Friday, July 21, 2023

Aishik Ghosh is a researcher in artificial intelligence for physics working for IJCLab and Université Paris-Saclay on the ATLAS experiment at CERN. Since October 2020, he has been based at the University of California Irvine and also affiliated with Berkeley Lab at University of California Berkeley. He has worked on risk assessment, bias mitigation, interpretability as well as synthetic data generation in the context robust and generalizable artificial intelligence models for particle physics at the Large Hadron Collider, CERN.

He has advocated for stronger open data policies and more public engagement in a report by the Early Career Researchers group mandated by the European Committee for Future Accelerators (ECFA). He is interested in the economic assessment of AI in enhancing scientific productivity, and public policy to ensure interpretable, auditable and inclusive AI.

Aishik Ghosh is a researcher in artificial intelligence for physics working for IJCLab and Université Paris-Saclay on the ATLAS experiment at CERN. Since October 2020, he has been based at the University of California Irvine and also affiliated with Berkeley Lab at University of California Berkeley. He has worked on risk assessment, bias mitigation, interpretability as well as synthetic data generation in the context robust and generalizable artificial intelligence models for particle physics at the Large Hadron Collider, CERN.

He has advocated for stronger open data policies and more public engagement in a report by the Early Career Researchers group mandated by the European Committee for Future Accelerators (ECFA). He is interested in the economic assessment of AI in enhancing scientific productivity, and public policy to ensure interpretable, auditable and inclusive AI.

Dr. Dane Morgan is the Harvey D. Spangler Professor of Engineering in the department of Materials Science and Engineering at the University of Wisconsin, Madison. His work combines thermostatistics, thermokinetics, and informatics analysis with atomic scale calculations to understand and predict materials properties.

Morgan is presently training or has graduated/trained over 70 graduate students and postdoctoral researchers and he leads the Informatics Skunkworks, which has helped engage over 400 undergraduates at the interface of data science and science and engineering. He has received multiple teaching and research awards and has published over 350 papers in materials science.

Bio: https://energy.wisc.edu/about/energy-experts/dane-morgan

Dr. Dane Morgan is the Harvey D. Spangler Professor of Engineering in the department of Materials Science and Engineering at the University of Wisconsin, Madison. His work combines thermostatistics, thermokinetics, and informatics analysis with atomic scale calculations to understand and predict materials properties.

Morgan is presently training or has graduated/trained over 70 graduate students and postdoctoral researchers and he leads the Informatics Skunkworks, which has helped engage over 400 undergraduates at the interface of data science and science and engineering. He has received multiple teaching and research awards and has published over 350 papers in materials science.

Bio: https://energy.wisc.edu/about/energy-experts/dane-morgan