Welcome to new CMS faculty


Ashton Anderson

Ashton Anderson received his PhD in Computer Science from Stanford University in 2015.  Prior to joining the University of Toronto, he spent two years at Microsoft Research in New York. His research concerns computational social science, modeling various elements of human behaviour in the digital world based on massive datasets of human internet activity and software interventions. He is the recipient of several research awards, including a Google PhD Fellowship in 2012.

Gennady Pekhimenko

Gennady Pekhimenko received his PhD in Computer Science from Carnegie Mellon University in 2016.  For the last year he has been with the Systems Research Group at Microsoft Research in Redmond.  His research interests include computer systems and computer architecture, focused on efficient memory hierarchy designs with data compression, approximate computing, compilers, web search, GPUs and bioinformatics.  He is the recipient of several research awards, including an NVIDIA Graduate Fellowship in 2015/16 and a Microsoft Research PhD Fellowship in 2013-2015.

Qiang Sun

Qiang earned his doctoral degree in Biostatistics from the University of North Carolina, Chapel Hill in 2014, supervised by Joseph Ibrahim and Hongtu Zhu. He has since held fellowships at both Yale University under the supervision of Heping Zhang, and Princeton University under the supervision of Jianqing Fan. His research interests span statistical modeling optimization for big data, modern statistical inference, robust estimation, and neuro-imaging genetics.


Stefanos Aretakis

Stefanos Aretakis joins CMS in 2016 as Assistant Professor of Mathematics.  Stefanos completed his Ph.D. at the University of Cambridge, after which he was Veblen Research Instructor at the Institute for Advanced Study and Princeton University, and then on faculty in Mathematics at Princeton.  His research concerns mathematical foundations in General Relatively, and geometric analysis more broadly.  He is particularly well-known for his results concerning extremal black holes.  He is a recipient of the 2016 Alfred P. Sloan Research Fellowship in Mathematics.

Caren Hasler

Caren Hasler completed a Ph.D. in Statistics, and Masters in Mathematics, Statistics and Higher Education from the University of University of Neuchâtel.  Caren's research interests Survey Sampling, especially issues of non-response, imputation and re-weighting procedures.  She joins CMS as Assistant Professor, Teaching Stream in Statistics.  To read more, see Caren's website.

Thierry Sans

Thierry Sans holds a Master's degree from the National Institute of Aeronautics and Space (Sup'Aero - ENSAE), Toulouse, and a Ph.D. in Computer Science from Telecom-Bretagne (formerly ENST-Bretagne), Rennes.  Following his Ph.D. Thierry joined Carnegie Mellon University - Qatar Campus, first as a Post-Doctoral Fellow and then as Assistant Teaching Professor.  His research and teaching interests include Distributed Systems, Programming Languages, Network Security and Software Engineering.  He joins CMS as Assistant Professor Teaching Stream in Computer Science.  To read more, see Thierry's website.

Guilio Tiozzo

Giulio Tiozzo received the Ph.D. from Harvard University in 2013. Following his Ph.D. Giulio was a Gibbs Assistant Professor of Mathematics at Yale University.  He is widely regarded as one of the top young mathematicians in the area of Dynamical Systems and Ergodic Theory, already with strong results.  Giulio joins the Department of Computer and Mathematical Sciences as Assistant Professor of Mathematics.  To read more, see Giulio's website.



Robert Haslhofer

Robert Haslhofer joins CMS in 2015 as Assistant Professor of Mathematics.  Bob completed his Ph.D. at ETH Zurich, followed by a post-doctoral fellowship in the Courant Institute at New York University.  His broad research interests concern Geometric Analysis, Geometric Flows, Differential Geometry, Partial Differential Equations, Calculus of Variations, Stochastic Analysis, and General Relativity, core areas of pure mathematics with far-reaching potential impact.  To read more, see Bob's website.



Daniel Roy

Daniel Roy joins CMS as Assistant Professor of Statistics. Prior to joining the University of Toronto, Dan was Newton Scholar at the University of Cambridge.  He received the Ph.D. from MIT in 2011, for which he recevied the George M. Sprowls Doctoral Dissertation Award. Dan's research blends theoretical computer science, statistics and probability to address fundamental problems on the boundary of machine learning, probabilistic programming, inference and Bayesian non-parametrics. Ultimately, he is motivated by the long term goal of making lasting contributions to our understanding of complex adaptive systems and AI. To read more, see Dan's website.