CHAI Seminar: Research Talk by Pinar Yanardag Delul, Assistant Professor, Computer Science, Virginia Tech
Date: Monday, April 13, 2026, 12:00-1:00 PM
Speaker: Pinar Yanardag Delul, Assistant Professor, CS, Virginia Tech
Title: From Chaos to Control: The Art of Taming Generative AI
Location: Virtual
Abstract: Deep generative models have made significant progress in a variety of real-world applications. However, these models are often interpreted as black boxes without the ability to understand what knowledge they learn in their latent representations. Before we can widely deploy deep generative models in high-stakes tasks such as self-driving cars or medical diagnosis, we need to understand the decision-making process of these models. This is an important research question with many practical implications, such as 1) explaining what knowledge generative models learn and what kind of controls they provide (CVPR’24, CVPR’25), 2) enabling new forms of creativity and foster human-AI collaboration (ICCV’25, NeurIPS’25), 3) creating fairer and more transparent models (ECCV’22, ICML’25). In this presentation, I will discuss our recent work on interpretable generative models at Generative Modeling Lab (GEM Lab): https://gemlab-vt.github.io.
Bio: Pinar Yanardag Delul received her PhD in Computer Science from Purdue and completed her postdoctoral research at MIT Media Lab. She is currently an assistant professor at Virginia Tech, Department of Computer Science. Her research interests are in the area of generative models, including GANs and diffusion models, to enable interpretability, transparency, creativity, and human-AI collaboration.
Event Snapshot
When and Where
Who
This is an RIT Only Event
| Cost | FREE |
Interpreter Requested?
No