#37 AI Series: Stanford University - S. Sanborn

We are excited to feature Sophia Sanborn, who is currently an Assistant Professor at Stanford University and will discuss "Virtual Neuroscience with Neural Digital Twins", lasting approximately 45 minutes. After the talk, seize the opportunity to connect with fellow AI enthusiasts to share ideas and questions while enjoying free drinks and pizza. Door close by 7.15pm, so please come early! Also, "attend"ing (RSVP) here on Meetup is strictly necessary to be guaranteed entry.
Please note that Meetup has recently been quite keen on promoting its Plus program. However, you are not obligated to purchase it, as both our events and the platform remain free.

Who is this event for?
This event is open to everyone interested in state-of-the-art AI research. We especially design it for students, PhD candidates, academic researchers, and industry professionals with a research focus in machine learning.

Abstract: A central goal of systems neuroscience is to understand how populations of neurons represent and transform the natural world. As neural datasets grow in scale and complexity, manual hypothesis generation and neuron-by-neuron characterization are becoming increasingly limiting. Neural digital twins — deep learning models trained to predict the responses of biological neurons — offer a complementary approach: distilling large-scale recordings into experimentally tractable models that can be queried, perturbed, and analyzed in silico. Using this framework, we characterize neurons in macaque and mouse visual cortex, revealing interpretable feature selectivity and previously hidden properties of the neural code. More broadly, these models enable a paradigm of virtual neuroscience, where learned models of neural systems become platforms for automated scientific discovery: searching stimulus space, mapping selectivity, testing representational hypotheses, and generating new candidate principles of neural computation. By enabling virtual experiments that would be difficult or impossible in vivo, neural digital twins open a path toward a new regime of scalable, computationally driven discovery in neuroscience.

Bio: Sophia Sanborn is an Assistant Professor in the Department of Ophthalmology, with a courtesy appointment in Neurology, at Stanford University. She is Co-Director of the Enigma Project, a large-scale neuroscience initiative aimed at understanding the neural code, and Co-Founder of Metamorphic, an AI company building neural digital twins and brain-aligned foundation models. Her research sits at the intersection of neuroscience, artificial intelligence, and mathematics, leveraging large-scale neural data and computational models to reveal principles of neural coding in biological and artificial systems.

We are BLISS e.V., the AI organization in Berlin that connects like-minded individuals who share great interest and passion for the field of machine learning. This summer 2026, we will, again, host an exciting speaker series on site in Berlin, featuring excellent researchers from cohere, ETH Zürich, University of Oxford, HuggingFace, and Stanford University.
Website: https://bliss.berlin
Youtube: https://www.youtube.com/@bliss.ev.berlin

Disclaimer: By attending this event you agree to be photographed.