WiDS Middlebury is independently organized by Breanna Guo ‘24.5 to be part of the mission to increase participation of women in data science and to feature outstanding women doing outstanding work. This fall, we have invited Middlebury alumni and professors, and Professor Laurie Baker from Bates College to talk about the range of work they do with data science, from mapping ocean ecosystems to leading business analytics for the Buffalo Bills.
Umar Serajuddin ‘96 will return to campus for a conversation moderated by Lomus Pudasaini ‘25 (Economics) and Lillian Caldwell ‘26 (Economics). This discussion explores pathways, out of the current polycrisis, to achieve progress toward eradicating poverty and boosting shared prosperity on a livable planet. The conversation is centered on the findings of the World Bank’s newly released Poverty, Prosperity, and Planet Report 2024: Pathways Out of the Polycrisis, which provides the first post-pandemic global assessment of poverty and shared prosperity.
Join George Lee (‘88, P’20), co-head of the Goldman Sachs Global Institute and Middlebury Trustee, for an open and frank discussion about the capabilities, impact, trajectory, and risks attendant to Generative AI. Audience members can submit questions in advance or pose them live during the event. Possible topics include questions about the limitations of the current technical architecture, expected future developments, the geopolitical impact of the technology and, of course, the possible impact on higher education.
Associate Professor of Geography at Dartmouth College Principle Investigator of Dartmouth’s Climate Modeling and Impact Group
Constraining Uncertanty in the Human Impacts of Climate Change
Tuesday, October 15, @ 4:30 PM in Axinn Center, room 229
Justin’s lecture will explore the climate change impacts on people and the things they value, by drawing examples from violent conflict, economic growth, and water resources.
Please consider attending the Middlebury Women in Data Science (WiDS) 2024 conference! The conference will feature three Middlebury faculty providing lightning talks on their work in data science, an alumni panel from recent Middlebury graduates who currently work in data science positions, and a keynote talk by Assistant Professor Sarah Brown from the department of Computer Science at University of Rhode Island. Everyone is welcome to attend the WiDS conference! Food and prizes will be provided.
Franklin Environmental Center, The Orchard-Hillcrest 103
Join midd.data for a Lightning Talk with panel speakers David Allen (Biology), Jessica L’Roe (Geography), Amy Yuen (Political Science), Genie Giaimo (Writing & Rhetoric), and Gyula Zsombok (French/Linguistics).
Join the faculty and students from the Data Science Across the Disciplines course to hear about their experiences and findings, and to discuss broader implications for providing all students equitable and inspiring access to data and digital tools.
Register for the in-person lunch by 5/2 or to receive the Zoom link.
Join midd.data for a Lightning Talk with Michelle Leftheris (Studio Art). NOWSPACE is an online, live-streaming observatory which collects video from cameras pointed at the sky across North America. In this immersive, web-based artwork, multiple streams are collaged into singular compositions of a synthesized view of the nation’s skies.
Dan Bouk, Associate Professor and Chair of History, Colgate, created a History Lab for students to contribute research to his recent book on the 1940 Census. Join us for lunch to learn about their collaborative work and to discuss ways in which humanists can learn from and teach with all the stuff “shrouded in cloaks of boringness”: bureaucracies, budgets, censuses, and all sorts of public and private numbers.
Join midd.data for a Lightning Talk with Chris Herdman (Physics). The familiar phases of matter we encounter every day—solids, liquids and gases—are well described by the laws of classical physics. Yet when matter is cooled down to very low temperatures, quantum mechanical effects can become important and transform ordinary matter into a quantum phase of matter. To discover a new phase of matter, you need to “know what it looks like”—that is, you need to identify a physical signature of the phase matter in experimental or simulation data.
