Abhishek Sinha

Abhishek Sinha
Assistant Professor
Dept. of Electrical Engg., IIT Madras
Email: abhishek.sinha@ee.iitm.ac.in
Office: ESB-212-A

Research Summary

My primary research interest broadly lies at the intersection of Probability theory, Stochastic control, Information theory, and Learning Theory, where I seek to develop new analytical tools for understanding and enhancing the performance of networked communication and control systems of wide varieties. During my Ph.D., I worked with Prof. Eytan Modiano at MIT, where we studied the multicasting and the broadcasting problems from a network control standpoint and proposed provably optimal and decentralized algorithms targeted for wireless networks. This is the first known throughput-optimal policy for solving a flow problem of such generality. My thesis committee included Prof. Leandros Tassiulas, Prof. David Gamarnik, and Prof. Eytan Modiano.

I interned with Bell Labs at Murray Hill, NJ, in the summer of 2016, where I worked with Matthew Andrews and Prasanth Ananth on optimal resource allocation problems. I spent the summer of 2014 as a research intern at Microsoft, Redmond, working with Jie Liu at Microsoft Research and David Maltz's group at Windows Azure. There I worked on control and optimization of anycast based load management systems.

I obtained my Master's degree from the Electrical Communication Engineering department at the Indian Institute of Science, located in the beautiful city of Bangalore, where I worked with Prof. Anurag Kumar. Some of the highlights of my present and past research works are given below:

Our group is currently investigating the fundamental performance limits of the Network Caching algorithms from an online learning perspective. We have some exciting new results and algorithms pertaining to this problem.

Our group is also investigating the problem of optimal online scheduling to minimize the Age-of-Information in 5G wireless networks. We have designed a set of robust algorithms, which are oblivious to the underlying statistics of the channel (non-stationary regime), yet operate close to the fundamental limits.

In my doctoral work, I designed an exciting new Max-Weight type dynamic routing and scheduling policy, called Universal Max-Weight. UMW provides a unified solution to the general network-flow problem and settles several open and fundamental questions in this field.

During my Ph.D., along with my colleagues, I designed a scheduler for minimizing the Age of Information with throughput constraints. This work won the Best Paper Award in IEEE INFOCOM 2018, Honolulu, HI.

In my Master's thesis, I worked on optimal impromptu deployment problems for wireless sensor networks along a random lattice trail, with Prof. Anurag Kumar at the Network Engineering Lab, IISc. We leveraged various tools from stochastic optimal control theory to develop a provably efficient algorithm, which is way faster than the traditional Value iteration.

At IISc, I also collaborated with others on solving the problem of optimal deployment of relays on a line for the multi-relay channel from an Information-theoretic perspective.

In my Bachelor's thesis, I worked with Prof. Swagatam Das, at the Electronics and Telecommunication Engg. dept., Jadavpur University, located at the bustling city of Kolkata. We leveraged several mathematical tools from non-negative matrix theory and linear systems theory to prove convergence and study the nature of equilibrium points of an increasingly popular evolutionary optimization algorithm known as BBO.

News

[March 2021] Our paper on optimal control of distributed service chaining is accepted to IEEE/ACM Transactions on Networking.

[March 2021] Gave a talk on Network Caching using Onine Learning at the Workshop on Stochastic Models organized by IIT Bombay.

[March 2021] Samrat Mukhopadhyay joined our group as an Institute Post-Doc Fellow. He will be working on Online Learning problems. Welcome Samrat!

[Jan 2021] Starting as the founder and PI of the proposed Center of Excellence (CoE) "Intelligent Networks" approved under the nationwide IoE scheme.

[Oct 2020] Delivered a talk in the Theory Matters online seminar series on our recent work on Network Caching using Online Learning. [slides]

[June 2020] Our short paper on designing competitive algorithms for minimizing the Age-of-Information has been accepted to the prestigious workshop MAthematical performance Modeling and Analysis (MAMA) 2020, cohosted with SIGMETRICS 2020, Boston, MA.

[May 2020] I am Serving as a TPC member of COMSNETS 2021, to be held at Bangalore. Consider submitting your papers to COMSNETS 2021!

[March 2020] Our network caching paper has been accepted to SIGMETRICS 2020, the flagship conference of the ACM Performance group.

[March 2020] Our paper on Age of Information has been accepted to ISIT 2020.

[Nov 2019] Serving as a TPC member of WiOpt 2020, to be held at Volos, Greece. Consider submitting your papers to WiOpt 2020!

[Oct 2019] Serving as a TPC member of SPCOM 2020, to be held at IISc Bangalore. Consider submitting your papers to SPCOM 2020!

[Sep 2019] Paper accepted to IEEE Transactions on Mobile Computing.

[July 2019] Received an unrestricted gift of 35K USD from Qualcomm.

[July 2019] Delivered an invited talk at ISI Kolkata.

[June 2019] Delivered an invited talk at the Joint Telematics Group (JTG) 2019 Summer School, held at IIT Madras.

[June 2019] Chaired a session on Age of Information at WiOpt 2019, held at Avignon, France.

[May 2019] Delivered an invited talk at the Huawei Mathematical and Algorithmic Sciences Lab, Paris.

Our paper wins the Best Paper Award in IEEE INFOCOM 2018, Honolulu, HI.

MIT News Article on our Age of Information research.

Campus Technology article on the proposed scheduling algorithm.

Science Daily article on our recent work.

Our paper wins the Best Paper Award in ACM Mobihoc 2016, Paderborn, Germany. MIT link, Yale link .

Some of my interviews: Interview 1, Interview 2.