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UID:www.tcs.tifr.res.in/event/1056
DTSTAMP:20230914T125948Z
SUMMARY:Optimal Resource Allocation and Scheduling in Networks and Systems
DESCRIPTION:Speaker: Rahul Singh (The Ohio State University\nColumbus\, Ohi
 o\, United States.)\n\nAbstract: \nAbstract: I will provide an account of 
 my research in various areas. As an exemplar\, I will discuss the first tw
 o topics in greater detail.\n1) Decentralized Control of Stochastic Dynami
 cal Systems: We begin by developing new methods to design decentralized c
 ontrol laws for stochastic dynamical systems which perform as well as an o
 ptimal centralized policy. We illustrate these methods on real-time multi
 -hop communication networks. The problem is challenging because it involv
 es inducing coordination amongst the controllers without knowing all the s
 tates of individual agents.\n\n2) Reinforcement Learning: We consider the 
 problem of designing learning rules for Markov decision processes under c
 onstraints on the cost expenditures by the controller/agent.\n\n3) Asympto
 tic Smoothness of a Service Discipline: We introduce a new performance met
 ric that is useful in order to characterize schedulers for networks servi
 ng real-time traffic. We also show that the popular MaxWeight scheduler p
 erforms well with respect to it.\n\n4) Networked Control Systems: We addre
 ss the problem of how to optimally schedule data packets over an unreliabl
 e channel in order to minimize the estimation error of a remote linear es
 timator that tracks the state of a Gauss Markov process. We show that a s
 imple index rule that calculates the value of information (VoI) of each pa
 cket\, and then schedules the packet with the largest current value of Vo
 I\, is optimal.\n\nI will conclude the talk by discussing my immediate and
  long-term research directions.\n\nBio: Rahul Singh is a postdoctoral res
 earcher at the Ohio State University. He received the B.Tech. degree in El
 ectrical Engineering from Indian Institute of Technology Kanpur in 2009\,
  the M.S. degree in Electrical Engineering from the University of Notre D
 ame in 2011\, and the Ph.D. degree in Computer Engineering from the Depart
 ment of  Electrical and Computer Engineering\, Texas A&M University\, Co
 llege Station\, in 2015. He was Postdoctoral Researcher at the Laboratory
  for Information and Decision Systems (LIDS)\, Massachusetts Institute of 
 Technology. He also worked as a Data Scientist at Encored Inc.\, and was 
 part of the Machine Learning Group at Intel. His research interests inclu
 de decentralized control of large-scale complex cyber-physical systems\, o
 peration of electricity markets with renewable energy\, optimal schedulin
 g and control of networks serving real time traffic\, machine learning\, 
 game theory\, stochastic control\, multi-armed bandits and reinforcement l
 earning.\n
URL:https://www.tcs.tifr.res.in/web/events/1056
DTSTART;TZID=Asia/Kolkata:20200224T110000
DTEND;TZID=Asia/Kolkata:20200224T120000
LOCATION:A-201 (STCS Seminar Room)
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