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DTSTART;VALUE=DATE:20240618
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UID:7308-1718668800-1718755199@tilos.ai
SUMMARY:TILOS Industry Day 2024
DESCRIPTION: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. \nAGENDA\n\n\n\n\n\n\n\n8:00 – 8:45am\nRegistration + Breakfast\n\n\n8:45 – 9:00am\nWelcome Remarks and Introduction to TILOS\nDirector Yusu Wang (UCSD)\nAD Translation Vijay Kumar (UPenn)\nRajesh Gupta (Director of HDSI@UCSD)\n\n\n9:00 – 10:30am\nSESSION 1  Chair: Vijay Kumar (UPenn)\nIndustry Keynote: Towards Scalable and Robust Autonomy\, Nicholas Roy (Zoox)\nTILOS Faculty Highlights:\n[9:50am] Traceable and Scalable GNN-based Circuit Optimization\, Farinaz Koushanfar (UCSD)\n[10:10am] Feature learning in neural networks and kernel models\, Misha Belkin (UCSD)\n\n\n10:30 – 10:45am\nBreak\n\n\n10:45am – 12:15pm\nSESSION 2  Chair: Yian Ma (UCSD)\nIndustry Keynote: AI and Networks: Challenges & Opportunities\, Nageen Himayat (Intel Labs)\nTILOS Faculty Highlights:\n[11:35am] Learning-enabled Optimization at Scale in Wireless Communications and  Networking\, Alejandro Ribeiro (UPenn)\n[11:55am] Reasoning Numerically\, Sean Gao (UCSD)\n\n\n12:15 – 2:00pm\nTILOS Trainee Poster Lightning Preview Session + Lunch\n\n\n2:00 – 3:00pm\nPanel Discussion on Academic–Industry Relations / Collaborations\nPanelists:\nNing Bi (Qualcomm VP Engineering)\nVitaly Feldman (Apple ML Research)\nKatherine Heller (Google Responsible AI)\nTara Javidi (UCSD)\nSomdeb Majumdar (Intel AI/ML Lab)\nModerator: Vijay Kumar (UPenn)\n\n\n3:00 – 3:30pm\nBreak\n\n\n3:30 – 5:00pm\nSESSION 3  Chair: Henrik Christensen (UCSD)\nIndustry Keynote: Foundation Models for Robotics\, Carolina Parada (Google DeepMind)\nTILOS Faculty Highlights:\n[4:20pm] Semantic Mapping and Task Planning for Autonomous Robots\,  Nikolay Atanasov (UCSD)\n[4:40pm] Bias in Evaluation Processes: An Optimization-Based Model\, Nisheeth Vishnoi (Yale U)\n\n\n5:00 – 7:30pm\nBuffet Dinner + Trainee Poster Session (HDSI 123 & 155)\n\n\n\nKEYNOTE PRESENTATION ABSTRACTS \nTowards Scalable and Robust Autonomy \nHow 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. \nNicholas 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. \n\nAI and Networks: Challenges & Opportunities \nArtificial 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. \nNageen 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. \n\nFoundations Models for Robotics \nFoundation 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. \nIt 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. \nDr. 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. \n\n\n		\n		\n			\n				\n			\n				\n				Nageen Himayat of Intel Labs presents “AI and Networks: Challenges & Opportunities” at TILOS Industry Day 2024\n				\n			\n				\n			\n				\n				Student and postdoc poster session at TILOS Industry Day 2024\n				\n			\n				\n			\n				\n				Sean Gao (UC San Diego) presents “Reasoning Numerically” at TILOS Industry Day 2024\n				\n			\n				\n			\n				\n				Demonstration of a Robotic Art outreach activity at TILOS Industry Day 2024\n				\n			\n				\n			\n				\n				TILOS Robotics team member Nikolay Atanasov (UC San Diego) presents “Semantic Mapping and Task Planning for Autonomous\nRobots” at TILOS Industry Day 2024\n				\n			\n				\n			\n				\n				Student and postdoc poster session at TILOS Industry Day 2024\n				\n			\n				\n			\n				\n				TILOS Associate Director of Translation and University of Pennsylvania Dean of Engineering Vijay Kumar (right) moderates a discussion on Academic–Industry Relations and Collaboration at TILOS Industry Day 2024 with panelists (from left) Ning Bi (Vice President of Engineering\, Qualcomm)\, Vitaly Feldman (Apple ML Research)\, Katherine Heller (Google Responsible AI)\, Tara Javidi (Professor of Electrical and Computer Engineering\, UC San Diego)\, and Somdeb Majumdar (Director\, Intel AI/ML Lab)\n				\n			\n		\n\nLocation: Halıcıoğlu Data Science Institute [MAP]\nRoom 123\n3234 Matthews Lane\nLa Jolla\, CA 92093 \nContacts: Angela Berti (aberti@ucsd.edu)\, Yusu Wang (yusuwang@ucsd.edu) \nParking: Hopkins Parking Structure (9800 Hopkins Dr\, La Jolla\, CA 92093; 10 minute walk to venue). \nParking 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.
URL:https://tilos.ai/event/tilos-industry-day-2024/
LOCATION:HDSI 123 and Virtual\, 3234 Matthews Ln\, La Jolla\, CA\, 92093\, United States
CATEGORIES:TILOS Sponsored Event
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