Welcome
Bio
I am a postdoctoral researcher at the EPFL CS theory group, working with Prof. Ola Svensson. Prior to this, I graduated from Singapore University of Technology and Design (SUTD) generously supported by the SUTD President's Graduate Fellowship (PGF). I was really grateful to be advised by Georgios Piliouras (SUTD) and Ioannis Panageas (UC Irvine).
Research Interests
I am interested in studying fundamental questions in machine learning problems motivated by realistic constraints in applications: such as data truncation/censoring and data dependence, presence of agents (algorithms) that adapt over time and compete for resources. More recently, I am interested in understanding algorithms for discrete and combinatorial optimization problems when having access to ML predictors. I serve as a reviewer for ICML,NEURIPS, AISTATS, ICLR, TMLR.
In addition, I have reviewed papers for Algorithmica, EC, WINE, SAGT.
Here is my CV .
Contact details:
saiDOTnagarajanAT epflDOTch
News
"Online Algorithms with Costly Predictions" is accepted at AISTATS 2023.
"Mean estimation of truncated mixtures of two Gaussians: A gradient based approach" is accepted at AAAI 2023.
I am excited to serve as a PC member for AAMAS 2023.
I am grateful to be recognized as a Top Reviewer for NeurIPS 2022.
In July 2022, I was a TA for the course on the Interplay between Optimization and Sampling in High Dimensions, by Santosh Vempala, as a part of the EPFL Summer School on Modern Trends in Combinatorial Optimization.
Two papers accepted to AISTATS 2021.
I defended my Phd thesis titled "Machine Learning via Dynamical Systems: Applications to Deep Learning, Game Theory and Optimization" successfully on January 20th 2021!
In 2021, I will be joining as a postdoc, hosted by Prof. Ola Svensson at the EPFL CS theory group!
Virtual Talk on "On the analysis of EM for truncated mixtures of two Gaussians" at ACAC 2020.
Virtual Talk on "From Chaos to Order: Symmetry and Conservation Laws in Game Dynamics" at ICML 2020.
Two papers accepted to ICML 2020.
Talk on "On the analysis of EM for truncated mixtures of two Gaussians" at ALT 2020, San Diego.
Presented my work "On the analysis of EM for truncated mixtures of two Gaussians" as a poster at MIT Foundations of Data Science workshop: Learning under Complex Structure from Jan 27th-Jan 29th 2020.
Recent work on "Depth-Width Trade-offs for ReLU Networks via Sharkovsky's Theorem" has been accepted as a spotlight presentation at ICLR 2020.
My work with Ioannis Panageas "On the analysis of EM for truncated mixtures of two Gaussians" is accepted for presentation in ALT 2020.
Awarded the prestigious Merit Award in the Minister for National Development's R & D Awards 2019 for my contribution in the Urban Microclimate Multiphysics Integrated Simulation Tool (UM-MIST) project done at A*STAR.
Contributed Talk in the Learning in the Presence of Strategic Behavior Workshop at Economics and Computation 2019, FCRC, Phoenix.
Attended the Deep Learning Bootcamp in the Simons Institute for the Theory of Computing at UC Berkeley from May 26th 2019- May 31st 2019.
Teaching Assistant for Simulation,Modelling and Analysis from Sept 2018-Dec 2018 and Jan 2019-May 2019 (TA led course).
Invited to attend the summer school on "Optimal Transport meets Economic Theory" at the Hausdorff Center of Mathematics, University of Bonn from Jul 23rd-28th 2018.
Talk on "Three Body Problems in Evolutionary Game Theory: Convergence, Periodicity and Limit cycles" at AAMAS 2018, Stockholm.