Praneeth Netrapalli

I am a research scientist at Google Research India, Bengaluru. I am also an adjunct professor at TIFR, Mumbai and a faculty associate of ICTS, Bengaluru. Prior to this, I was a researcher at Microsoft Research India for 4.5 years and did my postdoc at Microsoft Research New England in Cambridge, MA. I obtained my MS and PhD in ECE from UT Austin where I was fortunate to be advised by Sujay Sanghavi. Before coming to UT, I worked in the Quantitative Analysis group at Goldman Sachs, Bangalore. I obtained my B-Tech in Electrical Engineering from IIT Bombay. Honors and awards: INSA Medal for Young Scientists, 2021 IEEE Signal Processing Society Best Paper Award 2019 Associate of Indian Academy of Sciences (IASc) 2019-2022

Research Interests

My research interests are broadly in designing reliable and robust machine learning (ML) algorithms, representation learning, black-box optimization, time series modeling, quantum optimization and minimax/game theoretic optimization. I am also extremely interested in applying ML techniques to help solve problems from Sciences as well as enable positive social outcomes.

Google Scholar     DBLP     arXiv

News and announcements

• I am serving as a PC co-chair for research track of CODS-COMAD 2023. Please submit your great papers!

• Three papers accepted to ICLR 2022.

• Together with IKDD, we organized a ML in India social at NeurIPS 2021 to create more awareness about ML career opportunities in India across academia and industry. As part of this, we hosted short talks by six eminent speakers which is available here, and a list of job opportunities in ML in India across various sectors and organizations.

• Five papers accepted to NeurIPS 2021.

Professional service

On the program committee/area chair: NeurIPS 2019-21, COLT 2019-22, ICLR 2021, ICML 2019, 2021, AISTATS 2019.

Selected publications

* indicates alphabetical ordering of author names. Please see here for all publications.

• Minimax Optimization with Smooth Algorithmic Adversaries [*]
  T. Fiez, C. Jin, P. Netrapalli and L. Ratliff
  ICLR 2022
  

• No quantum speedup over gradient descent for non-smooth convex optimization [*]
  A. Garg, R. Kothari, P. Netrapalli and S. Sherif
  ITCS 2021
  

• The Pitfalls of Simplicity Bias in Neural Networks
  H. Shah, K. Tamuly, A. Raghunathan, P. Jain and P. Netrapalli
  NeurIPS 2020
  

• How to Escape Saddle Points Efficiently
  C. Jin, R. Ge, P. Netrapalli, S. M. Kakade and M. I. Jordan
  ICML 2017
  

• Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja's Algorithm [*]
  P. Jain, C. Jin, S. M. Kakade, P. Netrapalli and A. Sidford
  COLT 2016
  

• Phase Retrieval using Alternating Minimization
  P. Netrapalli, P. Jain and S. Sanghavi
  IEEE Transactions on Signal Processing 2015, Vol. 63, Issue 18, Pages 4814–4826
  IEEE Signal Processing Society Best Paper Award 2019 (awarded annually to up to six papers published during the previous five years)
  

• Low-rank Matrix Completion using Alternating Minimization [*]
  P. Jain, P. Netrapalli and S. Sanghavi
  STOC 2013
  

Mentoring

Contact details

• Address: Google India Pvt. Ltd., RMZ Infinity, No. 3, Swami Vivekananda Rd, Sadanandanagar, Bennigana Halli, Bengaluru, Karnataka 560016, India.

• E-mail: pnetrapalli [at] google [dot] com
  

• Follow @PNetrapalli