BEGIN:VCALENDAR VERSION:2.0 PRODID:-//wp-events-plugin.com//7.2.3.1//EN TZID:America/Los_Angeles X-WR-TIMEZONE:America/Los_Angeles BEGIN:VEVENT UID:49@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20231024T163000 DTEND;TZID=America/Los_Angeles:20231024T172000 DTSTAMP:20231020T174647Z URL:https://escience.washington.edu/events/uwdss-perkovic/ SUMMARY:UW Data Science Seminar: Ema Perkovic DESCRIPTION:\n\nPlease join us for a UW Data Science Seminar on Tuesday\, October 24th from 4:30 to 5:20 p.m. PST. The seminar will feature Ema Perk ovic\, UW Assistant Professor of Statistics. \n\n\nThis event will take p lace in the Physics/Astronomy Auditorium 102 (PAA A102) on the University of Washington campus.\n\n \;\n"Identifying and estimating causal effec ts with incomplete causal information"\nAbstract: Questions of cause and e ffect are ideally answered by intervening in a system through a randomized controlled experiment. However\, these experiments can often be costly\, time-consuming\, unethical\, or impossible to conduct. On the other hand\, observational data and specific domain or background knowledge may still be available. In this talk\, we consider how partial knowledge of causal r elationships can be combined with observational data to assess a causal ef fect while providing efficient estimators in certain settings.Suppose the causal system can be represented by a directed acyclic graph (DAG) encodin g causal relationships. This causal DAG is a priori unknown to us. Instead \, we have access to a class of potential causal DAGs representing the sam e set of observed conditional independencies and background knowledge. We present a necessary and sufficient graphical criterion to uniquely identif y a causal effect given such a class. When the causal effect cannot be uni quely identified given the class of possible graphical models\, we conside r the identification of a set of possible total causal effects and devise a minimal and complete approach to solving this problem. This result resol ves an issue with existing methods\, which often report possible total eff ects with duplicates\, namely those numerically distinct due to sampling v ariability but causally identical. Next\, for a causal effect that is iden tified from the partial knowledge of the causal relationships\, we devise an estimator based on recursive least squares. Under the linearity of the causal system\, this estimator consistently estimates the causal effect wh ile achieving a minimal asymptotic variance among a broad class of establi shed estimators. We conclude the presentation by discussing further resear ch directions.\n\nBio: Emilija Perkovic joined the Department of Statisti cs at the University of Washington in Autumn 2018 as an Acting Assistant P rofessor and was promoted to a tenure-track Assistant Professor role in Au tumn 2020.  Before coming to UW\, she completed a Ph.D. in Statistics at ETH Zürich in 2018 under the supervision of Professor Marloes Maathuis\, an M.Sc. in Statistics from ETH Zürich in 2014\, and a B.Sc. in Mathemati cs from the University of Belgrade in 2012.  Her research interests are f ocused on causal inference from the perspective of graphical models. A lar ge part of her Ph.D. thesis was on causal inference through covariate adju stment. She hopes to learn some new perspectives on causal inference while she is here.\n\n \;\nThe UW Data Science Seminar is an annual lectu re series at the University of Washington that hosts scholars working acro ss applied areas of data science\, such as the sciences\, engineering\, hu manities and arts along with methodological areas in data science\, such a s computer science\, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional partners\, governmental agencies and industry.\nThe 2022-2023 seminars wil l be held in person\, and are free and open to the public. LOCATION:Physics/Astronomy Auditorium A102\, 3910 15th Ave NE\, Seattle\, W A\, United States X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3910 15th Ave NE\, Seattle\ , WA\, United States;X-APPLE-RADIUS=100;X-TITLE=Physics/Astronomy Auditori um A102:geo:0,0 END:VEVENT BEGIN:VTIMEZONE TZID:America/Los_Angeles X-LIC-LOCATION:America/Los_Angeles BEGIN:DAYLIGHT DTSTART:20230312T030000 TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT END:DAYLIGHT END:VTIMEZONE END:VCALENDAR