Petros Drineas, PhD

Petros Drineas, PhD

Professor, Assistant Head
Computer Science Department
Purdue University


Petros Drineas is a Professor and Associate Head at the Computer Science Department of Purdue University. He earned a PhD in Computer Science from Yale University in 2003 and a BS in Computer Engineering and Informatics from the University of Patras, Greece, in 1997. From 2003 until 2016, Prof. Drineas was an Assistant (until 2009) and then an Associate Professor at Rensselaer Polytechnic Institute. His research interests lie in the design and analysis of randomized algorithms for linear algebraic problems, as well as their applications to the analysis of modern, massive datasets, with a particular emphasis on the analysis of genetics data. Prof. Drineas is the recipient of an Outstanding Early Research Award from Rensselaer Polytechnic Institute as well as an NSF CAREER award. He was a Visiting Professor at the US Sandia National Laboratories during the fall of 2005, a Visiting Fellow at the Institute for Pure and Applied Mathematics at the University of California, Los Angeles in the fall of 2007, a long-term visitor at the Simons Institute for the Theory of Computing at the University of California Berkeley in the fall of 2013, and has also worked for industrial labs (e.g., Yahoo Labs and Microsoft Research). From October 2010 to December 2011, he served the US National Science Foundation as a Program Director in the Information and Intelligent Systems (IIS) Division and the Computing and Communication Foundations (CCF) Division. Prof. Drineas has published over 140 papers (cited over 11,500 times) in theoretical computer science, applied mathematics, and genetics venues, including the Proceedings of the National Academy of Sciences, PLOS Genetics, Genome Research, the Journal of Medical Genetics, PLoS One, the Annals of Human Genetics, etc.

Prof. Drineas has presented keynote talks and tutorials in major conferences (e.g., SIAM ALA, KDD, VLDB, SDM, etc.) and over 100 invited colloquia and seminar presentations in the US and Europe. He received two fellowships from the European Molecular Biology Organization for his work in genetics and his research has been featured in various popular press articles, including SIAM News, LiveScience, ScienceDaily, Scitizen, the National Geographic, Yahoo! News, etc. Prof. Drineas has co-organized the widely attended Workshops on Algorithms for Modern Massive Datasets held bi-annually from 2006 to 2016 and is an editor of the SIAM Journal on Matrix Analysis and Applications (SIMAX), the SIAM Journal on Scientific Computing (SISC), the Applied and Computational Harmonic Analysis (ACHA) journal, and PLoS One.


Dimensionality Reduction in the Analysis of Human Genetic Data

Dimensionality reduction algorithms have been widely used for data analysis in numerous application domains including the study of human genetics. For instance, linear dimensionality reduction techniques (such as Principal Components Analysis) have been extensively applied in population genetics. We will discuss such methods and their applications in human genetics data.