AI for Science seminar with Marwin Segler, Microsoft Research.
Overview
Zoom password: ai4science
The on-site event will be followed by fika in the Analysen coffee area (fika from 16:00-16:30).
The AI for Science seminar series is also published here.
Bio:
Marwin Segler studied Chemistry at the University of Muenster, where he also did his PhD. He then worked at BenevolentAI London. Currently, he is at Microsoft Research AI for Science. His research interests are AI for chemical synthesis, molecular design, and AI-driven scientific discovery.
Structured learning
This theme focuses on how to make use of structure in data to build machine learning (ML) and artificial intelligence (AI) systems which are safer, more trustworthy and generalize better. Structure includes the relationship between data, in time and space, and how the predictions change when data is transformed in specific ways, for example rotated or scaled. These topics are abstract and general but have a direct impact on the use of AI and ML in the sciences and in applications such as drugs and materials design, or medical imaging.
Rocio Mercado
- Assistant Professor, Data Science and AI, Computer Science and Engineering
Rocio Mercado
- Assistant Professor, Data Science and AI, Computer Science and Engineering
Simon Olsson
- Associate Professor, Data Science and AI, Computer Science and Engineering
Simon Olsson
- Associate Professor, Data Science and AI, Computer Science and Engineering