AI Seminar: A New Workflow for Collaborative Machine Learning Research in Biodiversity
You can join this seminar physically or via Zoom: https://ucph-ku.zoom.us/j/61266312202
Serge Belongie, Andrew H. and Ann R. Tisch Professor in the Department of Computer Science at Cornell University and an Associate Dean at Cornell Tech.
In collaboration with the Global Biodiversity Information Facility (GBIF), iNaturalist, and Visipedia, we have introduced a new workflow for biodiversity research institutions who would like to make use of Machine Learning. With its billion+ species occurrence count contributed by thousands of institutions around the globe, GBIF is playing a vital role in enabling this workflow, whether in terms of data aggregation, collaboration across teams, or standardizing citation practices. In the short term, the most important role relates to an emerging cultural shift in accepted practices for the use of mediated data for training of ML models. In the process of data mediation, GBIF helps ensure that training datasets for ML follow standardized licensing terms, use compatible taxonomies and data formats, and provide fair and sufficient data coverage for the ML task at hand by potentially sampling from multiple source datasets.
Serge Belongie received a B.S. (with honor) in EE from Caltech in 1995 and a Ph.D. in EECS from Berkeley in 2000. While at Berkeley, his research was supported by an NSF Graduate Research Fellowship. From 2001-2013 he was a professor in the Department of Computer Science and Engineering at University of California, San Diego.
He is currently the Andrew H. and Ann R. Tisch Professor in the Department of Computer Science at Cornell University and an Associate Dean at Cornell Tech. His research interests include Computer Vision, Machine Learning, Crowdsourcing and Human-in-the-Loop Computing. He is also a co-founder of several companies including Digital Persona, Anchovi Labs and Orpix. He is a recipient of the NSF CAREER Award, the Alfred P. Sloan Research Fellowship, the MIT Technology Review “Innovators Under 35” Award and the Helmholtz Prize for fundamental contributions in Computer Vision.
This seminar is a part of the AI Seminar Series organised by SCIENCE AI Centre. The series highlights advances and challenges in research within Machine Learning, Data Science, and AI. Like the AI Centre itself, the seminar series has a broad scope, covering both new methodological contributions, ground-breaking applications, and impacts on society.