Mayank Baranwal

Hello 

Scientist
Divsion of Data & Decision Sciences
Tata Consultancy Services Research & Innovation

Adjunct Assistant Professor
Systems & Control Engineering
Indian Institute of Technology, Bombay

Email(s): baranwal.mayank@tcs.com
                  mbaranwal@iitb.ac.in

About me

I work as a scientist with the research division of TATA Consultancy Services in Mumbai (India). I also hold an Adjunct appointment with the Systems and Control group at the Indian Institute of Technology, Bombay. Prior to joining TCS, I was a postdoctoral scholar in the Department of Electrical and Computer Engineering at the University of Michigan, Ann Arbor in Prof. Alfred Hero's lab. I received my PhD in Mechanical Engineering at the University of Illinois at Urbana-Champaign, under the supervision of Prof. Srinivasa Salapaka. I develop techniques and technologies that help in comprehensive modeling, analysis and control of complex network systems.

I graduated with Masters in Mechanical Science and Engineering in Summer 2014 and Masters in Mathematics in Spring 2015, both from UIUC.

An ardent Cricket fan, I enjoy watching and playing Cricket a lot. I also have an inclination towards painting.

Research

My research interests are multi-disciplinary. I have primarily been interested in control theory and its overarching contributions to machine learning and optimization theory in particular. I have also enjoyed an occasional stint or two with implementation of robust control algorithms in power electronic devices and nanopositioning systems. Using my expertise in combinatorial and discrete optimization, mean field inference, robust and distributed control, distributed optimization and machine learning, I address a range of problems in network systems, including, but not limited to, power systems, large scale machine learning, medical sciences, and transportation networks. Here is an incomplete list of research areas that I find interesting:

  • Control Theory: Design of fast optimization algorithms, Distributed optimization and consensus, Variational inequality problems

  • Machine Learning Theory: Fundamental limits of GNNs, Reinforcement learning in delayed environments, Gradient flows and normalization, Determining number of clusters, Stabilizing training of GANs

  • Deep Learning Applications: Molecular property predictions, Intelligent inventory management, Tumor grading, Synthesis of microbial communities

  • Combinatorial Optimization: Mean-field annealing, Integer linear programs, Dynamic resource allocation, Traveling salesmen problems, Reduction of networks

  • Control Applications: Distributed control of microgrids, Communication-agnostic control, Robust control of AFMs

Background

  • Scientist, TCS Research & Innovation — July'20 - Present

  • Adjunct Asst. Professor, IIT Bombay — Jan'21 - Present

  • Guest Faculty, NITIE Mumbai — June'22 - Present

  • Postdoctoral Scholar in EECS, University of Michigan, Ann Arbor — Aug'18 - June'20

  • PhD in MechSE, University of Illinois, Urbana-Champaign — May'15 - May'18

  • MS in Mathematics, University of Illinois, Urbana-Champaign — Aug'14 - May'15

  • MS in MechSE, University of Illinois, Urbana-Champaign — Aug'11 - Aug'14

  • BTech in ME, Indian Institute of Technology, Kanpur — Aug'07 - May'11