Praneeth Netrapalli

I am a researcher at Microsoft Research India, Bengaluru since August 2016. Prior to this, I was a postdoctoral researcher 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. My research focuses on designing efficient and provable algorithms for machine learning problems. Google Scholar     DBLP     arXiv

News and announcements

• Two papers accepted to NeurIPS 2019. One on minimax optimization and another on learning rate schedules for stochastic optimization.

• I have been selected as an associate of Indian Academy of Sciences.

• Sujay Sanghavi and I gave a tutorial on Understanding Non-convex Optimization at ISIT 2019. Slides here.

• Two recent papers on SGD. One accepted to ICML 2019 and one to COLT 2019.

• I will be giving an invited talk at ICCOPT 2019.

• I will be teaching a short course on optimization in machine learning at the JTG summer school 2019 at IIT Madras.

• New papers on minimax optimization and escaping saddle points with SGD on arxiv.

• Postdoc position, broadly in the areas of optimization and machine learning, open at MSR India. See here for more details. Please drop me an email if interested.

Professional service

On the program committee of NeurIPS 2019, COLT 2019, ICML 2019, AISTATS 2019. Reviewed for ICML, COLT, NIPS, STOC, SODA, IEEE TSP, IEEE TPAMI, JMLR…

Selected publications

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

• 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
  

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

Mentoring

I have been extremely fortunate to work with an amazing set of students.

Interns/Visitors (in reverse chronological order)

• Vihari Piratla (IIT Bombay)

• Kaustav Tamuly (BITS Goa)

• Suhail M. Shah

• Sheshansh Agrawal (IIT Bombay -> MSR India)

• Arun Sai Suggala (CMU)

• Dheeraj Nagaraj (MIT)

• Govinda M. Kamath (Stanford)

• Rahul Kidambi (Univ. of Washington)

• Chi Jin (UC Berkeley -> Asst. Prof. @Princeton EE)

Research fellows (in reverse chronological order)

• Harshay Shah

• Abhishek Panigrahi

• Suhas Jayaram (now PhD student at CMU)

• Raghav Somani (now PhD student at University of Washington)

• Chirag Gupta (now PhD student at CMU)

• Rahul Anand Sharma (now PhD student at CMU)

• Vivek Gupta (now PhD student at University of Utah)

• Yeshwanth Cherapanamjeri (now PhD student at UC Berkeley)

Contact details

• Address: Microsoft Research, # 9, Vigyan 1st floor, Lavelle Road, Bengaluru, Karnataka 560001, India.

• E-mail: praneeth [at] microsoft [dot] com
  

• Follow @PNetrapalli