Seminars

September 29, 2026: (4PM)- Hao Li, University of California, San Francisco
Drifting of a Genetic Switch Involved in Key Developmental Decisions Underlies Aging Across Human Tissues.
Host: Jialong Jiang
Aging is often regarded as the last chapter of development, and growing evidence suggests that the two are mechanistically linked. Here I describe the identification of a genetic switch that links development to aging across human tissues. Using a human fibroblast replicative aging model and systematic perturbation analysis, we identified a genetic switch involving EGR1 and EZH2 as opposing regulatory nodes. We provide evidence that this switch is widely used in different tissues/organs to choose between proliferative and non-proliferative but functionally specialized states during development and tissue regeneration. During aging, this switch becomes ambiguous and cells drift away from the initial state established in youth. Since genetic switches are widely used in development to establish and reinforce cellular identity, we propose that attenuation of developmental switches may underlie aging across diverse organs and tissues, and partially accounts for the erosion of the epigenetic landscape and the loss of cellular identity.
Tuesday, October 6, 2026: (4PM)- Ilya Nemenman, Emory University (Location: Smith Hall Annex, A-Level, Physics Seminar Room)
Learning Dynamics, and Dynamics of Learning.
Host: Eric Siggia
The Rescorla–Wagner model of associative learning is a staple of animal learning theory. I will start with the model’s strong spots, but then show, by analyzing two experiments — in songbirds and in worms — that it cannot give a quantitative account of the dynamics of learning in these animals. The worm needs multiple associative channels of differing sign, magnitude, and learning rate to explain spontaneous recovery and other features of its behavior. The bird is better described by Bayesian filtering with non-Gaussian error channels. And both animals generalize what they learn to different contexts. I will show how modified related models explain the data much better, and what this implies for how learning is implemented in real nervous systems and should be implemented in artificial ones. Switching gears, I will then walk you through our lab’s attempts to learn biological dynamics directly from data, with machine learning that keeps the inferred models interpretable — from the nociceptive response of C. elegans to our recent attempts to write a fairly generic dynamics inference agent, which I hope some of you may want to use.
Thursday, October 8, 2026: (4PM)- Mackenzie Mathis, Swiss Federal Institute of Technology, Lausanne (EPFL)
Neural Dynamics of Sensorimotor Learning in the Cortex.
Host: Nikolas Schonsheck
Neural activity is tightly coupled to body dynamics, and predictive internal models are thought to support sensorimotor control by computing prediction errors. Here, we test whether such errors are encoded in primary somatosensory (S1) and motor (M1) cortex during motor adaptation in mice. Using control theory–derived features, we show that functionally distinct neurons map onto specific computational motifs. Layer 2/3 population dynamics encode command-like signals and sensorimotor prediction errors (SPEs), with S1 neurons representing SPEs more prominently than M1 and exhibiting larger learning-related changes in latent dynamics. To identify the coordinate frameworks of these errors, we developed a 50-muscle biomechanical model of the mouse forelimb in a physics simulator, and used DeepLabCut data to animate the model. We find that SPEs are represented in both 3D task space and muscle space. Together, our results provide a new model of how S1 dynamics support adaptive motor learning.
October 20, 2026: (4PM)- Seppe Kuehn, The University of Chicago
The Biophysics of Nitrogen Cycling in Soils.
Host: Avi Flamholz
The microbial communities that inhabit soils are one of the most complex ecological systems on the planet. The thousands of microbial species that inhabit every gram of soil reside in a complex mineral matrix that stores gigatons of organic carbon and nitrogen on a global scale. Microbial metabolic processes from degradation to respiration liberate this organic matter enabling plant growth and driving planetary scale elemental cycles. Understanding how these community-level metabolic processes emerge from microbial physiology and ecology, and depend on the environment, remains a central challenge. I present our efforts to address this question in the context of ubiquitous anaerobic respiration of oxidized nitrogen compounds in soils (nitrate, nitrite). I show that the utilization of nitrate by soil communities is characterized by a handful of distinct dynamic regimes that change with environmental pH. A phenomenological model proposes underlying mechanisms governing these regimes that are experimentally validated. I show that these dynamic regimes are a generic feature of soils across the globe. I suggest that the simplicity and regularity of community-level metabolism in soils arises from conserved metabolic interactions between microbes; an idea I support with statistical analysis of large-scale metagenomic surveys and quantitative measurements of interactions at the single-strain level.
October 27, 2026: (4PM)- Sangjin Kim, University of Illinois Urbana-Champaign
Space, Motion, and Information Flow in the Bacterial Cell.
Host: Shixin Liu
Bacterial cells organize a remarkable range of molecular activities within a small, crowded interior. My lab combines single-molecule imaging, quantitative analysis, genetics, and modeling to investigate how these activities unfold in space and time. I will first present our work on the coordination of transcription, translation, and RNA degradation. These studies reveal how translation activity and the cellular localization of RNA-degradation machinery constrain the fate of bacterial transcripts, defining when successive steps in the RNA life cycle are coupled or uncoupled. I will then introduce two ongoing studies that extend our investigation of the bacterial cell’s physical organization. Chromosome-tracking experiments reveal persistent subdiffusion and show how fluorescent labels influence the motion we measure. Measurements of cytoplasmic transport examine how different molecular probes exhibit distinct modes of motion within the same cellular environment. I will conclude with the questions and experimental approaches guiding our efforts to understand molecular motion and coordination in living bacterial cells.
November 3, 2026: (4PM)- Nikta Fakhri, Massachusetts Institute of Technology
To Be Announced.
Host: Jialong Jiang
To come.
November 10, 2026: (4PM)- Dipti Nayak, University of California, Berkeley
To Be Announced.
Host: Jeremy Rock
To come.
November 17, 2026: (4PM)- Jerome Gros, Pasteur Institute
To Be Announced.
Host: Alan Rodrigues
To come.
December 1, 2026: (4PM)- Yuhai Tu, Flatiron Institute
To Be Announced.
Host: Jialong Jiang
To come.
December 8, 2026: (4PM)-
To Be Announced.
Host: To Be Announced
To come.
December 15, 2026: (4PM)-
To Be Announced.
Host: To Be Announced
To come.
February 16, 2027: (4PM)-
To Be Announced.
Host: To Be Announced
To come.
February 23, 2027: (4PM)- Michael Manhart, Rutgers University
To Be Announced.
Host: Avi Flamholz
To come.
March 9, 2027: (4PM)- Kerwyn C. Huang, Stanford University (Location: Smith Hall Annex, A-Level, Physics Seminar Room)
To Be Announced.
Host: Jeremy Rock
To come.
March 16, 2027: (4PM)-
To Be Announced.
Host: To Be Announced
To come.
March 23, 2027: (4PM)-
To Be Announced.
Host: To Be Announced
To come.
March 30, 2027: (4PM)-
To Be Announced.
Host: To Be Announced
To come.
April 6, 2027: (4PM)-
To Be Announced.
Host: To Be Announced.
To come.
April 20, 2027: (4PM)- Amanda Larracuente, University of Rochester
To Be Announced.
Host: Li Zhao
To come.
April 27, 2027: (4PM)-
To Be Announced.
Host: To Be Announced
To come.
May 4, 2027: (4PM)-
To Be Announced.
Host: To Be Announced
To come.
May 11, 2027: (4PM)- Tom Shimizu, AMOLF
To Be Announced.
Host: Avi Flamholz
To come.