Register here to attend Adji Bousso Dieng 's AC seminar taking place in person at 700 University Avenue in the 10th Floor Seminar Room or online via Zoom.
Vendi Scoring for Discovery
Abstract: This talk will cover the concepts, tools, and methods that make up Vendi Scoring, a new research direction focused on the concept of diversity. It will begin with an introduction to the Vendi Scores, a family of diversity metrics rooted in ecology and quantum mechanics, along with their extensions. Next, algorithms for efficiently searching large materials databases and exploring complex energy landscapes, such as those found in molecular simulations, will be discussed in the context of Vendi Scores. Finally, the talk will introduce the concept of "algorithmic microscopy," which stems from Vendi Scoring, and describe the Vendiscope, the first algorithmic microscope designed to help scientists zoom in on large data collections for data-driven discovery.
Bio: Adji Bousso Dieng is an Assistant Professor of Computer Science at Princeton University where she leads the lab Vertaix on research at the intersection of artificial intelligence and the natural sciences. She is affiliated with the Chemical and Biological Engineering Department, the Princeton Materials Institute, the Princeton Quantum Initiative, the Andlinger Center for Energy and the Environment, and the High Meadows Environmental Institute (HMEI) at Princeton. She is also a Research Scientist at Google AI and the founder and President of the nonprofit The Africa I Know. She has been recently named an Early-Career Distinguished Presenter at the MRS Spring Meeting, one of 10 African Scholars to watch in 2025 by The Africa Report, an Outstanding Recent Alumni by Columbia University's Grad School of Arts and Sciences, an AI2050 Early Career Fellow by Schmidt Sciences, and as the Annie T. Randall Innovator of 2022 for her research and advocacy by the American Statistical Association. She received her Ph.D. from Columbia University. Her doctoral work received many recognitions, including a Google Ph.D. Fellowship in Machine Learning, a rising star in Machine Learning nomination by the University of Maryland, and a Savage Award from the International Society for Bayesian Analysis, for her doctoral thesis. Dieng's research has been covered in media such as the New Scientist and TechXplore. She hails from Kaolack, Senegal.
About the AC Seminar Series
The Acceleration Consortium (AC) seminar series explores perspectives on the future of AI for science, presents cutting-edge research findings, enables collaborations, and offers training and upskilling opportunities. Presented both in-person and online, these seminars will host a diverse set of speakers on topics related to accelerated discovery across three tracks:
- AC Distinguished Seminars: Leaders in the autonomous discovery community will share their findings and perspectives that are helping to shape future directions and address key challenges. These will be delivered in a hybrid format at the University of Toronto.
- AC Early Career Seminars: Early career researchers will present results from their latest publications, taking a technical dive into findings, methods, and tools. These will be delivered in a hybrid format at the University of Toronto.
- AC Virtual Training Seminars: Instructors will provide standalone introduction lectures and hands-on tutorials on topics related to self-driving labs with an emphasis on principles, literacy, and skills. These will be delivered virtually.
Do you have a suggestion for a talk? We welcome your ideas for potential speakers from diverse career stages and backgrounds.
