Abstract: Understanding how nanoscale objects, from nanoparticles to proteins, move, interact, and reorganize in liquid environments is central to understanding both materials behavior and biological function. However, existing imaging and spectroscopy techniques are fundamentally limited in their ability to capture these dynamics in real time and with nanometer resolution. This talk introduces a new class of AI-driven electron microscopy frameworks that combine in situ liquid-phase transmission electron microscopy (LPTEM) with machine learning to visualize and interpret nanoscale dynamics directly in liquid. I will first describe how we use LPTEM-based nanorheology to quantify the viscoelastic response of confined liquids from single-particle trajectories. Building on this, I will present LEONARDO, a physics-informed generative model that learns the stochastic diffusion of nanoparticles in LPTEM, bridging statistical physics with representation learning to infer hidden physical parameters and generate synthetic trajectories. Finally, I will introduce a new hardware-software co-designed acquisition framework for high-throughput electron microscopy that integrates generative priors into the data acquisition process, enabling acquisition at higher speed, thus finer temporal resolution.

Bio: Vida Jamali is an Assistant Professor and Daniel B. Mowrey Faculty Fellow in the School of Chemical and Biomolecular Engineering at Georgia Tech since August 2022. Before that, she was a postdoctoral researcher at UC Berkeley, working with Prof. A. Paul Alivisatos in the College of Chemistry and Kavli Energy Nanoscience Institute. She received her PhD in Chemical and Biomolecular Engineering from Rice University in 2017 with Matteo Pasquali. Her research group at Georgia Tech focuses on developing AI-driven electron microscopy platforms to visualize and understand nanoscale dynamics of proteins, nanoparticles, and self-assembled soft materials in their native liquid environments. Vida is the recipient of the NSF CAREER award (2024) and the ACS PRF Doctoral New Investigator Award (2023). She was named a Scialog Fellow in Automating Chemical Labs in 2024 and a 30 Voices of Chemistry of Materials in 2023.