Past Events
Penn AI Seminar featuring Pengtao Xie (UCSD)
Foundation Models and Generative AI for Medical Imaging Segmentation in Ultra-Low Data Regimes
Amy Gutman Hall, Room 414
Also on Zoom
Semantic segmentation of medical images is pivotal in disease diagnosis and treatment planning. While deep learning has excelled in automating this task, a major hurdle is the need for numerous annotated masks, which are resource-intensive to produce due to the required expertise…
AI + Us featuring Konrad Kording
AI is everywhere, but talking about it doesn’t take a PhD
The Garage at Yards Brewery
500 Spring Garden St.
Philadelphia, PA 19123
Open to everyone (21 and over)
AI + Us is a new Penn AI/Data Driven Discovery Initiative series bringing big ideas about artificial intelligence out of academia and into the world. Join us at Yards Brewery for our second event featuring Perelman School of Medicine and Penn Engineering's PIK Professor Konrad…
The AI Arts & Sciences Showcase
Lightning talks from SAS postdocs and graduate students
Tedori Auditorium, Neural and Behavioral Sciences Building
Join for the AI Arts & Sciences Showcase! Part of AI Month at Penn, the event will bring together graduate students and postdoctoral researchers for a series of fast-paced lightning talks highlighting how artificial intelligence is transforming research across Penn’s sciences and…
AI + Science Seminar: Soledad Villar
Machine Learning and Symmetries
Amy Gutman Hall, Room 414
Symmetries play a significant role in machine learning. In scientific applications, they often arise as constraints imposed by physical laws. More broadly, symmetries emerge whenever objects admit multiple ways to express them (for example, in graph machine learning). In addition…
AI x Science Seminar: Matthieu Wyart
Creativity by Compositionality in Generative Diffusion Models
Amy Gutman Hall, Room 414
In this talk, we will model this structure using probabilistic context-free grammars – tree-like generative models from linguistics. I will present a theory of denoising diffusion on this data, predicting a phase transition that governs the reconstruction of features at various…
AI is everywhere, but talking about it doesn’t require a PhD
AI + Us
The Garage at Yards Brewery
500 Spring Garden St.
Philadelphia, PA 19123
Where AI meets real life. AI + Us is a new public event series from Penn AI and the Data Driven Discovery Initiative designed to bring conversations about artificial intelligence out of the lab and into the real world. Join us at Yards Brewery for an evening of lively, accessible…
AI x Science Seminar: Mert Sabuncu
Ways to handle distribution shift and missingness in AI for medical diagnosis
Amy Gutman Hall, Room 414
Medical diagnosis can be naturally framed as a classification problem: inferring an underlying pathology from observed (e.g., imaging) data. A common failure mode in classification is shortcut learning, where models exploit spurious or confounding correlations. Shifts in patient…
AI x Science Seminar: Steve Sun
Generative constitutive laws as graphs and tree
Amy Gutman Hall, Room 414
Capturing path- and rate-dependent behaviors of solids, such as creeping, plastic deformation, damage, and fracture, often requires interpreting and quantifying relationships among the histories of variables, such as dislocation density and porosity. This relational information…
AI x Science Seminar: Pranam Chatterjee
Designing Programmable Molecules with Generative Sequence Models
Amy Gutman Hall, Room 414
The Chatterjee Lab at the University of Pennsylvania develops generative algorithms to design functional molecules directly from sequence. Our work begins with a question: can short peptides be de novo designed to bind undruggable targets like disordered oncogenic fusions…
AI x Science Seminar: Bhuv Jain
Machine Learning in Cosmology
Amy Gutman Hall, Room 414
Professor Jain will describe how we map dark matter from large surveys of galaxies via gravitational lensing. Testing theories of cosmology with maps of galaxies and dark matter is a rich area for machine learning. He will describe the ‘old-fashioned’ physics-based approaches and…
