BEGIN:VCALENDAR
VERSION:2.0
METHOD:PUBLISH
CALSCALE:GREGORIAN
PRODID:-//WordPress - MECv7.34.1//EN
X-ORIGINAL-URL:https://datasciences.utoronto.ca/
X-WR-CALNAME:DSI
X-WR-CALDESC:A hub for data science activity at the University of Toronto.
X-WR-TIMEZONE:America/Toronto
BEGIN:VTIMEZONE
TZID:America/Toronto
X-LIC-LOCATION:America/Toronto
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T030000
RRULE:FREQ=YEARLY;BYMONTH=03;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T010000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-PUBLISHED-TTL:PT1H
X-MS-OLK-FORCEINSPECTOROPEN:TRUE
BEGIN:VEVENT
CLASS:PUBLIC
UID:MEC-d457c0235036396f11714cb337bc0445@datasciences.utoronto.ca
DTSTART;TZID=America/Toronto:20231110T090000
DTEND;TZID=America/Toronto:20231111T170000
DTSTAMP:20240229T150422Z
CREATED:20240229
LAST-MODIFIED:20240301
PRIORITY:5
SEQUENCE:0
TRANSP:OPAQUE
SUMMARY:Forging A Path: Causal Inference and Data Science for Improved Policy Workshop
DESCRIPTION:In the evolving landscape of statistical, econometric, and data science advancements, a significant number of innovative methodologies remain untapped by applied research. There is a disconnect between cutting-edge econometric tools and relevant economic questions addressing societies’ most pressing concerns. This in-person Workshop seeks to address this gap and establish research collaboration between data scientists, experts in the causal inference literature, and applied researchers who better understand the empirical contexts, objectives, and challenges faced by policymakers. In the spirit of working across multiple disciplines and employing a variety of methodologies, the DSI Causal Inference Emerging Data Science Program is in collaboration with the Forward Society (FOS) Lab.\nThis Workshop is part of the Causal Inference Emerging Data Science Program  ( https://datasciences.utoronto.ca/causal_inference/ )that aims to facilitate cross-disciplinary exchange, where applied researchers from different disciplines can present their research questions and methodological issues. In turn, data science and causality researchers explore new and existing methods while promoting their research agendas.\nJoin us in-person at the Workshop to foster collaborative exploration, amplifying the impact of causal inference and data science research on real-world policy challenges.\nProgram\n\n\n\nNovember 10, 2023\n\n\n\n\n9:00 – 9:30 am\n Registration and Breakfast \n\n\n9:30 – 9:40 am\nOpening Remarks\nProf. Linbo Wang, Department of Statistical Sciences, Faculty of Arts & Science, University of Toronto\nProf. Gustavo Bobonis, Department of Economics, Faculty of Arts & Science, University of Toronto\n\n\n9:40 – 10:20 am\nCausal Inference with Deep Generative Model\nProf. Rahul G. Krishnan, Department of Computer Science, Faculty of Arts & Science, and\nDepartment of Laboratory Medicine and Pathobiology, Temerty Faculty of Medicine, University of Toronto\n\n\n10:20 – 11:00 am\nHow Can Novel Data Science Approaches Improve Causal Inference for Population Health?\nProf. Laura Rosella, Dalla Lana School of Public Health, and Associate Director, Education and Training, Data Sciences Institute, University of Toronto\n\n\n11:00 – 11:20 am\n Break \n\n\n11:20 – 12:00 pm\nDeconstructing Risk in Predictive Risk Models for Human-Centred Causal Inferences\nProf. Shion Guha, Faculty of Information, University of Toronto\n\n\n12:00 – 1:30 pm\n Lunch \n\n\n1:30 – 2:10 pm\nThe Unclaimed Property Puzzle: Billion Dollar Bills Lying on the Sidewalk\nProf. Eva Vivalt, Department of Economics, Faculty of Arts & Science, University of Toronto\n\n\n2:10 – 2:50 pm\nMethods for Counterfactual Data Augmentation in Reinforcement Learning\nProf. Elliot Creager, Department of Electrical and Computer Engineering, University of Waterloo\n\n\n2:50 – 3:10 pm\n Break \n\n\n3:10 – 4:10 pm\n Estimating the Value of Evidence-Based Decision Making – Keynote\nProf. Alberto Abadie, Department of Economics, MIT\n\n\n4:10 – 4:20 pm\n Concluding Remarks\nProf. Ismael Mourifié, Department of Economics, Faculty of Arts & Science, University of Toronto\n\n\n4:20 – 5:30 pm\n Refreshments and Social Hour \n\n\n\n\n\n\nNovember 11, 2023\n\n\n\n\n9:00 – 9:30 am\nBreakfast \n\n\n9:30 – 10:30 am\n Estimating Causal Effects Under Interference and Implications for Policy – Keynote\nProf. Elizabeth Halloran, Professor, Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Center, and Department of Biostatistics, University of Washington\n\n\n10:30 – 10:40 am\n Break \n\n\n10:40 – 11:20 am\n The Effects of School Consolidation on Students and Teachers: Evidence from an Underperforming System\nProf. Gustavo Bobonis, Department of Economics, Faculty of Arts & Science, University of Toronto\n\n\n11:20 – 12:00 pm\n Student-Led Roundtable: Wrap Up and Next Steps\nVahid Balazadeh, Sonia Markes, Stephen Tino, Dario Toman, Atom Vayalinkal\n\n\n12:00 – 1:30 pm\n Lunch \n\n\n\n
URL:https://datasciences.utoronto.ca/forging-a-path-causal-inference-and-data-science-for-improved-policy/
CATEGORIES:Causal Inference Workshops & Speaker Series
LOCATION:10th floor, 700 University Avenue, Toronto 
ATTACH;FMTTYPE=image/png:https://datasciences.utoronto.ca/wp-content/uploads/2024/02/Screenshot-2024-02-29-at-4.37.36 PM.png
END:VEVENT
END:VCALENDAR