Rashish Tandon (राशीश टंडन)


I am a graduate student (PhD) in the Department of Computer Science at UT Austin, advised by Alex Dimakis and Pradeep Ravikumar(now at CMU). My research interests span machine learning and optimization in high-dimensional, big data and distributed settings.

Prior to joining UT Austin, I obtained a B.Tech/M.Tech(Dual Degree) in CS from IIT Kanpur in 2011.

Email :


  • Gradient Coding from Cyclic MDS codes and Expander Graphs [pdf]
       N. Raviv, I. Tamo, R. Tandon, A. Dimakis

  • Gradient Coding : Avoiding stragglers in distributed Synchronous Gradient Descent [pdf] [code]
       R. Tandon, Q. Lei, A. Dimakis, N. Karampatziakis
       In International Conference on Machine Learning (ICML) , 2017 (to appear)
       - A shorter version appeared in the ML Systems Workshop (MLSyS), NIPS 2016

  • Kernel Ridge Regression via Partitioning [pdf] [code]
       R. Tandon, S. Si, P. Ravikumar, I. Dhillon

  • On the Information Theoretic Limits of Learning Ising Models [pdf]
       R. Tandon, K. Shanmugam, P. Ravikumar, A. Dimakis
       In the Advances in Neural Information Processing Systems (NIPS), 2014

  • Learning Graphs with a Few Hubs [pdf] [appendix]
       R.Tandon, P.Ravikumar
       In the International Conference on Machine Learning (ICML), 2014

  • Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization [pdf]
       A. Agarwal, A. Anandkumar, P. Jain, P. Netrapalli and R. Tandon
       In the Conference on Learning Theory (COLT), 2014

  • On the Difficulty of Learning Power-Law Graphical Models [pdf]
       R. Tandon, P. Ravikumar
       In the IEEE International Symposium on Information Theory (ISIT), 2013

Teaching Experience

  • Teaching Assistant,  CS 303E - Elements of Computers and Programming,  UT Austin, Fall 2016

  • Teaching Assistant,  CS 378 - Statistical Learning and Data Mining,  UT Austin, Spring 2013

  • Teaching Assistant,  ESC 101 - Fundamentals of Computing,  IIT Kanpur,  Aug - Nov 2010