Lunch With a Scientist Schedule

March Meeting 2024

On select days, researchers will be available for informal conversations over lunch in the press room. Seating is first-come, first-served. This schedule is subject to change.

Tuesday, March 5, 12-1 p.m. CT: Maya Lassiter

Maya Lassiter is a PhD candidate in electrical and systems engineering at the University of Pennsylvania where she is both a Presidential Fellow and a GEM Fellow. Maya’s research includes the first demonstration of microscopic robots with onboard computers. Her work collapses the distance between building and using electronics and shows how emerging technologies can be made with an understanding of the socio-geo-political context surrounding their design, fabrication, use, and waste.

Wednesday, March 6, 12-1 p.m. CT: Sneha Kachhara

Sneha Kachhara is a postdoctoral fellow in the Department of Molecular Biosciences at Northwestern University. Sneha’s research uses models, nonlinear dynamics, and time series analyses to study biological systems and processes. Specifically, Sneha studies circadian rhythms to understand how living cells and organisms adapt to changes in day-night cycles. Sneha’s other interests include complex systems that show properties that are not reducible to the sum of their individual parts, like climate, variable stars, stock market trends, and more. Sneha has a PhD in physics from the Indian Institute of Science Education and Research.

Thursday, March 7, 11:30-12 p.m. CT, Alexandria Volkening

Alexandria Volkening is an assistant professor of mathematics and (by courtesy) biomedical engineering at Purdue University. She earned her PhD in applied mathematics at Brown University. Her research in applied mathematics and math biology, particularly complex systems, aims to better understand how the interactions of individuals — whether voters, cells, pedestrians, or other agents — lead to emergent group dynamics and collective behavior. At the March Meeting, Alexandria will discuss voter dynamics and share her group's U.S. election forecasts based on mathematical modeling.