[Quantum-ms] [Seminar] EE Faculty Candidate Lecture 4/3 at 11:40am

[Columbia EE Events]

Hi all, just a reminder that this event is happening now.

On Tue, Apr 1, 2025 at 9:59 AM Columbia EE Events <ee-events at ee.columbia.edu>
wrote:

> [image: Left-aligned blue cuee logo.png]
>
> *Please join us for the EE faculty candidate lecture on 4/3!*
>
> *When: *4/3, Thursday, 11:40am - 12:40pm
> *Where: *CEPSR 750, also via zoom
> <https://columbiauniversity.zoom.us/j/4419920270#success >.
> *Who:* Dr. Bingyi Kang
> *Title: *Visually Elicited Physical Intelligence
>
> *Abstract: * Foundation models have transformed the field of computer
> vision by learning general-purpose understanding and generation models that
> connect the visual world with semantic concepts. However, the ability to
> recover and model the physical world from visual observations is still in
> its infancy, despite being crucial for humans and animals to interact with
> others and their environment. We refer to these abilities as physical
> intelligence, which is fundamental to various applications including AR/VR,
> robotics and AI agents. In this talk, we explore physical intelligence and
> present several studies aimed at its development. First, we demonstrate the
> necessity of new techniques by showing that current state-of-the-art video
> generation methods fail to capture the physical attributes of the
> underlying world. Then, we discuss three crucial components in pursuing
> physical intelligence: 1) Physical modeling: building foundation models
> that can recover geometry information from arbitrary visual inputs; 2) Data
> intelligence: learning from real-world data with arbitrary distributions;
> 3) Decision making: training AI agents or robots with high-level planning
> and low-level control. Finally, we discuss future directions for bringing
> physical intelligence into reality and exciting opportunities for
> interdisciplinary collaborations.
>
> *Bio: *Bingyi Kang is currently a Research Scientist and Lead at TikTok
> Research in Seattle. He received his Ph.D. from the National University of
> Singapore in 2021 and was a visiting scholar at UC Berkeley, working with
> Trevor Darrell. His research areas include embodied AI, computer vision and
> machine learning. He aims to develop AI agents that can perceive, model,
> and interact with the physical world. He led the research of the Depth
> Anything series, which is widely recognized by both academia and industry,
> including adoption by Apple Core ML.
>
>
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