VASC Seminar
Nataniel Ruiz
Research Scientist
Google

Unlocking Magic: Personalization of Diffusion Models for Novel Applications

3305 Newell-Simon Hall

Abstract: Since the recent advent of text-to-image diffusion models for high-quality realistic image generation, a plethora of creative applications have suddenly become within reach. I will present my work at Google where I have attempted to unlock magical applications by proposing simple techniques that act on these large text-to-image diffusion models. Particularly, a large class of [...]

RI Seminar
Nikolai Matni
Assistant Professor
Department of Electrical and Systems Engineering, University of Pennsylvania

What Makes Learning to Control Easy or Hard?

1403 Tepper School Building

Abstract: Designing autonomous systems that are simultaneously high-performing, adaptive, and provably safe remains an open problem. In this talk, we will argue that in order to meet this goal, new theoretical and algorithmic tools are needed that blend the stability, robustness, and safety guarantees of robust control with the flexibility, adaptability, and performance of machine [...]

RI Seminar
Allison Okamura
Richard W. Weiland Professor of Engineering
Department of Mechanical Engineering, Stanford University

Soft Wearable Haptic Devices for Ubiquitous Communication

1403 Tepper School Building

Abstract: Haptic devices allow touch-based information transfer between humans and intelligent systems, enabling communication in a salient but private manner that frees other sensory channels. For such devices to become ubiquitous, their physical and computational aspects must be intuitive and unobtrusive. The amount of information that can be transmitted through touch is limited in large [...]

RI Seminar
Anirudha Majumdar
Associate Professor
Mechanical and Aerospace Engineering, Princeton University

Robots That Know When They Don’t Know

1403 Tepper School Building

Abstract: Foundation models from machine learning have enabled rapid advances in perception, planning, and natural language understanding for robots. However, current systems lack any rigorous assurances when required to generalize to novel scenarios. For example, perception systems can fail to identify or localize unfamiliar objects, and large language model (LLM)-based planners can hallucinate outputs that [...]