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SUMMARY:CIS - Colloquium -  by Prof. Chris Wiggins\, Columbia University
DTSTART:20221212T151500
DTEND:20221212T161500
DTSTAMP:20260511T081249Z
UID:90a8b39be7ce58f549d591e212849fa422c9d8f502dcba7713766b31
CATEGORIES:Conferences - Seminars
DESCRIPTION:  Prof. Chris Wiggins\nTitle: Data science @ the new york tim
 es\nAbstract: The Data Science group at The New York Times develops and de
 ploys machine learning solutions to newsroom and business problems.\nRe-fr
 aming real-world questions as machine learning tasks requires not only ada
 pting and extending models and algorithms to new or special cases but also
  sufficient breadth to know the right method for the right challenge.\nI'l
 l first outline how\n\n	unsupervised\,\n	supervised\, and\n	reinforcement 
 learning methods\n\nare increasingly used in human applications for\n\n\n	
 description\,\n	prediction\, and\n	prescription\,\n\nrespectively.\nI'll t
 hen focus on the 'prescriptive' cases\, showing how methods from the reinf
 orcement learning and causal inference literatures can be of direct impact
  in\n\n	engineering\,\n	business\, and\n	decision-making more generally.\n
 \nBio:\nChris Wiggins is an associate professor of applied mathematics at 
 Columbia University and the Chief Data Scientist at The New York Times. At
  Columbia he is a founding member of the   executive committee of the Da
 ta Science Institute\, and of the Department of Applied Physics and Applie
 d Mathematics as well as  the Department of Systems Biology\, and is affi
 liated faculty in Statistics. He is a co-founder and co-organizer of hackN
 Y (http://hackNY.org)\, a nonprofit which since 2010 has organized once a 
 semester student hackathons and the hackNY Fellows Program\, a structured 
 summer internship at NYC startups. Prior to joining the faculty at Columbi
 a he was a Courant Instructor at NYU (1998-2001) and earned his PhD at Pri
 nceton University (1993-1998) in theoretical physics. He is a Fellow of th
 e American Physical Society   and is a recipient of Columbia's Avanessia
 ns Diversity Award. His forthcoming book "Data Science in Context: Foundat
 ions\, Challenges\, Opportunities"\, with Alfred Spector\, Peter Norvig\, 
 and Jeannette M. Wing\, will be published by Cambridge University Press in
  2022 and is available in draft form online via https://datascienceinconte
 xt.com/. His forthcoming book "How Data Happened: A History from the Age o
 f Reason to the Age of Algorithms"\, with Matthew L. Jones\, will be publi
 shed by Norton Press in 2023.\n\nBooks:\n"Data Science in Context: Foundat
 ions\, Challenges\, Opportunities" (Cambridge Press)\nhttps://www.amazon.c
 om/Data-Science-Context-Foundations-Opportunities/dp/1009272209/ and "How 
 Data Happened: A History from the Age of Reason to the Age of Algorithms" 
 (Norton Press\; March 21\, 2023) https://www.amazon.com/How-Data-Happened-
 History-Algorithms/dp/1324006730/\n\nThe Center for Intelligent Systems at
  EPFL (CIS) is a collaboration among IC\, ENAC\, SB\; SV and STI that brin
 gs together researchers working on different aspects of Intelligent System
 s. In June 2020\, CIS has launched its CIS Colloquia featuring invited not
 able speakers.\nMore info\n 
LOCATION:Zoom https://epfl.zoom.us/meeting/register/u5wkd-mtpz8uH9CmBiWVRU
 5WnRwEzZQiLSMn
STATUS:CONFIRMED
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