference on VLSI Design, pp. 84-91, 2003.
- Drineas and Y. Makris, On the Compaction of Independent Test Sequences for Sequential Circuits, IEEE European Test Workshop (ETW), 2003.
- Drineas and Y. Makris, Concurrent fault detection in random combinational logic, Proc. of the IEEE International Symposium on Quality Electronic Design (ISQED), pp. 425-430, 2003.

- Drineas, I. Kerenidis, and P. Raghavan, Competitive recommendation systems, Proc. of the 34th ACM Symposium on Theory of Computing (STOC), pp. 82-90, 2002.
- Akcoglu, P. Drineas, and M. Kao, Fast universalization of investment strategies with provably good relative returns, Proc. of the 29th International Colloquium on Automata, Languages and Programming (ICALP), pp. 888-900, 2002.
- Drineas and Y. Makris, Non-intrusive design of concurrently self-testable FSMs, Proc. of the IEEE Asian Test Symposium (ATS), pp. 33-38, 2002.
- Drineas and Y. Makris, Non-intrusive design of concurrently self-testable FSMs, IEEE North Atlantic Test Workshop (NATW), Montauk NY, USA, 2002.

- Drinea, P. Drineas, and P. Huggins, A randomized singular value decomposition algorithm for image processing applications, Proc. of the 8th Panhellenic Conference on Informatics, pp. 278-288, 2001.
- Drineas and R. Kannan, Fast monte carlo algorithms for approximate matrix multiplication, Proc. of the 42nd IEEE Symposium on Foundations of Computer Science (FOCS), pp. 452-459, 2001.

- Drineas, R. Kannan, A. Frieze, S. Vempala, and V. Vinay, Clustering in large graphs and matrices, Proc. of the 10th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 291-299, 1999.

## Tutorials

Randomized Algorithms in Linear Algebra and Applications, Workshop on Algorithms for Modern Massive Datasets
(MMDS), Jun 2010.

Information retrieval and data mining: a linear algebraic perspective, Institute for Pure and Applied
Mathematics, UCLA, Sep 2007 (a podcast of the talk is also available).

Randomized algorithms for matrices and massive datasets, SIAM Conference on Data Mining (SDM), Apr 2006.

Randomized algorithms for matrices and massive datasets, ACM International Conference on Knowledge Discovery and
Data Mining (KDD), Aug 2005.

## Slides from various presentations

Randomized Algorithms in Linear Algebra and the Column Subset Selection Problem

Dimensionality reduction in the analysis of human genetics data

Identifying ancestry informative markers via the singular value decomposition

Randomized matrix algorithms and their applications

## Teaching (since January 2003)

- CSCI 2200, Foundations of Computer Science (FoCS), Spring 2016
- CSCI 4966 & 6220, Randomized Algorithms, Spring 2016
- CSCI 4966 & 6967, Foundations of Data Science (FoDS), Spring 2015
- CSCI 6962, Randomized Algorithms, Spring 2013
- CSCI 2200, Foundations of Computer Science (FoCS), Spring 2013
- CSCI 6962, Randomized Algorithms, Spring 2012
- CSCI 2400, Models of Computation, Spring 2012
- CSCI 6962, Randomized Algorithms, Spring 2010
- CSCI 2400, Models of Computation, Spring 2010
- CSCI 6962, Randomized Algorithms, Spring 2009
- CSCI 2400, Models of Computation, Spring 2009
- CSCI 6962, Randomized Algorithms, Spring 2008
- CSCI 2400, Models of Computation, Spring 2008
- CSCI 6962, Randomized Algorithms, Spring 2007
- CSCI 2400, Models of Computation, Spring 2007
- CSCI 6962, Randomized Algorithms, Spring 2006
- CSCI 2400, Models of Computation, Spring 2006
- CSCI 2400, Models of Computation, Spring 2005
- CSCI 4961, Network Flows and Linear Programming, Spring 2004
- CSCI 1200, Computer Science II, Spring 2004
- CSCI 6962, Randomized Algorithms, Fall 2003
- CSCI 1200, Computer Science II, Spring 2003

## Resume / CV

Petros Drineas

Associate Professor

Computer Science Department

Purdue University

305 N. University Street

West Lafayette

IN 47907-2107

USA

Education Yale University, New Haven CT

Ph.D. in Computer Science (advisor: Ravi Kannan), May 2003.

Yale University, New Haven CT

M.Phil. in Computer Science, May 1999.

Yale University, New Haven CT

M.Sc. in Computer Science, May 1998.

University of Patras, Greece

BS and M.Sc. in Computer Engineering, (advisor: Athanasios Tsakalidis), Jun 1997.

Appoint- Associate Professor

ments Purdue University, Jul 2016 - now

Associate Professor

Rensselaer Polytechnic Institute, Jan 2009 - Jun 2016

Adjunct Faculty

Department of Mathematics, North Carolina State University, Nov 2012 - now

Long-term visitor

Simons Institute for the Theory of Computing, University of California, Berkeley, Fall 2013

Program Director

National Science Foundation, Information and Intelligent Systems (IIS) Division and Computing and Communication
Foundations (CCF) Division, Oct 2010 - Nov 2011

Assistant Professor

Rensselaer Polytechnic Institute, Jan 2003 - Dec 2008

Visiting Assistant Professor

Institute of Pure & Applied Mathematics, University of California, Los Angeles, Sep 2007 -

Dec 2007

Visiting Research Scientist

Yahoo! Research, Jul 2006 - Sep 2006

Visiting Assistant Professor

Sandia National Laboratories, Aug 2005 - Dec 2005

Visiting Researcher

Microsoft Research Silicon Valley, Jul 2002

Summer Intern

Verity Inc., Silicon Valley CA, May 2001 - Aug 2001

Research Assistant

Yale University, Sep 1998 - Dec 2002

Teaching Assistant

Yale University, Sep 1998 - Dec 2002

Research Theory: The design and analysis of Randomized Numerical Linear Algebra algorithms

Interests (RandNLA).

Applications: Data mining, in particular the analysis of population genetics data, internet

data, and electronic circuit testing data.

Honors Near-Optimal Column-Based Matrix Reconstruction, which appeared in the 52nd IEEE

Symposium on Foundations of Computer Science (FOCS), was invited to the special issue of the SIAM Journal on
Computing for the top papers from FOCS 2011.

European Molecular Biology Organization (EMBO) Fellowship, 2010.

Best paper award, MobiOpp 2010.

Senior Member, Association for Computing Machinery, 2009.

European Molecular Biology Organization (EMBO) Fellowship, 2009.

Mentoring Excellence Award, Rensselaer Polytechnic Institute, 2009.

Outstanding Early Research Award, School of Science, Rensselaer Polytechnic Institute,

2007.

NSF CAREER Award, 2006.

- Tinsley Oden Visiting Faculty Fellowship, University of Texas at Austin, 2005.

- Total citations (according to Google Scholar): > 6, 400.
- h-index (according to Google Scholar): 38.
- i10-index (according to Google Scholar): 77.

- P. Buhlmann, P. Drineas, M. Kane, and M. van der Laan, Handbook of Big Data,

Journal Publications (Accepted)

- G. Stamatoyannopoulos, A. Bose, A. Teodosiadis, F. Tsetsos, A. Plantinga, N. Psatha,
- Zogas, E. Yannaki, P. Zalloua, K. K. Kidd, B. L. Browning, J. Stamatoyannopoulos,
- Paschou, and Petros Drineas, Genetics of the Peloponnesean Populations and the

Human Genetics (EJHG), 25(5), pp. 637-645, 2017.

- K. Fountoulakis, A. Kundu, E. Kontopoulou, and P. Drineas, A Randomized Rounding

(TKDD), 11(3), pp. 1-26, 2017.

- C. Iyer, H. Avron, G. Kollias, Y. Ineichen, C. Carothers, and P. Drineas, A Randomized

Computational Science, Journal of Computational Science, http://dx.doi.org/10.1016/

j.jocs.2016.09.007, 2016.

- N. J. Forde, A. S. Kanaan, J. Widomska, S. S. Padmanabhuni, E. Nespoli, J. Alexander, J. Rodriguez Arranz, S. Fan, R. Houssari, M. S. Nawaz, N. R. Zilhao, L. Pagliaroli,
- Rizzo, T. Aranyi, C. Barta, T. M. Boeckers, D. I. Boomsma, W. R. Buisman, J.
- Buitelaar, D. Cath, A. Dietrich, N. Driessen, P. Drineas, M. Dunlap, S. Gerasch,
- Glennon, B. Hengerer, O. A. van den Heuvel, C.e Jespersgaard, H. E. Moller, K. R.

- Tumer, D. Veltman, Y. D van der Werf, P. J. Hoekstra, A. Ludolph, and P. Paschou,

10, article 384, 2016.

- F. Tsetsos, S. S. Padmanabhuni, J. Alexander, I. Karagiannidis, M. Tsifintaris, A.

Tourette Syndrome and Attention Deficit Hyperactivity Disorder provides support for

a shared genetic basis, Frontiers in Neuroscience, 10, article 340, 2016.

- K. Clarkson, P. Drineas, M. Magdon-Ismail, M. W. Mahoney, X. Meng, and D. P. Woodruff,

2016.

- S. Paul, M. Magdon-Ismail, and P. Drineas, Feature Selection for Linear SVMs with

- M. W. Mahoney and P. Drineas, RandNLA: Randomized Numerical Linear Algebra,

- J. Alexander, O. Kalev, S. Mehrabian, L. Traykov, M. Raycheva, D. Kanakis, P. Drineas,
- I. Lutz, T. Strbel, T. Penz, M. Schuster, C. Bock, I. Ferrer, P. Paschou, and
- G. Kovacs, Familial early-onset dementia with complex neuropathological phenotype

- S. Paul and P. Drineas, Feature Selection for Ridge Regression with Provable Guarantees, Neural Computation, MIT Press Journals, 28, pp. 716-742, 2016.
- M. W. Mahoney and P. Drineas, Structural Properties Underlying high-quality Randomized Numerical Linear Algebra algorithms, CRC Handbook on Big Data, pp. 137-154,

- N. Nguyen, P. Drineas, and T. Tran, Tensor sparsification via a bound on the spectral

195-229, 2015.

- C. Boutsidis, A. Zouzias, M. W. Mahoney, and P. Drineas, Randomized Dimensionality

pp. 1045-1062, 2015.

- P. Paschou, P. Drineas1

Europe, Proceedings of the National Academy of Sciences, doi:10.1073/pnas.1320811111,

2014.

- P. Saurabh, C. Boutsidis, M. Magdon-Ismail, and P. Drineas, Random Projections

(TKDD), 8(4):22, 2014.

- C. Boutsidis, P. Drineas, and M. Magdon-Ismail, Near-Optimal Column-Based Matrix

- C. Boutsidis, P. Drineas, and M. Magdon-Ismail, Near-Optimal Coresets for LeastSquares Regression, IEEE Transactions on Information Theory, 59(10), 6880 - 6892,

- J. R. Hughey, P. Paschou, P. Drineas, D. Mastropaolo, D. M. Lotakis, P. A. Navas,
- Michalodimitrakis, J. A. Stamatoyannopoulos, and G. Stamatoyannopoulos, A European Population in Minoan Bronze Age Crete, Nature Communications, (4)1861

- P. Drineas, M. Magdon-Ismail, M. W. Mahoney, and D. Woodruff, Fast Approximation

13, pp. 3475-3506, 2012.

1Equal contribution with the first author.

- V. Stathias, G. Sotiris, I. Karagiannidis, G. Bourikas, G. Martinis, G. Papazoglou,
- Tavridou, N. Papanas, E. Maltezos, M. Theodoridis, V. Vargemezis, V. Manolopoulos, W. C. Speed, J. R. Kidd, K. K. Kidd, P. Drineas, P. Paschou, Exploring genomic

472-483, 2012.

- N. Kupp, H. Huang, P. Drineas, and Y. Makris, Improving Analog and RF Device

pp. 64-75, 2011.

- A. Javed, P. Drineas, M.W. Mahoney, and P. Paschou, Reconstructing the genome with

- J. Lewis, Z. Abas, C. Dadousis, D. Lykidis, P. Paschou, and P. Drineas, Tracing Cattle

6(4): e18007, 2011.

- U. Acer, P. Drineas, and A. Abouzeid, Connectivity in Time-Graphs, Pervasive and

- N. G. Sgourakis, M. Merced-Serrano, C. Boutsidis, P. Drineas, Z. Du, C. Wang, and
- E. Garcia, Atomic-level characterization of the ensemble of the Aβ(1−42) monomer

- C. Tsourakakis, P. Drineas, E. Michelakis, I. Koutis, and C. Faloutsos, Spectral Counting of Triangles via Element-Wise Sparsification and Triangle-Based Link Recommendation, Journal of Social Network Analysis and Mining (SNAM), 1(2), pp. 75–81,

- P. Drineas, M. W. Mahoney, S. Muthukrishnan, and T. Sarlos, Faster least squares

- P. Drineas and A. Zouzias, A note on element-wise matrix sparsification via a matrixvalued Bernstein inequality, Information Processing Letters, 111, pp. 385-389, 2011.
- P. Paschou, J. Lewis, A. Javed, and P. Drineas, Ancestry Informative Markers for FineScale Individual Assignment to Worldwide Populations, Journal of Medical Genetics,

- P. Drineas, J. Lewis, and P. Paschou, Inferring Geographic Coordinates of Origin

e11892, 2010.

- H-G. D. Stratigopoulos, P. Drineas, M. Slamani, and Y. Makris, RF specification test

1002–1006, 2010.

- N. Kupp, P. Drineas, M. Slamani, and Y. Makris, On Boosting the Accuracy of Non-RF

Theory and Applications, 25(6), pp. 309-321, 2009.

- C. Boutsidis and P. Drineas, Random projections for the nonnegative least-squares

- A. Dasgupta, P. Drineas, B. Harb, R. Kumar, and M. W. Mahoney, Sampling algorithms and coresets for `p regression, SIAM Journal on Computing, 38(5), pp. 2060–

- M. W. Mahoney and P. Drineas, CUR matrix decompositions for improved data analysis, Proceedings of the National Academy of Sciences, 106(3), pp. 697–702, 2009.
- M. W. Mahoney, M. Maggioni, and P. Drineas, Tensor-CUR decompositions for tensorbased data, SIAM Journal on Matrix Analysis and Applications, 30(2), pp. 957–987,

- P. Drineas, M.W. Mahoney, and S. Muthukrishnan, Relative-error CUR matrix decompositions, SIAM Journal on Matrix Analysis and Applications, 30(2), pp. 844–881,

- P. Paschou, P. Drineas2

- Chasman, R. Krauss, and E. Ziv, Tracing sub-structure in the European American

- P. Paschou, E. Ziv, E. Burchard, S. Choudhry, W. Rodriguez-Cintron, M. W. Mahoney,

populations, PLOS Genetics, 3(9), pp. 1672-1686, 2007.

- P. Paschou, M. W. Mahoney, A. Javed, J. Kidd, A. Pakstis, S. Gu, K. Kidd, and
- Drineas, Intra- and inter-population genotype reconstruction from tagging SNPs,

- P. Drineas and M. W. Mahoney, A randomized algorithm for a tensor-based generalization of the SVD, Linear Algebra and its Applications, 420, pp. 553-571, 2007.
- P. Drineas, M. W. Mahoney, and R. Kannan, Sampling sub-problems of heterogeneous

32(3), pp. 307 – 333, 2007.

- P. Drineas, R. Kannan, and M. W. Mahoney, Fast monte carlo algorithms for matrices

157, 2006.

- P. Drineas, R. Kannan, and M. W. Mahoney, Fast monte carlo algorithms for matrices

36(1), pp. 158-183, 2006.

- P. Drineas, R. Kannan, and M. W. Mahoney, Fast monte carlo algorithms for matrices III: computing a compressed approximate matrix decomposition, SIAM Journal on

- S. Almukhaizim, P. Drineas, and Y. Makris, Entropy-driven parity tree selection for

on Computer-Aided Design of Integrated Circuits and Systems, 25(8), pp. 1547-1554,

2006.

- P. Drineas and M. W. Mahoney, On the Nystrom method for approximating a Gram

pp. 2153-2175, 2005.

- S. Almukhaizim, P. Drineas, and Y. Makris, Compaction-based concurrent error detection for digital circuits, Microelectronics Journal, 36(9), pp. 856-862, Elsevier, 2005.
- P. Drineas, R. Kannan, A. Frieze, S. Vempala, and V. Vinay, Clustering of large graphs

- K. Akcoglu, P. Drineas, and M. Kao, Fast universalization of investment strategies,

- P. Drineas and Y. Makris, SPaRe: selective partial replication for concurrent fault

pp. 1729-1737, 2003.

- P. Drineas, E. Drinea, and P. Huggins, An experimental evaluation of a monte carlo

Selected Papers from the 8th Panhellenic Conference on Informatics, Lecture Notes in

Computer Science 2563, pp. 279-296, 2003.

Journal Publications (submitted, available in ArXiv)

2Equal contribution with the first author.

- A. Kundu, P. Drineas, and M. Magdon-Ismail, Recovering PCA from Hybrid-(`1, `2)

- P. Drineas, I. Ipsen, E. Kontopoulou, and M. Magdon-Ismail, Structural Convergenece

- C. Boutsidis, P. Drineas, P. Kambadur, E. Kontopoulou, and A. Zouzias, A Randomized

Matrix, under review, 2016.

Conference Publications

- C. Iyer, C. Carothers, and P. Drineas, Randomized Sketching for Large-Scale Sparse

Large-Scale Systems (ScalA16), held in conjunction with the 2016 International Conference on High Performance Computing, Networking, Storage and Analysis (SC16),

2016.

- C. Iyer, H. Avron, G. Kollias, Y. Ineichen, C. Carothers, and P. Drineas, A Scalable

Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA15), held in

conjunction with the 2015 International Conference on High Performance Computing,

Networking, Storage and Analysis (SC15), 2015.

- A. Kundu, P. Drineas, and M. Magdon-Ismail, Approximating Sparse PCA from Incomplete Data, Proc. of Neural Information Processing Systems (NIPS), 2015.
- S. Paul, M. Magdon-Ismail, and P. Drineas, Column Selection via Adaptive Sampling,

- S. Paul, M. Magdon-Ismail, and P. Drineas, Feature Selection for Linear SVM with

- S. Paul and P. Drineas, Deterministic Feature Selection for Regularized Least Squares

of Knowledge Discovery in Databases (ECML-PKDD), LNCS 8725, pp. 533-548, 2014.

- S. Paul, C. Boutsidis, M. Magdon-Ismail, and P. Drineas, Random Projections and

Intelligence and Statistics (AISTATS), 2013.

- K. L. Clarkson, P. Drineas, M. Magdon-Ismail, M. W. Mahoney, X. Meng, and D. P. Woodruff,

Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2013.

- P. Drineas, M. Magdon-Ismail, M. W. Mahoney, and D. Woodruff, Fast Approximation

on Machine Learning (ICML), 2012.

- C. Boutsidis, P. Drineas, and M. Magdon-Ismail, Sparse Features for PCA-like Linear

- C. Boutsidis, P. Drineas, and M. Magdon-Ismail, Near-Optimal Column-Based Matrix

Science (FOCS), 2011.

- N. Kupp, H. Stratigopoulos, P. Drineas, and Y. Makris, On Proving the Efficiency of

2011.

- C. Boutsidis, A. Zouzias, and P. Drineas, Random Projections for k-means Clustering,

- N. Kupp, H. Huang, P. Drineas, and Y. Makris, Post-Production Performance Calibration in Analog/RF Devices, IEEE International Test Conference (ITC), 8.3.1-8.3.10,

- U. Acer, P. Drineas, and A. Abouzeid, Random walks in time-graphs, Proceedings of

pp. 93–100, 2010.

- C. Boutsidis, M. W. Mahoney, and P. Drineas, Unsupervised Feature Selection for the

2009.

- C. Tsourakakis, P. Drineas, E. Michelakis, I. Koutis, and C. Faloutsos, Spectral Counting of Triangles in Power-Law Networks via the Element-wise Sparsification, Proc.

(ASONAM), pp. 66–72, 2009.

- C. Boutsidis, M.W. Mahoney, and P. Drineas, An improved approximation algorithm for

on Discrete Algorithms (SODA), pp. 968–977, 2009.

- C. Boutsidis, M.W. Mahoney, and P. Drineas, Unsupervised feature selection for Principal Components Analysis, Proc. of the 14th Annual ACM Conference on Knowledge

- N. Kupp, P. Drineas, M. Slamani, and Y. Makris, Confidence Estimation in Non-RF

Test Symposium (ETS), pp. 35–40, 2008.

- A. Dasgupta, P. Drineas, B. Harb, R. Kumar, and M. W. Mahoney, Sampling algorithms and coresets for `p regression, Proc. of the 19th Annual ACM-SIAM Symposium

- A. Dasgupta, P. Drineas, B. Harb, V. Josifovski, and M. Mahoney, Feature selection

- H-G. D. Stratigopoulos, P. Drineas, M. Slamani, and Y. Makris, Non-RF to RF test

Symposium (VTS), pp. 9–14, 2007.

- P. Drineas, M. W. Mahoney, and S. Muthukrishnan, Subspace sampling and relative

pp. 316-326, 2006.

- P. Drineas, M. W. Mahoney, and S. Muthukrishnan, Subspace sampling and relative

European Symposium on Algorithms (ESA), pp. 304-314, 2006.

- P. Drineas, A. Javed, M. Magdon-Ismail, G. Pandurangan, R. Virrankoski, and A. Savvides, Distance matrix reconstruction from incomplete distance information for sensor

Ad Hoc Communications and Networks (SECON), pp. 536-544, 2006.

- P. Drineas and M. W. Mahoney, Randomized algorithms for matrices and massive data

1269, 2006.

- M. W. Mahoney, M. Maggioni, and P. Drineas, Tensor-CUR decompositions for tensorbased data, Proc. of the 12th Annual ACM Conference on Knowledge Discovery and

- P. Drineas, M. W. Mahoney, and S. Muthukrishnan, Sampling algorithms for `2 regression and applications, Proc. of the 17th Annual ACM-SIAM Symposium on Discrete

- D. Freedman and P. Drineas, Energy minimization via graph cuts: settling what is

Recognition (CVPR), pp. 939-946, 2005.

- P. Drineas and M. W. Mahoney, Approximating a Gram matrix for improved kernelbased learning, Proc. of the 18th Annual Symposium on Computational Learning

- P. Drineas, R. Kannan, and M. W. Mahoney, Sampling sub-problems of heterogeneous

on Theoretical Aspects of Computer Science (STACS), Lecture Notes in Computer

Science 3404, pp. 57-68, 2005.

- P. Drineas, M. Krishnamoorthy, D. Sofka, and B. Yener, Studying E-mail graphs for

the Symposium on Intelligence and Security Informatics, Lecture Notes in Computer

Science 3073, pp. 297-306, 2004.

- S. Almukhaizim, P. Drineas, and Y. Makris, Cost-driven selection of parity trees, Proc.

- S. Almukhaizim, P. Drineas, and Y. Makris, Concurrent error detection for combinational and sequential logic via output compaction, Proc. of the IEEE International

- S. Almukhaizim, P. Drineas, and Y. Makris, On concurrent error detection with bounded

(DATE), pp. 596-601, 2004.

- P. Drineas and R. Kannan, Pass Efficient Algorithms for Approximating Large Matrices, Proc. of the 14th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA),

- S. Almukhaizim, P. Drineas, and Y. Makris, On Compaction-based concurrent error

- P. Drineas and Y. Makris, On the compaction of independent test sequences for sequential circuits, Proc. of the IEEE International Conference on Computer Design (ICCD),

- P. Drineas and Y. Makris, Non-intrusive concurrent error detection in FSMs through

- P. Drineas and Y. Makris, SPaRe: selective partial replication for concurrent fault

84-91, 2003.

- P. Drineas and Y. Makris, On the Compaction of Independent Test Sequences for Sequential Circuits, IEEE European Test Workshop (ETS), Maastricht, Netherlands,

- P. Drineas and Y. Makris, Concurrent fault detection in random combinational logic,

pp. 425-430, 2003.

- P. Drineas, I. Kerenidis, and P. Raghavan, Competitive recommendation systems, Proc.

- K. Akcoglu, P. Drineas, and M. Kao, Fast universalization of investment strategies

Automata, Languages and Programming (ICALP), pp. 888-900, 2002.

- P. Drineas and Y. Makris, Non-intrusive design of concurrently self-testable FSMs,

- P. Drineas and Y. Makris, Non-intrusive design of concurrently self-testable FSMs,

- E. Drinea, P. Drineas, and P. Huggins, A randomized singular value decomposition

on Informatics, pp. 278-288, 2001.

- P. Drineas and R. Kannan, Fast monte carlo algorithms for approximate matrix multiplication, Proc. of the 42nd IEEE Symposium on Foundations of Computer Science

- P. Drineas, R. Kannan, A. Frieze, S. Vempala, and V. Vinay, Clustering in large graphs

Abstracts & Technical Reports

- A. Bose, D. E. Platt, L. Parida, P. Paschou, P. Drineas, Genetic Variation reveals

Meeting of the American Society of Human Genetics, 2016. Selected for platform

presentation.

- A. Plantinga, F. Tsetsos, P. Paschou, P. Drineas, B. Browning, and G. Stamatoyannopoulos, Identity by descent analysis reveals fine-scale population structure in Crete,

- P. Paschou, I. Karagiannidis, A. Tsirigoti, A. Stampoliou, V. Papadopoulou, V. G. Manolopoulos, J. R. Kidd, K. K. Kidd, and P. Drineas, Evaluation of the HapMap dataset as

Genetics, 2010.

- J. Lewis, Z. Abas, C. Dadousis, D. Lykidis, P. Paschou, and P. Drineas, Tracing The

on Genetics Applied to Livestock Production, 2010. Selected for platform presentation.

- P. Paschou, J. Lewis, and P. Drineas, Accurate inference of individual ancestry geographic coordinates within Europe using small panels of genetic markers, Annual Meeting of the American Society of Human Genetics, 2009.
- P. Paschou, J. Lewis, A. Javed, and P. Drineas, Using principal components analysis to

of Human Genetics, 2008.

- P. Paschou, E. Ziv, E. G. Burchard, M. W. Mahoney, and P. Drineas, PCA-correlated

the American Society of Human Genetics, 2007.

- P. Paschou, M. W. Mahoney, A. Javed, J. R. Kidd, A. J. Pakstis, S. Gu, K. K. Kidd,

Annual Meeting of the American Society of Human Genetics, 2006. Selected for

platform presentation.

- P. Drineas, M. W. Mahoney, and S. Muthukrishnan, Polynomial time algorithm for

Report 2006-04, 2006.

- P. Drineas, Pass efficient algorithms for approximating large matrices, Mathematisches

NP-Hard Problems, Oberwolfach, Germany, 2004.

News

Articles 1. E. Gallopoulos, P. Drineas, I. Ipsen, and M. W. Mahoney, RandNLA, Pythons, and the

CUR for your Data problems, SIAM News, p. 7, February 2016.

- A brief interview including my thoughts on Linear Algebra appeared in Kuldeep Singh’s

//drineas.org.

- Numerous news articles have covered my June 2014 paper in the Proceedings of the

relevant articles is available at http://drineas.org.

- Harnessing the Petabyte: Data Science Research Center at Rensselaer Polytechnic

Mary L. Martialay, RPI Press Release, Sep 2013.

(Available at http://news.rpi.edu/content/2013/09/06/harnessingpetabyte-data-science-research-center-explores

-cloud-computing-and?destination=node/40180)

- DNA Analysis Unearths Origins of Minoans, the First Major European Civilization by

(Available at http://news.rpi.edu/luwakkey/3181)

- Study Helps Pinpoint Genetic Variations in European Americans (by Gabrielle DeMarco), RPI Press Release, Aug 2008.

- Computer Program Reveals Anyone’s Ancestry (by Gabrielle DeMarco), featured at

(Available at http://www.livescience.com/health/080404-bts-drineas.html)

- Tracing Your Ancestry: Computer Program Accurately Analyzes Anonymous DNA

(Available at http://www.sciencedaily.com/releases/2007/09/070921071744.htm)

- DNA Markers and Computer Science Methodology Can be Used to Trace Individual

(Available at http://scitizen.com/stories/Biotechnology/2007/10/DNA-Markers

-and-Computer-Science-Methodology-Can-be-Used-to-Trace-Individual-Ancestry/)

- G.H. Golub, M.W. Mahoney, P. Drineas, and L.-H. Lim, MMDS 2006: bridging the gap

SIAM News, Oct 2006.

Teaching

(The last column reflects the Summary Evaluation Adjusted Score from the IDEA report.

The maximum score is five.)

Date Number Title Enrol. IDEA

2003 Spring CSCI-1200 Computer Science II 140 3.8

2003 Fall CSCI-6962 Randomized Algorithms 12 4.3

2004 Spring CSCI-1200 Computer Science II 206 4.0

2004 Spring CSCI-4961 Network Flows & Linear Programming 18 4.1

2005 Spring CSCI-2400 Models of Computations 99 4.0

2006 Spring CSCI-2400 Models of Computations 63 4.1

2006 Spring CSCI-6962 Randomized Algorithms 15 4.6

2007 Spring CSCI-2400 Models of Computations 69 4.1

2007 Spring CSCI-6962 Randomized Algorithms 11 4.4

2008 Spring CSCI-2400 Models of Computations 102 4.4

2008 Spring CSCI-6962 Randomized Algorithms 6 5

2009 Spring CSCI-2400 Models of Computations 78 4.4

2009 Spring CSCI-6962 Randomized Algorithms 8 4.9

2010 Spring CSCI-2400 Models of Computations 79 4.5

2010 Spring CSCI-6962 Randomized Algorithms 10 5

2012 Spring CSCI-2400 Models of Computations 77 4.4

2012 Spring CSCI-6962 Randomized Algorithms 12 5

2013 Spring CSCI-2200 Foundations of Computer Science 95 4.3

2013 Spring CSCI-2400 Models of Computations 54 4.1

2013 Spring CSCI-6962 Randomized Algorithms 14 4.6

2015 Spring CSCI-4966/6967 Foundations of Data Science 23 4.7

2016 Spring CSCI-2200 Foundations of Computer Science 198 4.4

2016 Spring CSCI-6962 Randomized Algorithms 31 4.9

2016 Fall CS-59000 Randomized Algorithms in NLA 11 4.9

Graduated Ph.D. StudentsPhD

Students Asif Javed, graduated December 2008

Utku Gunay Acer, graduated August 2009

Jamey Lewis, graduated September 2010

Christos Boutsidis, graduated May 2011 (awarded the 2011 Robert McNaughton Prize)

Saurabh Paul, graduated May 2015

Abhisek Kundu, graduated Dec 2015

Nivas Nambirajan, graduated Dec 2015

Current Ph.D. Students

Chander Iyer, joined Sep 2012

Aritra Bose, joined Sep 2014

Eugenia Kontopoulou, joined Sep 2015

Agniva Chowdhury, joined Jan 2017

Ph.D. Committee Memberships

Kevin Cheng (advisor: Ravi Kannan, Yale University)

John Holodnak (advisor: Ilse Ipsen, North Carolina State University)

Thomas Wentworth (advisor: Ilse Ipsen, North Carolina State University)

Chris Stuetzle (advisor: Barbara Cutler)

Nabhendra Bisnik (advisor: Alhussein Abouzeid)

Evrim Acar (advisor: Bulent Yener)

Utku Gunay Acer (advisor: Alhussein Abouzeid)

Victor Boyarshinov (advisor: Malik Magdon-Ismail)

Bugra Caskurlu (advisor: Malik Magdon-Ismail)

Ali Civril (advisor: Malik Magdon-Ismail)

Karlton Sequeira (advisor: Mohammed Zaki)

Tutorials (Keynote talks and tutorials.)

& Keynotes 1. Summer School (lecturer): RandNLA: Randomization in Numerical Linear Algebra, Institute for Advanced Study (IAS) and the Park City Mathematics Institute

(PCMI) Graduate Summer School 2016: The Mathematics of Data, Midway, Utah,

Jul 2016.

- Invited Tutorial: RandNLA: Randomization in Numerical Linear Algebra, SIAM

- Summer School (organizer and lecturer): RandNLA: Randomization in Numerical Linear Algebra, Gene Golub SIAM Summer School (G2S3), Delphi, Greece, Jun

- Keynote Speaker: RandNLA: Randomization in Numerical Linear Algebra, SIAM

- Tutorial: Past, Present and Future of Randomized Numerical Linear Algebra , Big

- Tutorial: Mining Massive Datasets: a (Randomized) Linear Algebraic Approach,

“Massive Datasets” 2012-2013 program, Sep 2012.

- Keynote Speaker: Randomized Algorithms in Linear Algebra, SIAM Conference on

- Keynote Speaker: Randomized Algorithms in Data Mining: a Linear Algebraic

May 2012.

- Keynote Speaker: Randomized Algorithms for Low-Rank Approximations and Data

in conjunction with the Neural Information Processing Systems Conference, 2010.

- Tutorial: Randomized Algorithms in Linear Algebra and Applications, Workshop on

- Keynote Speaker: Randomized algorithms for the least-squares approximation problem, Midwest Theory day, University of Michigan, Ann Arbor, May 2008.
- Tutorial: Information retrieval and data mining: a linear algebraic perspective, Mathematics of Knowledge and Search Engines, Institute for Pure and Applied Mathematics,

- Tutorial: Randomized algorithms for matrices and massive datasets, VLDB, Sep 2006.
- Tutorial: Randomized algorithms for matrices and massive datasets, SIAM Conference on Data Mining (SDM), Apr 2006.
- Tutorial: Randomized algorithms for matrices and massive datasets, ACM International Conference on Knowledge Discovery and Data Mining (KDD), Aug 2005.

Talks 16. Dimensionality reduction in the analysis of human genetics data, Math-Bio Seminar,

University of Pennsylvania, Oct 2016.

- Leverage Scores, Statistics Colloquium, University of Chicago, Oct 2016.
- An approximation algorithm for Sparse PCA, Theory Seminar, Purdue University, Sep

- RandNLA: Randomization in Numerical Linear Algebra, Computer Science Colloquium, Washington University St. Louis, Sep 2016.
- RandNLA: Randomization in Numerical Linear Algebra, Machine Learning Day,

- Leverage Scores in Data Analysis, Mathematical Institute, Oxford University, May

- RandNLA: Randomization in Numerical Linear Algebra, Workshop on Optimization

- RandNLA: Randomization in Numerical Linear Algebra, Computer Science Colloquium, Purdue University, Nov 2014.
- Identifying Influential Entries in a Matrix, Yahoo Labs New York, Nov 2014.
- RandNLA: Randomization in Numerical Linear Algebra, Computational Math Colloquium, University of Waterloo, Nov 2014.
- Identifying Influential Entries in a Matrix, Householder Symposium XIX, Spa, Belgium,

- Leverage scores, School of Mathematics, University of Edinburgh, Apr 2014.
- RandNLA: Randomization in Numerical Linear Algebra, Computer Science Department, University of Edinburgh, Apr 2014.
- Leverage Scores in Data Analysis, International Computer Science Institute (ICSI),

- RandNLA: Randomization in Numerical Linear Algebra, SKYTREE, The Machine

- Leverage Scores in Data Analysis, Neyman Seminar, Department of Statistics, University of California Berkeley, Nov 2013.
- RandNLA: Randomization in Numerical Linear Algebra, Workshop on Succinct Data

- RandNLA: Randomization in Numerical Linear Algebra, Simons Foundation Workshop on Computer Science Issues in Big Data, Apr 2013.
- RandNLA: Randomization in Numerical Linear Algebra, Workshop celebrating Ravi

- Randomized Algorithms in Numerical Linear Algebra, NSF workshop on Big Data:

- RandNLA: Randomization in Numerical Linear Algebra, DARPA Workshop on Big

- Leverage Scores, Numerical Analysis Seminar, North Carolina State University, Nov

- Randomized Algorithms in Linear Algebra and Applications in Data Analysis, Computer Science and Artificial Intelligence Laboratory (CSAIL), MIT, Sep 2012.
- Leverage Scores, Scientific Computing and Numerics (SCAN) Seminar, Cornell University, Sep 2012.
- Randomized Algorithms in Linear Algebra and the Column Subset Selection Problem,

- Dimensionality reduction in the analysis of human genetics data, Bioinformatics Seminar, MIT, Apr 2011.
- Randomized matrix algorithms, Theory Colloquium, University of Maryland College

- Randomized matrix algorithms and their applications, Special Session on Random Matrix Theory and Applications in 2010 Spring Western Sectional Meeting of the American Mathematical Society, Apr 2010.
- Sampling algorithms for `2 regression, Theory Seminar, University of Toronto, Nov

- Randomized Algorithms in Linear Algebra, SIAM Conference on Applied Linear Algebra, Oct 2009.
- Dimensionality Reduction in the Analysis of Human Genetics Data, DIMACS Workshop on Algorithmics in Human Population-Genomics, Apr 2009.
- Randomized Algorithms for Matrix Computations and Applications to Data Mining,

- Approximating a tensor as a sum of rank-one components, NSF Workshop on Future

- Randomized Algorithms for Matrix Computations and Applications to Data Mining,

- Randomized Algorithms for Linear Algebraic Computations and Applications to Network Analysis, Workshop on New Mathematical Frontiers in Network Multi-Resolution

- The Column Subset Selection Problem: Theory and Applications, Computer Science

- Randomized Algorithms for Matrix Computations and Applications to Data Mining,

- The Column Subset Selection Problem, Householder Symposium XVII, Zeuthen, Germany, Jun 2008.
- Randomized Algorithms for Matrix Computations and Applications to Data Mining,

- Randomized Algorithms for Matrix Computations and Applications to Data Mining,

- Identifying ancestry informative markers via Principal Components Analysis, Workshop on Search and Knowledge Building for Biological Datasets, Institute for Pure and

- Sampling algorithms for `2 regression and the column subset selection problem, Applied

- Deterministic and randomized algorithms for column subset selection, NumAn2007

- From the singular value decomposition of matrices to CUR-type decompositions, Colloquium, Max Planck Institute for Informatics, Aug 2007.
- Fast randomized algorithms for least squares approximations, Theory colloquium, Max

- Fast randomized algorithms for least squares approximations, International Congress

- From the singular value decomposition of matrices to CUR-type decompositions: algorithms and applications, Colloquium, Computer Science Department, Dartmouth University, Apr 2007.
- Sampling algorithms and coresets for `2 regression and applications, Princeton Theory

- From the singular value decomposition of matrices to CUR-type decompositions, New

- From the singular value decomposition of matrices to CUR-type decompositions, General Electric Research Division, Niskayuna, Nov 2006.
- Subspace sampling and relative error matrix approximation, Workshop on Algorithms

- Subspace sampling: coresets for `2 regression problems, Bertinoro workshop on spaceconscious algorithms, Jun 2006.
- From the singular value decomposition of matrices to CUR-type decompositions: algorithms and applications, Bioinformatics Colloquium, Rensselaer Polytechnic Institute,

- Approximating a matrix with submatrices: algorithms and applications, Theory Colloquium, Computer Science Department, Yale University, Apr 2006.
- A relative-error CUR decomposition for matrices and its data applications, Theory

- A relative-error CUR decomposition for matrices and its data applications, Theory

- CUR matrix decompositions for improved data analysis, Yahoo! Research, Oct 2005.
- Randomized algorithms for matrices and applications, Sandia National Laboratories,

- Sampling algorithms for `2 regression and applications, Dagstuhl Seminar on Sublinear

- Randomized algorithms for matrices and applications, IBM Research, Almaden, May

- Monte-carlo algorithms for matrices and massive datasets, Theory Colloquium, Computer Science Department, Stanford University, May 2005.
- The CUR matrix decomposition and its applications to algorithm design and massive data sets, Colloquium, Computer Science Department, Rutgers University and

- A Novel matrix decomposition with applications to algorithm design and massive data

Ann Arbor, Sep 2004.

- Fast monte-carlo algorithms for common matrix operations, Colloquium, Computer

- Randomized algorithms for matrix operations, Colloquium, Computer Engineering and

- Pass-efficient algorithms for approximating large matrices, Mathematisches Forschungsinstitut Oberwolfach (MFO) Workshop on Approximation Algorithms for NP-Hard Problems, Jun 2004.
- Computing sketches of matrices efficiently and privacy preserving data mining, DIMACS Workshop on Privacy Preserving Data Mining, Mar 2004.
- Randomized algorithms for matrix operations, Colloquium, Department of Mathematics, Rensselaer Polytechnic Institute, Feb 2004.
- Pass efficient algorithms for matrix operations and max-2-CSP problems, NEC Research, Princeton, Jul 2003.
- Pass efficient algorithms for matrix approximations, Colloquium, Department of Computer Science, Brown University, Mar 2002.
- Pass efficient algorithms for matrix approximations, Colloquium, Department of Computer Science, Rensselaer Polytechnic Institute, Feb 2002.
- Pass efficient algorithms for matrix approximations, Theory Colloquium, Department

- Randomized algorithms for approximate matrix multiplication and singular value decomposition, Theory Colloquium, Department of Computer Science, Brown University,

- Fast monte carlo algorithms for matrix multiplication, DIMACS Workshop on Sublinear Algorithms, Sep 2000.
- A fast monte carlo singular value decomposition algorithm, Theory Colloquium, Department of Computer Science, Yale University, Apr 1999.

- (PI: Huo, co-PI Drineas)“Workshop on Theoretical Foundations of Data Science

- (PI: Ipsen, co-PI Drineas)“RandNLA: Randomization in Numerical Linear Algebra”, National Science Foundation (NSF), $25,000, 2015.
- (co-PIs: Drineas, Gallopoulos, Ipsen, Mahoney)“RandNLA: Randomization in

$85,000, 2015.

- (PI Mahoney, co-PI Drineas), “BIGDATA:F:DKA:Collaborative Research: Randomized Numerical Linear Algebra (RandNLA) for multi-linear and non-linear data”,

- (PI Drineas), “III: Small: Fast and Efficient Algorithms for Matrix Decompositions

2013 – 2016.

- (PI Drineas, co-PIs Carothers, Garcia, Yener, and Zaki), “III: Medium: Mining petabytes of data using cloud computing and a massively parallel cyberinstrument”,

- (PI Drineas), “Intergovernmental Mobility Assignment”, National Science Foundation (NSF), $225,000, 2010-2011.
- (PI Drineas, co-PI Saunders), “Randomized Algorithms in Linear Algebra and

$450,000, 2010 – 2013.

- (PI Drineas), “Fast and Efficient Randomized Algorithms for Solving Laplacian Systems of Linear Equations and Sparse Least Squares Problems”, National Science Foundation (NSF), $323,000, 2010 – 2013.
- (PI Drineas), European Molecular Biology Organization (EMBO) short term fellowship, $12,000, Jun - Aug 2010.
- (PI Makris, co-PI Drineas), “Collaborative Research: Correlation Mining and its

in Analog/RF Circuits”, National Science Foundation (NSF), $450,000, 2009 – 2012.

- (PI Drineas), European Molecular Biology Organization (EMBO) short term fellowship, $12,000, Jun - Aug 2009.
- (PI Drineas), “Extracting PCA-correlated SNPs from the Human Genome Diversity

- (PI Isler, co-PI Drineas, co-PI Trinkle), “Research/Education Infrastructure

$350,000, 2007 – 2010.

- (PI Makris, co-PI Drineas), “Statistical Analysis of Parametric Measurements and

$150,000, 2007 – 2010.

- (PI Drineas, co-PI Abouzeid), “NeTS-NBD: Towards a Disconnection-Tolerant,

- (PI Drineas),Yahoo! Research Gift, $18,000, 2006.
- (PI Drineas), “Research Experience for Undergraduates (REU) Supplement: Implementing Algorithms for tSNP selection in MatLab”, National Science Foundation

- (PI Drineas), “CAREER: A Framework for Mining Multimode, Non-Homogeneous

Foundation (NSF), $400,000, 2006 – 2011.

- (PI Golub, co-PIs Drineas, Mahoney, and Lim), “Workshop on Algorithms for

Boards

- Member, Gene Golub SIAM Summer School Committee, Jan 2018 – now.
- Editorial Board Member, SIAM Journal on Scientific Computing, Jan 2017 – now.
- Editorial Board Member, Applied and Computational Harmonic Analysis, Jan 2017 –

- Editor, Handbook of Big Data, CRC Press, Taylor & Francis Group, 2016.
- Editorial Board Member, SIAM Journal on Scientific Computing, Special Issue for

- Editorial Board Member, SIAM Journal on Matrix Analysis and Applications, Jan

- Editorial Board Member, Information and Inference: A Journal of the IMA, Feb 2014

- Editorial Board Member, PLoS ONE, May 2013 – now.
- Member, Committee for the Advancement of Theoretical Computer Science (CATCS),

Committee

Service 1. Senior Program Committee Member, ACM Conference on Information and Knowledge

Management, Nov 2017.

- Program Committee Member, ACM SIGKDD International Conference on Knowledge

- Program Committee Member, 16th IEEE International Workshop on High Performance Computational Biology, held in conjunction with IEEE IPDPS, May 2017.
- Invited Reviewer, Neural Information Processing Systems Conference, Dec 2016.
- Program Committee Member, ACM SIGKDD International Conference on Knowledge

- Organizing Committee Member, 5th Workshop on Algorithms for Modern Massive

- Chair, Workshop on Theoretical Foundations of Data Science (TFoDS), Apr 2016.
- Organizing Committee Member, Gene Golub SIAM Summer School (G2S3), Jun 2015.
- Program Committee Member, IEEE International Conference on Data Mining (ICDM),

- Program Committee Member, International Conference on Parallel Processing (ICPP),

- Organizing Committee Member, SIAM Conference on Applied Linear Algebra (ALA),

- Organizing Committee Member, Workshop on Optimization and Matrix Methods in

- Program Committee Member, IEEE International Conference on Data Mining (ICDM),

- Program Committee Member, International Conference on Parallel Processing (ICPP),

- Organizing Committee Member, 5th Workshop on Algorithms for Modern Massive

- Program Committee Member, ACM Symposium on Theory of Computing (STOC),

- NSF DMS Review Panel, 2014.
- NSF CCF Review Panel, 2014.
- Program Committee Member, ACM-SIAM Symposium on Discrete Algorithms (SODA),

- Invited Reviewer, Neural Information Processing Systems Conference, Dec 2013.
- Chair, Workshop on Succinct Data Representations and Applications, Simons Institute

- NSF IIS Review Panel, 2013.
- Vice Chair, IEEE International Conference on Data Mining (ICDM), Dec 2013.
- Program Committee Member, ACM SIGKDD International Conference on Knowledge

- NSF CCF Review Panel, 2012.
- NSF IIS Review Panel, 2012.
- Program Committee Member, International Conference on Pattern Recognition Applications and Methods, Feb 2013.
- Organizing Committee Member, Randomized Numerical Linear Algebra: Theory and

on Foundations of Computer Science (FOCS), Oct 2012.

- Invited Reviewer, Neural Information Processing Systems Conference, Dec 2012.
- Program Committee Member, ACM International Conference on Information and

- Program Committee Member, International Conference on Data Technologies and Applications, Jul 2012.
- Organizing Committee Member, Workshop on Algorithms for Modern Massive Datasets

- Program Committee Member, Workshop on Large-scale Data Mining: Theory and Applications, to be held in conjunction with the ACM SIGKDD Conference on Knowledge

- Program Committee Member, International Conference on Pattern Recognition Applications and Methods, Feb 2012.
- Program Committee Member, ACM SIGKDD International Conference on Knowledge

- Invited Reviewer, Neural Information Processing Systems Conference, Dec 2010.
- Program Committee Member, Workshop on Large-scale Data Mining: Theory and Applications, to be held in conjunction with the ACM SIGKDD Conference on Knowledge

- Organizing Committee Member, Workshop on Algorithms for Modern Massive Datasets

- Program Committee Member, ACM Transactions on Knowledge Discovery from Data:

- Program Committee Member, Workshop on Feature Selection in Data Mining, to be

Mining, Jun 2010.

- Program Committee Member, 21st Annual Symposium on Combinatorial Pattern Matching, Jun 2010.
- Program Committee Member, Pacific-Asia Conference on Knowledge Discovery and

- NSF IIS Review Panel, 2009.
- Program Committee Member, ICDM Workshop on Large-scale Data Mining: Theory

- Invited Reviewer, Neural Information Processing Systems Conference, Dec 2009.
- Co-organizer (with I. Ipsen), Randomized Algorithms in Linear Algebra, minisymposium in the SIAM Conference on Applied Linear Algebra, Oct 2009.
- Program Committee Member, ACM SIGKDD International Conference on Knowledge

- Program Committee Member, International Conference on Artificial Intelligence and

- Program Committee Member, Pacific-Asia Conference on Knowledge Discovery and

- NSF CDI Review Panel, 2009.
- Invited Reviewer, Neural Information Processing Systems Conference, Dec 2008.
- Co-organizer (with S. Das and M. Zaki), RPI Computer Science Day: Data Mining

- Technical Program Committee Member, NumAn 2008 Conference in Numerical Analysis, Sep 2008.
- Co-chair, Data-Centric Computing Group for the Visions for Theoretical Computer

- Technical Program Committee Member, Workshop on Data Mining Using Matrices

Knowledge Discovery and Data Mining, Aug 2008.

- Organizing Committee Member, Workshop on Algorithms for Modern Massive Datasets

- Organizing Committee Member, Workshop on Data Mining for Biomedical Informatics, held in conjunction with the SIAM Conference on Data Mining, Apr 2008.
- Technical Program Committee Member, SIAM Conference on Data Mining, Apr 2008.
- Technical Program Committee Member, NumAn 2007 Conference in Numerical Analysis, Sep 2007.
- Technical Program Committee Member, ACM SIGKDD International Conference on

- Organizing Committee Member, Workshop on Data Mining for Biomedical Informatics, held in conjunction with the SIAM Conference on Data Mining, Apr 2007.
- Co-organizer (with D. Freedman), RPI Computer Science Day: Aspects of Geometric

- NSF CCF review panel, 2006.
- Organizing Committee Member, Workshop on Algorithms for Modern Massive Datasets

- Program Committee Member, International Workshop on architectures, models and

conjunction with the 17th ACM Conference on Hypertext and Hypermedia, 2006.

- Technical Program Committee Member, ACM SIGKDD International Conference on

- Technical Program Committee Member, ACM SIGKDD International Conference on

- Technical Program Committee Member, Workshop on Peer to Peer and Service-Oriented

- Technical Program Committee Member, NSF-RPI Workshop on Pervasive Computing,

Biographical Year of birth: 1975

Data Country of birth: Greece

Citizenship: USA, Greece

Updated May 6, 2017.