Community Celebration and Building Dedication
Join the MIT Stephen A. Schwarzman College of Computing to celebrate the dedication of the College’s new building, a hub for research and education for computer science and artificial intelligence.
Come explore the new MIT Schwarzman College of Computing building and join us for refreshments, demos, and giveaways. All MIT faculty, staff, and students are invited; no registration required.
Event Details
Tuesday, April 30, 2024
3:30-5:00 pm
MIT Schwarzman College of Computing
51 Vassar Street, Building 45
Cambridge, MA 02139
Agenda
Can I Walk Your Dog?
Watch this robotic dog trained via deep reinforcement walk up the lobby stairs of the new MIT Schwarzman College of Computing building. The robot dog utilizes a depth camera to adapt its training to the different levels and surfaces it encounters.
Presented by Ge Yang, postdoctoral fellow, and Alan Yu, undergraduate student from EECS, from the Embodied Intelligence and Visual Computing Group led by Phillip Isola.
Robot Locomotion
We can build machines that exploit their natural dynamics to achieve extraordinary agility, efficiency, and robustness using rigorous tools from dynamical systems, control theory, and machine learning. In this demo, see an example of robotic manipulation, a result of the recent revolution in machine learning that has opened a pathway in these applications to the merger of control theory and perception at a level that has never been considered before.
Presented by Boyuan Chen, PhD student in EECS and researcher in CSAIL, who works with Vincent Sitzmann and Russ Tedrake.
Decoding the Why in Decision Making
Explore how methodologies can be leveraged from casual inference, survival analysis, and machine learning to aid decision making in social science and life science.
Presented by Jessy (Xinyi) Han, PhD student in IDSS and LIDS, co-advised by Devavrat Shah and Fotini Christia.
Let AI Be Your Engineer
Learn about multimodal AI for engineering design and how advanced models could enable designers to translate information from any modality or combination of modalities into comprehensive 2D or 3D designs.
Presented by Rui (Raymond) Zhou, PhD student in Mechanical Engineering, working with Faez Ahmed.
Let’s Play Soccer
Play with Dribblebot, a legged robot designed to dribble a soccer ball. This research demonstrates that quadrupeds can effectively handle dynamic control tasks involving both movement and manipulation.
Presented by Srinath Mahankali, an undergraduate student in EECS, working with Pulkit Agrawal.
Neural Scene Representation
See how neural networks create detailed 3D models of entire scenes from only two input images.
Presented by PhD students David Charatan and Sizhe Lester Li, who worked on this project under the guidance of Vincent Sitzmann within EECS.
TinyChat: An AI System in Your Hands
TinyChat is an efficient model for running large language models and visual language models locally on the edge. The key technique is 4-bit AWQ model quantization. It’s being used by IBM, NVIDIA, and Intel.
Presented by Shang Yang, PhD student in EECS, advised by Song Han.