Keynote, “A New Frontier at the Intersection of Causality and LLMs”, HDSI Causality Workshop, UC San Diego, April 4th, 2024. [Slides]
Invited Talk, “A New Frontier at the Intersection of Causality and LLMs,” Are Language Models Simply Causal Parrots? Workshop at the 38th Annual AAAI Conference on Artificial Intelligence. February 27, 2024. [Slides]
Panelist, “Bridging the Gap: Responsible Language Model Deployment in Industry and Academia,” AAAI Workshop on Responsible Language Models (ReLM). February 26, 2024.
Panelist, “Challenges in Commercializing LLM in Enterprise-Wide Intelligence,” Industry Panel. February 23, 2024.
Keynote, University of Michigan Annual Data Science & AI Summit 2023, “A New Frontier at the Intersection of Causality and LLMs”, Nov. 14, 2023. [Slides]
Invited Talk, UC Berkeley Computational Precision Health and Center for Targeted Machine Learning, “Causal Inference and LLMs: A New Frontier”, Oct. 24, 2023.
Invited Talk, Stanford RAIN (Research on Algorithms and Incentives in Networks) Seminar, “Causal Inference and LLMs: A New Frontier”, Oct. 23, 2023.
Invited Talk, Pfizer/Northeastern/ ASA Symposium on Risks and Opportunities of AI in Pharmaceutical Medicine, “Extending a Causal Analysis Suite for Health Analyses: Capturing and Validating Critical Assumptions,” June 5, 2023.
Invited Talk, University of Cambridge Centre for AI in Medicine, “Opening a New Frontier for Causality”, May 28, 2023. [Video]
Invited Talk, ML in Medicine Seminar (Boston University, Univ. of Pittsburgh, UPMC, Univ of Toronto), “Extending a Causal Analysis Suite for Health Analyses: Capturing and Validating Critical Assumptions” May 17, 2023.
Speaker, WSDM 2023 Industry Day, “An Open-Source Suite of Causal AI Tools and Libraries,” February 27, 2023.
Plenary Speaker, UIUC CSL Student Conference, “Frontiers of Causal AI,” February, 22, 2023. Html
Invited Talk, UW CSE Data Science Lab Seminar, “Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization,” February 6, 2023. [Slides]
Invited Talk, UW Center for Statistics & Social Sciences Seminar, “Lessons being learned from an open-source causal AI suite,” February 1, 2023. [Html|Slides]
Speaker, Global AI Student Conference, “Foundations of Causal Inference and Open Source Causal Analysis Tools,” December 13, 2022.
Invited Talk, Forum on the Integration of Observational and Randomized Data (FIORD) 2022, “Extending a Causal Analysis Suite for Health Analyses: Capturing and Validating Critical Assumptions,” November 17, 2022.
Invited Talk, UMN Machine Learning Seminar, “Challenges in Causal Learning and its Applications,” April 6, 2022.
Plenary speaker, 3rd AI Summer School at Seoul National University (SNU), “Challenges in Causal Learning and Its Applications,” August 2, 2022. Video
Talk, Causal Data Science Meeting, “”, November 8, 2022. Html
Talk, NABE Tech Economics Conference, “An open-source suite of causal AI tools and libraries,” November 7, 2022. Html
Track Host, Microsoft Research Summit, Causal Machine Learning, October 18, 2022. Video
Keynote, Society of Quantitative Analysts, “Introduction to Causality,” January 20, 2022.
Invited talk, Swiss Joint Research Center Workshop. “Perspective on AI Research: Human-centered AI and Robustness” May 20, 2021. Video
Seminar, Microsoft Research Webinar. Foundations of causal inference and its impacts on machine learning webinar. December 3, 2020. Video
Invited talk, Microsoft Research India Academic Research Summit 2020. “Challenges of Security and Privacy in AI-Driven Systems” January 30, 2020. Video
Keynote, Social Informatics (SOCINFO) 2019. “Research Questions, Data Methods, and Ethics: From Memex to the Automated Scientist” November 18, 2019.
Keynote, Workshop on Truth Discovery and Fact Checking: Theory and Practice at KDD 2019. “Missing Information in Misinformation” August 5, 2019. Slides.
Tutorial, MILA / IVADO Summer School on Bias and Discrimination in AI. “Fairness-aware Machine Learning: Practical Challenges and Lessons Learned.” June 5, 2019. Presented with Margaret Mitchell. Also prepared with Krishnaram Kenthapadi, Sarah Bird, Ben Hutchinson. Slides.
Tutorial, MILA / IVADO Summer School on Bias and Discrimination in AI. “Where does Data Bias come from?” June 4, 2019. Slides.
Tutorial, The Web Conference 2019. “Fairness-aware Machine Learning: Practical Challenges and Lessons Learned.” Presented with Krishnaram Kenthapadi, Sarah Bird, Ben Packer. Also prepared with Benjamin Hutchinson. Slides.
Keynote, European Symposium Series on Societal Challenges in Computational Social Science: Biases and Discrimination, Dec 7, 2018. “Where Does Data Bias Come from? with Notes on Fairness and the Uses and Limitations of Causal Reasoning”. Slides.
Invited Talk, University of Chicago Computer Science Dept. Seminar, Nov 26, 2018. “Answering Ad Hoc Causal Questions in Web Search”.
Invited Talk, University of Washington DUB Seminar, Nov 7, 2018. “Answering Ad Hoc Causal Questions in Web Search” Slides, Video.
Cornell Tech Connective Media Brownbag, Oct 12, 2018. “Answering Ad Hoc Causal Questions in Web Search”.
2018 ACM SIGKDD Workshop on Causal Discovery Keynote, Aug 20, 2018. “Answering Ad Hoc Causal Questions in Web Search” Slides
2018 ACM SIGKDD Tutorial, Aug 19, 2018. “Causal Inference and Counterfactual Reasoning” with Amit Sharma. Website and Slides
SIGIR 2018 Industry Day Invited Talk, July 10, 2018. “Causal Inference Over Longitudinal Data to Support Expectation Exploration” [Slides]
ICWSM 2018 Tutorial, June 25, 2018. “Tutorial on Causal Inference and Counterfactual Reasoning,” with Amit Sharma. [Slides]
WSDM 2018 Tutorial, Feb 5, 2018. “A Critical Review of Online Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries” with Alexandra Olteanu and Carlos Castillo. [Slides]
Invited talk, Natl. Inst. on Drug Abuse / Natl. Inst. of Health Workshop on Youth Risky Behavior, Oct 17, 2017. “Studying Risky Behavior through Propensity Scored Analyses of Social Media Timelines” [Slides]
Invited talk, CSI Seminar, Emory University, Oct 27, 2017. “Learning about Personal Experiences and their Outcomes: Analyzing Social Media as an Observational Study” [Seminar Slides]
Invited talk, GVU Center Brown Bag Seminar, Oct 26, 2017. “Learning About Personal Experiences & Their Outcomes: Analyzing Social Media as an Observational Study” [Seminar Slides]
KDD 2017 Tutorial, Aug 13, 2017. “A Critical Review of Online Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries” with Alexandra Olteanu, Carlos Castillo and Fernando Diaz. [Slides]
Causal Inference Tutorial at Workshop on Observational Studies in Social Media at ICWSM 2017, May 15, 2017. “Tutorial: Intuition and basic methods for causal inference over social media data” [Slides]
Keynote at MAISoN WSDM Workshop, Feb 10, 2017. “Learning about Personal Experiences and their Outcomes: Analyzing Social Media as an Observational Study” [Slides]
Observational Studies in Social Media, Mar 23, 2016. “A System for Extracting the Outcomes of Personal Experiences from Social Media Timelines”
EPFL, Dec 10, 2015. “Discovering Outcomes via Propensity Score Analysis of Social Media Timelines” [Slides]
MPI-SWS, Dec 8, 2015. “Discovering Outcomes via Propensity Score Analysis of Social Media Timelines”
UW/MS Symposium on Computational Linguistics. Nov 6, 2015. “Discovering Outcomes via Propensity Score Analysis of Social Media Timelines”
MSR Latin American Faculty Summit, May 7, 2014. “Discussion Graphs: Putting Social Media in Context” [Slides, Video]
Workshop on a Digital Dynamic Earth, Mapping Science Committee, National Research Council, April 21, 2014. “Social Media Models”. [Slides]
AAAI-13 Spotlight Talk on ICWSM, July 17. I gave a talk reviewing the conference and current open challenges being addressed in the community.
MSR Machine Learning Summit, Apr 23, 2013. “Investigating Bias and Incentives in Social Media”. [Slides]
CHI-2013 Tutorial, Apr 30, 2013. “Analyzing Social Media Systems”. [Slides]
UIUC DAIS Seminar, Oct 17th, 2012. “Querying Human Activities from Social Media Traces”. In this talk, I discuss bias and external influences on social media.
Rutgers Yahoo Data Science Seminar, Feb 22, 2012. “Learning about the world through social media”
Berkeley Cloud Seminar, Feb 13, 2012. “Learning about the world through social media”