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UID:914@fds.yale.edu
DTSTART;TZID=America/New_York:20260408T120000
DTEND;TZID=America/New_York:20260408T130000
DTSTAMP:20260401T193245Z
URL:https://fds.yale.edu/events/fds-colloquium-nikhil-garg-cornell/
SUMMARY:FDS Colloquium: Nikhil Garg (Cornell)\, "Recommendations in the NYC
  High School Match (and other high-stakes settings)"
DESCRIPTION:\nAbstract: Recommendation systems are now used in high-stakes 
 settings\, including to help find jobs\, schools\, and partners. Building 
 public interest recommender systems in such settings bring both individual
 -level (enabling exploration\, diversity\, data quality) and societal (fai
 rness\, capacity constraints\, monoculture) challenges. I will talk about 
 an ongoing collaboration with the NYC Public Schools\, in which we designe
 d and deployed an informational intervention to help students from underse
 rved middle schools discover high-performing\, nearby high schools where t
 hey have a strong individual admissions likelihood. However\, recommending
  specific programs brings a methodological challenge\, congestion: if many
  applicants are recommended the same program\, affecting admissions likeli
 hoods\, then the recommendations may be self-defeating. Time permitting\, 
 I'll also overview other directions in tackling such challenges\, includin
 g on (a) algorithmic monoculture and LLM homogeneity\, (b) a platform to h
 elp discharge patients to long-term care facilities\, and (c) feed ranking
  algorithms on Bluesky for research paper recommendations.\n\n\n\nSpeaker 
 Bio: Nikhil Garg joined the Cornell University faculty as an Assistant Pro
 fessor of Operations Research and Information Engineering at Cornell Tech 
 in July 2021.\n\n\n\nGarg’s research is at the intersection of computer 
 science\, economics\, and operations—on the application of algorithms\, 
 data science\, and mechanism design to the study of democracy\, markets\, 
 and societal systems at large. His research interests include surge pricin
 g\, rating systems\, how to vote on budgets\, the role of testing in colle
 ge admissions\, stereotypes in word embeddings\, and polarization on Twitt
 er.\n\n\n\nGarg received his Ph.D. from Stanford University in 2020\, wher
 e he was part of the Society and Algorithms Lab and Stanford Crowdsourced 
 Democracy Team. He also received a B.S. and B.A. degrees from the Universi
 ty of Texas at Austin in 2015.\n\n\n\nHe has spent time at Uber\, NASA\, M
 icrosoft\, the Texas Senate\, and IEEE’s policy arm\, and most recently 
 was the principal data scientist at PredictWise—which provides election 
 analytics for political campaigns—and is currently completing a postdoc 
 at the University of California\, Berkeley in the Department of Electrical
  Engineering and Computer Science.\n
CATEGORIES:FDS Events,Colloquium
LOCATION:Yale Institute for Foundations of Data Science & Webcast\, 219 Pro
 spect Street\, 13th Floor\, New Haven\, CT\, 06511\, United States
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=219 Prospect Street\, 13th 
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 Yale Institute for Foundations of Data Science & Webcast:geo:0,0
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