Petros Drineas
Professor and Associate Head, Department of Computer Science, Purdue University
Associate Director, Health Data Science, Regenstrief Center for Healthcare Engineering (RCHE)
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: Randomized Numerical Linear Algebra (RandNLA).
Applications: Genomics & Big Data
Links: Wikipedia, Google Scholar, short bio, full CV.
Randomization in Numerical Linear Algebra made a cameo appearance in Netflix's hit series 'The Lincoln Lawyer'! Watch this short clip from Season 1, Episode 3 (disclaimer). Michael Mahoney and I coined this term in late 2011 and the first workshop on Randomized Numerical Linear Algebra (RandNLA) was held during FOCS 2012 (check the Nuit Blanche and My Biased Coin blog posts for details).
News
Mar '23: Congratulations to Pritesh Jain for for successfully defending his thesis. Pritesh will join the LKCMedicine group at the Nanyang Technological University Singapore as a Research Fellow.
Feb '23: I am honored to have received Purdue's College of Science Diversity Award.
Nov '22: I am honored to have been appointed a Purdue University Faculty Scholar.
Sep '22: Purdue Computer Science reaches #16 in U.S. News & World Report rankings! Go Boilers!
Sep '22: Slides from my talk at the mini-symposium on Randomized Methods in Large-Scale Inference and Data Problems (co-organized with R. Renaut and M. Chung) and held under the auspices of the 2022 SIAM Conference on Mathematics of Data Science (MDS22).
Jun '22: Slides from my plenary talk on "Sketching-based Algorithms for Ridge Regression" at the XXI Householder Symposium on Numerical Linear Algebra.
Jun '22: Sides from my talk on "Dimensionality Reduction in the Analysis of Human Genetics Data" at the Computer Engineering and Informatics Department at the University of Patras.
May '22: Slides from my talk on Randomized Numerical Linear Algebra for Interior Point Methods at the Algorithms and Foundations of Data Science workshop (co-organized by Y. Li and D. Woodruff).
May '22: Our work (joint with Gregory Dexter, Agniva Chowdhury, and Haim Avron) "On the Convergence of Inexact Predictor-Corrector Methods for Linear Programming" was selected for long presentation (2% acceptance rate) at the 2022 International Conference on Machine Learning (ICML).
Apr '22: Slides from my talk on "Randomized Numerical Linear Algebra: From Least Squares to Interior Point Methods" at the Third Workshop on Matrix Computations, dedicated to Gene H. Golub.
Apr '22: Congratulations to Myson Burch for been awarded the John R. Rice Fellowship in Scientific Computing for 2022-2023.