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UID:www.tcs.tifr.res.in/event/1371
DTSTAMP:20240109T044521Z
SUMMARY:Of the data\, by the data\, for the data: an algorithmic viewpoint
DESCRIPTION:Speaker: Ashok Vardhan Makkuva (École Polytechnique Fédérale
  de Lausanne (EPFL))\n\nAbstract: \nRanging from arts to science\, in disc
 iplines traditionally considered as bastions of human ingenuity\, data-dri
 ven algorithms have led remarkable breakthroughs in recent years through C
 hatGPT (natural languages)\, AlphaGo (game playing)\, and AlphaFold (biolo
 gy). With their ever growing prominence and ubiquity\, there is a growing 
 consensus that the need of the hour is a fundamental understanding of the 
 success and pitfalls of these algorithms. To this end\, my research adopts
  an interdisciplinary approach to design mathematical foundations and prin
 cipled algorithms for problems of great practical relevance. While advanci
 ng the success frontiers of data-driven methods\, this approach offers a u
 nique mathematical lens to study and understand them.\nIn this talk\, I wi
 ll present my contributions along these themes in the fields of informatio
 n theory\, machine learning\, and optimization. Through our work on KO cod
 es\, I will demonstrate how data-driven algorithms can discover state-of-t
 he-art codes for wireless communication\, a fundamental problem at the hea
 rt of information and coding theory. This research highlights the great po
 tential these methods hold for the design of next generation communication
  systems. Next\, I will present our novel algorithmic contribution in opti
 mal transport where we design an efficient and reliable algorithm to learn
  the optimal transport map between two distributions. These key ideas have
  broad applications in biology and medicine including cell perturbation an
 alysis and drug discovery. Finally\, I will present our ongoing work on de
 signing a solid set of theoretical and algorithmic tools to study large la
 nguage models (LLMs) and transformers. Despite their impressive performanc
 e\, our understanding of these models is still in infancy and my main goal
  here is to develop new insights into their inner workings and faster and 
 efficient training algorithms. I will conclude with my broader research vi
 sion in the realm of data science.\n \nAshok is a postdoctoral researcher
  at EPFL with Michael Gastpar. He obtained his PhD in ECE from the Univers
 ity of Illinois at Urbana-Champaign in August 2022\, with Pramod Viswanath
  and Sewoong Oh. He obtained his Masters in ECE with Yihong Wu also from U
 IUC in 2017. Earlier he graduated from IIT Bombay with a B.Tech. in EE and
  Minors in Mathematics working with Vivek Borkar. His research interests a
 re in foundations of data science in topics including machine learning\, i
 nformation theory\, optimization\, and statistics. He is a recipient of Be
 st Paper Award from ACM MobiHoc 2019. He is also a recipient of several gr
 aduate student awards and fellowships including Joan and Lalit Bahl Fellow
 ship (twice)\, Sundaram Seshu International Student Fellowship\, finalist 
 for the Qualcomm Innovation Fellowship 2018.\n
URL:https://www.tcs.tifr.res.in/web/events/1371
DTSTART;TZID=Asia/Kolkata:20240109T160000
DTEND;TZID=Asia/Kolkata:20240109T170000
LOCATION:A-201 (STCS Seminar Room)
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