October 2024 - Sanghani-faculty

Fw: re You are invited to a complimentary Kohl Centre workshop: Causality and Machine Learning/AI at Virginia Tech
by Shalaby, Wanawsha 28 Oct '24

28 Oct '24

FYI ________________________________ From: Chris North <north(a)cs.vt.edu> Sent: Monday, October 28, 2024 1:30 PM To: Shalaby, Wanawsha <wanah92(a)vt.edu> Subject: Fwd: re You are invited to a complimentary Kohl Centre workshop: Causality and Machine Learning/AI at Virginia Tech please distribute to Sanghani faculty if it has not already been sent out… YOU ARE INVITED Scholars from renowned universities such as Cornell, University of Chicago, and UC Irvine, along with various departments at Virginia Tech, are coming together to explore the critical intersections of causality and machine learning/AI. Causality plays a pivotal role in social science, business, and applied economics, shaping the future of machine learning and AI applications in diverse industries. This fundamental concept has earned prestigious recognition, with the 2021 Nobel Prize in Economics and the 2012 Turing Award in Computer Science both honoring contributions to causality. The upcoming complimentary Kohl Centre workshop aims to foster collaborations that transcend traditional boundaries, driving research forward, and aligning closely with the cutting-edge work at Virginia Tech. This workshop is in partnership with and sponsored by the Center for Advanced Innovation in Agriculture<https://caia.cals.vt.edu/>, the Center for Future Work Places and Practices<https://cfwpp.icat.vt.edu/>, the Department of Marketing in the Pamplin College of Business<https://marketing.pamplin.vt.edu/>, and the Institute for Society, Culture, and Environment<https://www.isce.vt.edu/>. REGISTER FOR THE WORKSHOP<https://docs.google.com/forms/d/e/1FAIpQLSeb-UWf2ilm3xD3_Rpa9h9-4i2WIZqoCl3…> Pre-workshop: Tutorial session on causal machine learning by Hengrui Cai, author of Causal Decision Making<https://causaldm.github.io/Causal-Decision-Making/Overview.html> * Date: Friday, November 1, 2024 * Time: 2:00 - 5:00 pm * Location: Room 132 in the Data and Decision Sciences Building Workshop: * Date: Saturday, November 2, 2024 * Time: 8:30 am - 5:00 pm * Location: The Inn at Virginia Tech and Skelton Conference Center Sessions include: * Causality in the Age of Generative AI * Towards Trustworthy Machine Learning: A Causal Lens on Learning Non-Spuriousness * Current and Prospective Uses of AI/ML in Addressing Problems Related to 6G Security * Rehabilitating the Once-Abandoned Endogenous IV * Causal Machine Learning for Policy Evaluation with Housing Transaction Data * Dynamic Treatment Effect Estimation with Interactive Fixed Effects and Short Panels * Controlling for problematic responses in survey data: A Causal Forest approach * Valid Post-Inference for Contextual Bandit Problems * Randomization inference and sensitivity analysis for quantiles of individual treatment effects * Estimating Stochastic Block Models in the Presence of Covariates * Heterogeneous Complementarity and Team Design * Causal Inference in the Presence of Network Interference with Low-Order Interactions Contact: Le Wang, Director of the Kohl Centre and David M. Kohl Chair and Professor in the Department of Agricultural and Applied Economics, lewangecon(a)vt.edu<mailto:lewangecon@vt.edu> [image001.png]

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Talk on ML interpretability
by Jia, Ruoxi 21 Oct '24

21 Oct '24

Hi all, As part of our ECE 6514 trustworthy ML course, we have invited an external speaker to give a guest lecture on ML interpretability. If you or any of your students or collaborators are interested in this area, we’d be happy to have you stop by! Bio: Dr. Ian Covert is a postdoctoral researcher at Stanford University, where I'm advised by James Zou and Tatsu Hashimoto. He was previously a Ph.D. student at the University of Washington, where I was advised by Su-In Lee. He also worked with Emily Fox at UW, He was a student researcher at Google Brain working with Jiening Zhan and Ming Jack Po, and I interned as a quantitative researcher at Citadel Securities and Goldman Sachs. Before that, He completed my Bachelor's degree at Columbia University, where he did computational neuroscience research in Liam Paninski's lab. He co-created an explainable AI course in Spring 2022. Title: Interpreting Black-Box Models: Shapley Values and Beyond Time: 10/22/2024 Tuesday 11am-12:15 Abstract: Modern machine learning relies heavily on black-box models, including transformers, CNNs, and tree ensembles, depending on the application. These models provide state-of-the-art accuracy but make it difficult to understand the logic that drives their predictions. This talk discusses “feature attribution” approaches that quantify the influence of each input feature, and provide one of the main lenses to interpret model predictions. We first cover removal-based explanations, a broad class of algorithms encompassing many of the most popular approaches in the field (LIME, SHAP, permutation tests, etc.); we then focus on Shapley values, including their origins in game theory and techniques to accelerate their computation. Zoom: Meeting ID: 840 8576 5484 Passcode: 887334 Best, Ruoxi -- Ruoxi Jia, Ph.D. ruoxijia.net<https://ruoxijia.net/> Assistant Professor Bradley Department of Electrical and Computer Engineering Virginia Tech

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Amazon Research Awards - Fall 2024 CFP
by Shalaby, Wanawsha 21 Oct '24

21 Oct '24

Hello, Amazon Research Awards (ARA) is announcing the fall 2024 call for proposals (CFP) for the AI for Information Security,<https://www.amazon.science/research-awards/call-for-proposals/ai-for-inform…> Automated Reasoning<https://www.amazon.science/research-awards/call-for-proposals/automated-rea…>, AWS AI<https://www.amazon.science/research-awards/call-for-proposals/aws-ai-call-f…>, AWS Cryptography<https://www.amazon.science/research-awards/call-for-proposals/aws-cryptogra…> and Sustainability <https://www.amazon.science/research-awards/call-for-proposals/sustainabilit…> research areas. The deadline for submissions is 11:59 p.m. PT on November 6, 2024. Proposals will be reviewed for the quality of their scientific content, creativity, and their potential for impact at scale. Proposals related to theory, practice, and novel new techniques are all welcome. ARA provides grant recipients unrestricted funds and AWS promotional credits. Funded projects are assigned an Amazon research contact, and recipients also receive training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers. Before applying, researchers are encouraged to visit the ARA website<https://www.amazon.science/research-awards> and read the frequently asked questions<https://www.amazon.science/research-awards/frequently-asked-questions> for more specific program information. Learn more about the CFP and how to apply.<https://www.amazon.science/research-awards/program-updates/amazon-research-…> Thank you, Wanawsha Wanawsha Shalaby Manager of Operations UrbComp Program Coordinator Sanghani Center for AI and Data Analytics - Virginia Tech 900 N. Glebe Road, Arlington, VA 22203 Phone: (571) 858-3361 E-Mail: wanah92(a)vt.edu<mailto:wanah92@vt.edu>

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Fw: Nov 12 2pm Distinguished lecture by Aidong Zhang (UVa)
by Shalaby, Wanawsha 11 Oct '24

11 Oct '24

Please see attached flyer. Wanawsha ________________________________ From: Yao, Danfeng via Nvcstaff <nvcstaff(a)cs.vt.edu> Sent: Friday, October 11, 2024 12:02 PM To: CS Faculty & Staff <facstaff(a)cs.vt.edu> Subject: [Nvcstaff] Nov 12 2pm Distinguished lecture by Aidong Zhang (UVa) Good afternoon! I am happy to announce a Distinguished Lecture jointly hosted by the Sanghani Center for Artificial Intelligence and Data Analytics and the CS department. Speaker: Dr. Aidong Zhang, Thomas M. Linville Professor of Computer Science at UVa Title: Can large language models help with scientific hypothesis generation? Time: Nov 12th 2pm-3:15pm Location: * Kelly 310 in Blacksburg * or watch over Zoom in Room 3-024 in VTRC-A, Arlington Please circulate to your students. See the attached flyer for more information. Best, Daphne

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Sanghani Center Faculty Meeting - Friday, Sept. 27 at 12 PM
by Shalaby, Wanawsha 10 Oct '24

10 Oct '24

Hi All, I hope everyone's semester is going well so far. Our first faculty meeting of the semester will be Friday, September 27 at 12:00 - 1:30 pm. As usual, if you have any recent news or updates since our last faculty meeting, please send them my way so that I may add them to our meeting slides. Updates include awards, proposals, grants, conference presentations, events, etc. Please send all updates by Wednesday, Sept. 25. I have sent an updated calendar invite with the new dates. Those of you in Blacksburg will be meeting in D&DS 337, which those of us in the D.C. area will be connecting via Zoo. Below is the Zoom information, please note that it's the same link for all our Sanghani Faculty meetings this semester. Join Zoom Meeting Https://virginiatech.zoom.us/j/89087118458 Meeting ID: 890 8711 8458 --- One tap mobile +16469313860,,89087118458# US +19294362866,,89087118458# US (New York) --- Dial by your location • +1 646 931 3860 US • +1 929 436 2866 US (New York) • +1 301 715 8592 US (Washington DC) • +1 305 224 1968 US • +1 309 205 3325 US • +1 312 626 6799 US (Chicago) • +1 360 209 5623 US • +1 386 347 5053 US • +1 507 473 4847 US • +1 564 217 2000 US • +1 669 444 9171 US • +1 669 900 6833 US (San Jose) • +1 689 278 1000 US • +1 719 359 4580 US • +1 253 205 0468 US • +1 253 215 8782 US (Tacoma) • +1 346 248 7799 US (Houston) Thanks, Wanawsha Wanawsha Shalaby Manager of Operations UrbComp Program Coordinator Sanghani Center for AI and Data Analytics - Virginia Tech 900 N. Glebe Road, Arlington, VA 22203 Phone: (571) 858-3361 E-Mail: wanah92(a)vt.edu<mailto:wanah92@vt.edu>

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