Ken Kennedy Institute AI Seminar Series | Thursdays 12:00–12:50 PM Central
The Rice Computer Science department, CS GSA, and Ken Kennedy Institute will host a weekly AI Seminar on Thursdays from 12:00–12:50 PM at Rice University. This event is open to Rice University graduate students; no RSVP required. Join us each week at noon for a light lunch before the talk begins at 12:15 PM. See the list of seminars below.
| Date | Location | Seminar Details |
|---|---|---|
| 2/27 | DH 1046 | Speaker: Prof. Na Zou, PhD (Assistant Professor, University of Houston) Talk: Exploring and Exploiting Shortcuts in AI/ML: Algorithms, Challenges and Solutions For speaker bio and more information, please check the event page: Here AI/ML algorithms have made significant advancements and are extensively used in critical applications such as employment, personalized medicine, and more. Despite the success, mitigating shortcut features and spurious correlation in AI/ML remains a significant challenge. These algorithms may inadvertently rely on confounding factors or shortcut features in the data, resulting in unintended and misleading associations and thus poor model generalization. This issue hinders the widespread adoption of AI/ML in high-stakes applications. This talk will provide a computational perspective on shortcuts and spurious correlation in AI/ML, encompassing the measurement, detection, and mitigation of shortcuts and spurious correlation to address diverse challenges throughout the AI/ML life cycle. The speaker will first introduce real-world examples, fundamental concepts and the existing work. The speaker will also highlight her ongoing research across three key stages in AI/ML: enhancing data quality, refining algorithmic design, and optimizing model deployment. |
| 3/6 | DH 1070 | Speaker: Prof. Jessica Ouyang, PhD (Assistant Professor, UT Dallas) Talk: Generating Scientific Literature Reviews For speaker bio and more information, please check the event page: Here As researchers, we spend a lot of time interacting with literature reviews: we read them when we want to quickly get up to speed in a new research area, and we write them when we need to ground our own research contributions in the landscape of existing work. In this talk, I will discuss my lab's work on developing neural approaches to generate scientific literature reviews. I will begin by highlighting our contributions in the task of citation generation in the context of a larger literature review paragraph, including generation at the sub- and multi-sentence levels, enforcing coherence with the surrounding paragraph, and retrieving grounding sentences from cited papers. Then, I will introduce our work on full-length literature review generation and describe a detailed user study on the capabilities of current state-of-the-art language models on this task. Finally, I will conclude with a discussion of current challenges in literature review generation, as well as the ethical considerations that arise when automating part of the scientific writing process. |
| 3/13 | O'Connor 5th Floor | Speaker: Prof. Mauricio Araya Polo, PhD (Adjunct Professor, Rice; Senior R&D Manager, Total Energies) Talk: Addressing Geophysical Problems with Scientific ML For speaker bio and more information, please check the event page: Here Advances in machine learning (ML) are open new avenues for complex geophysical problems. This seminar explores how scientific ML techniques, in particular DL-driven inversion, can enhance traditional geophysical methods. We illustrate their application to seismic inversion, subsurface characterization, and CO2 monitoring through examples. Attendees will gain insights into current methodologies and future directions in integrating scientific ML with geosciences. |
| 3/20 | N/A | No Seminar — Spring Break |
| 3/27 | DH 1070 | Speaker: Prof. David Harwath, PhD (Assistant Professor, UT Austin) Talk: Professor David Harwath received his Ph.D. of Computer Science from Massachusetts Institute of Technology. His research interests are in the area of machine learning for speech, language, and sound processing. |
| 4/3 | O'Connor 5th Floor | Speaker: Prof. Sunyang Fu, PhD (Assistant Professor, UTHealth Houston) Talk: Professor Sunyang Fu received his Ph.D. of Biomedical Informatics and Computational Biology from University of Minnesota. He is the 2023-24 Leadership Fellow with the National Institute's of Health's AIM-AHEAD. His research focuses on clinical natural language processing and clinical research informatics, with an emphasis on accelerating, improving, and governing the secondary use of electronic health records for valid, reproducible, and trustworthy discoveries. |
| 4/10 | DH 1070 | Speaker: Jyoti Anand (Director of Data Science, Walmart) Talk: Gen AI in Retail Technology As the director of Walmart Data Science team, Jyoti has been integrating ML solutions with business functions to create the next generation of AI-powered capabilities. Her rich industry experience in Allegis, FDA, and Walmart has given her deep insight in Forecasting, LLMs, Deep Learning models. |
| 4/17 | DH 1070 | Speaker: Prof. Tianlong Chen, PhD (Assistant Professor, University of North Carolina at Chapel Hill) Talk: Professor Tianlong Chen received the Ph.D. degree in Electrical and Computer Engineering from University of Texas at Austin. His research focuses on building accurate, trustworthy, and efficient machine learning. |
| 4/24 | DH 1070 | Speaker: Prof. Cheng Zhang, PhD (Assistant Professor, Texas A&M University) Talk: Professor Cheng Zhang received his Ph.D. in the Department of Computer Science and Engineering at The Ohio State University. His research interests are machine learning and its applications to computer vision, multimodal understanding, human modeling for extended reality, and cyber-physical systems. |
To see a list of all upcoming events related to the Ken Kennedy Institute, visit https://kenkennedy.rice.edu/events.
For questions, please contact at hd31@rice.edu.
