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WiDS Datathon 2023 Climate Change Webinar
In this panel discussion, we speak with experts in a wide range of domains and institutions in order to explore the multi-faceted challenges posed by climate change. Not only do we aim to glimpse at how climate change impacts sectors spanning healthcare, energy and environmental protection, we will hear from our panel how data science can help us understand and mitigate the effects of climate change. This webinar is appropriate for audiences of all backgrounds – no prior familiarity with data science is assumed.

Feb 3, 2023 09:00 AM in Mountain Time (US and Canada)

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Marie-Laure Charpignon, MSc (she/her)
PhD Candidate @MIT Institute for Data, Systems, and Society (IDSS); Laboratory for Information and Decision Systems (LIDS)
Marie is a PhD candidate at MIT Institute for Data, Systems, and Society, conducting research at the Laboratory for Information and Decision Systems and Department of Health, Sciences, and Technology. Her interests include causal inference, agent-based modeling, and computational social science, with applications in public health. Previously, Marie obtained a BSc in Engineering Sciences from Ecole Centrale Paris and a MSc in Computational and Mathematical Engineering from Stanford University. As a data scientist at Microsoft, she analyzed the effects of technology usage and digital collaboration on student academic outcomes and socio-emotional learnings in school networks with treatment spillovers.
Utkarsha Agwan
PhD Candidate @EECS, UC Berkeley
Utkarsha is a PhD candidate in the Department of Electrical Engineering and Computer Sciences at UC Berkeley. Her research focuses on distributed energy resources, specifically batteries, electric vehicles and flexible loads, and how they can participate in the larger power grid. The overarching theme of her work is climate change mitigation. She also works as a consultant for companies in the smart energy space, with projects on distributed generation, storage, and local energy markets. Previously, Utkarsha obtained her undergraduate degree in Electrical Engineering from IIT Delhi.
Sarah Ostermeier
Field Data Scientist @Arthur AI
Sarah began her career as a neuroscience researcher before completing her Master’s Degree in Computer Science and Machine Learning. She went on to work as a research machine learning engineer specializing in time series and biomedical models before joining Arthur as a Field Data Scientist. She now works to enable enterprise clients to incorporate fairness and observability into their ML systems.