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.