TILOS Industry Day 2024

TILOS (The NSF National AI Institute for Learning-enabled Optimization at Scale) will hold its 3rd Annual Industry Day on June 18, 2024, at the Halıcıoğlu Data Science Institute at UC San Diego, which is the campus hub for Data Science. Our first two Industry Days have attracted more than 100 participants, each featuring (1) talks from invited Industry Speakers sharing their perspectives on challenges in AI + Optimization + Use domains (chips, robotics, networking), (2) research highlights from TILOS team members, and (3) most importantly, a vibrant TILOS Trainee Poster Session (30+ posters) together with a “Facebook” of students and postdocs (a booklet of these trainees). There is no cost to attend, but please register here.

AGENDA

8:00 – 8:45am Registration + Breakfast
8:45 – 9:00am Welcome Remarks and Introduction to TILOS
Director Yusu Wang (UCSD)
AD Translation Vijay Kumar (UPenn)
Rajesh Gupta (Director of HDSI@UCSD)
9:00 – 10:30am SESSION 1  Chair: Vijay Kumar (UPenn)
Industry Keynote: Towards Scalable and Robust Autonomy, Nicholas Roy (Zoox)
TILOS Faculty Highlights:
[9:50am] Traceable and Scalable GNN-based Circuit Optimization, Farinaz Koushanfar (UCSD)
[10:10am] Feature learning in neural networks and kernel models, Misha Belkin (UCSD)
10:30 – 10:45am Break
10:45am – 12:15pm SESSION 2  Chair: Yian Ma (UCSD)
Industry Keynote: AI and Networks: Challenges & Opportunities, Nageen Himayat (Intel Labs)
TILOS Faculty Highlights:
[11:35am] Learning-enabled Optimization at Scale in Wireless Communications and Networking, Alejandro Ribeiro (UPenn)
[11:55am] Reasoning Numerically, Sean Gao (UCSD)
12:15 – 2:00pm TILOS Trainee Poster Lightning Preview Session + Lunch
2:00 – 3:00pm Panel Discussion on Academic–Industry Relations / Collaborations
Panelists:
Ning Bi (Qualcomm VP Engineering)
Vitaly Feldman (Apple ML Research)
Katherine Heller (Google Responsible AI)
Tara Javidi (UCSD)
Somdeb Majumdar (Intel AI/ML Lab)
Moderator: Vijay Kumar (UPenn)
3:00 – 3:30pm Break
3:30 – 5:00pm SESSION 3  Chair: Henrik Christensen (UCSD)
Industry Keynote: Foundation Models for Robotics, Carolina Parada (Google DeepMind)
TILOS Faculty Highlights:
[4:20pm] Semantic Mapping and Task Planning for Autonomous Robots, Nikolay Atanasov (UCSD)
[4:40pm] Bias in Evaluation Processes: An Optimization-Based Model, Nisheeth Vishnoi (Yale U)
5:00 – 7:30pm Buffet Dinner + Trainee Poster Session (HDSI 123 & 155)

KEYNOTE PRESENTATION ABSTRACTS

Towards Scalable and Robust Autonomy

How we design and deploy highly autonomous robots such as self-driving cars is evolving rapidly, and there are numerous technical challenges in how to deploy an autonomous system at scale. I will describe some of the technical design decisions in developing an autonomous robotic at scale, some of the candidate solutions and open questions for the future.

Nicholas Roy is the Autonomy Architecture Lead and a principal software engineer at Zoox. He and his team address technical challenges that cut across the autonomy verticals, leading the design and deployment of cross-functional capabilities in the Zoox autonomy system. He is also the Bisplinghoff Professor of Aeronautics & Astronautics and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology. Roy’s research focuses on decision-making under uncertainty, mobile robot autonomy and human-robot interaction. Roy’s research has been transitioned into multiple commercial applications.

AI and Networks: Challenges & Opportunities

Artificial Intelligence and Machine Learning (AI/ML) Technologies are widely expected to play an integral role in the design and architecture of Next Generation Networks. We present several applications where AI/ML techniques are used to enhance the performance of wireless networking systems, as well as discuss approaches to enhance AI computations over resource constrained networks. We also highlight the importance of ensuring resilience of network AI solutions and discuss future directions.

Nageen Himayat is a Senior Principal Engineer with the Security and Privacy Research Labs. She leads the Trusted & Distributed Intelligence (TDI) team conducting research on trustworthy AI and network security topics. Her research contributions span areas such as AI security, distributed ML, machine learning for networks, multi-radio heterogeneous networks, cross layer radio resource management, and non-linear signal processing techniques. Nageen has authored over 350 technical publications, contributing to several IEEE peer-reviewed publications, 3GPP/IEEE standards, as well as numerous patent filings. Prior to Intel, Nageen was with Lucent Technologies and General Instrument Corp, where she developed standards and systems for both wireless and wire-line broadband access networks. Nageen obtained her B.S.E.E degree from Rice University, and her M.S./Ph.D. degree from the University of Pennsylvania. She also holds an MBA degree from the Haas School of Business at University of California, Berkeley.

Foundations Models for Robotics

Foundation models have unlocked major advancements in AI. In this talk, I will discuss how foundation models are enabling a step function in progress towards general purpose robots, including enabling robots to understand, reason, hold situated conversations with humans and learn from them, transfer visual and semantic generalization to real world actions, and show initial signs of transfer between robot embodiments.

It is still early in this research journey but it is an exciting one because we can confidently be part of this fantastic fast and dynamic field of foundation models and not only ride the wave of innovation, but help shape it. With this new approach, we have to once again ask all the tough questions, and call for advances in perception, grounded reasoning, and safety to build more advanced embodied foundation models, while leveraging the human-centeredness, semantic understanding, and natural interaction that these models seamlessly enable. We’re just getting started.

Dr. Carolina Parada is an Engineering Director at Google DeepMind Robotics who is passionate about developing useful robots through human centered robot learning. Since 2019, she leads multiple research groups in robot learning, perception, simulation, and embodied reasoning. Prior to that, she led the perception team for self-driving cars at Nvidia for 2 years. She was also a lead with Speech @ Google for 7 years, where she drove research and engineering efforts that enabled all the voice products at Google.

Location: Halıcıoğlu Data Science Institute [MAP]
Room 123
3234 Matthews Lane
La Jolla, CA 92093

Contacts: Angela Berti (aberti@ucsd.edu), Yusu Wang (yusuwang@ucsd.edu)

Parking: Hopkins Parking Structure (9800 Hopkins Dr, La Jolla, CA 92093; 10 minute walk to venue).

Parking fees are payable at pay stations or pay-by-phone. Note that many visitor spots are limited to two hours. Even though the app allows you to pay for longer periods, you will get a ticket after that time if parked in a 2-hour space.

Local Time

  • Timezone: America/New_York
  • Date: 18 Jun 2024
  • Time: 11:00 - 22:30

Location

Halıcıoğlu Data Science Building Room 123
3234 Matthews Ln, La Jolla, CA 92093

Organizer

TILOS

Speakers