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  • Headshot of Dr. Koushil Sreenath

    TILOS-HDSI Seminar: Safety, Representations, and Generative Learning in Dynamical Systems

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Koushil Sreenath, UC Berkeley Abstract: This talk explores the interplay between model-based guarantees and learning-based flexibility in the control of dynamical systems. I begin with safety-critical control using control barrier functions (CBFs), highlighting that while CBFs enforce state constraints, they may induce unstable internal dynamics. I introduce conditions under which CBF-based safety filters ensure boundedness […]

  • Headshot of Dr. Tengyu Ma

    Canceled [CANCELED] Optimization for ML and AI Seminar: Fantastic Pretraining Optimizers and Where to Find Them

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Tengyu Ma, Stanford Abstract: AdamW has long been the dominant optimizer in language model pretraining, despite numerous claims that alternative optimizers offer 1.4 to 2x speedup. We posit that two methodological shortcomings have obscured fair comparisons and hindered practical adoption: (i) unequal hyperparameter tuning and (ii) limited or misleading evaluation setups. To address these two […]

  • Headshot of Dr. Yang Zheng

    Optimization for ML and AI Seminar: Extended Convex Lifting for Policy Optimization in Control

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Yang Zheng, UC San Diego Abstract: Direct policy search has achieved great empirical success in reinforcement learning. Many recent studies have revisited its theoretical foundation for continuous control, which reveals elegant nonconvex geometry in various benchmark problems. In this talk, we introduce an Extended Convex Lifting (ECL) framework, which reveals hidden convexity in classical optimal […]

  • Headshot of Dr. Sung-Kyu Lim

    TILOS-MICS Seminar: AI-Driven Design Automation for Multi-Chip Integration in AI Chips

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Sung-Kyu Lim, University of Southern California Abstract: Multi-chip integration has become a standard approach in AI training and is rapidly gaining traction in edge learning applications. Leveraging 2.5D and 3D IC architecture enables substantial improvements in energy efficiency and latency by optimizing inter chip data transfer. At the core of this transformation lies the automation […]

  • Headshot of Dr. Maarten de Hoop

    TILOS-HDSI Seminar: Kinetic Theory Perspective of Foundation Models for Physics

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Maarten de Hoop, Rice University Abstract: We present a kinetic theory perspective of foundation models for physics. We begin with providing a mathematical framework for analyzing transformers. To uniformly address their expressivity, we consider the case that the mappings are conditioned on a context represented by a probability distribution of tokens. That is, transformers become […]

  • Headshot of Dr. Jason Eshraghian

    TILOS-HDSI Seminar: Neuromorphic LLMs

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Jason Eshraghian, UC Santa Cruz Abstract: This talk will show you what neuromorphic computing can do when an academic lab accidentally pulls $2-million of GPU-hours. We will showcase a series of frontier reasoning LLMs developed out of an academic lab, from data curation and pre-training to post-training and alignment. These models surpass leading LLMs from […]

  • Headshot of Dr. Bharath Sriperumbudur

    Optimization for ML and AI Seminar: (De)regularized Wasserstein Gradient Flows via Reproducing Kernels

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Bharath Sriperumbudur, Pennsylvania State University Abstract: Wasserstein gradient flows have become a popular tool in machine learning with applications in sampling, variational inference, generative modeling, and reinforcement learning, among others. The Wasserstein gradient flow (WGF) involves minimizing a probability functional over the Wasserstein space (by taking into account the intrinsic geometry of the Wasserstein space). […]

  • Headshot of Dr. Yuejie Chi

    Optimization for ML and AI Seminar: Transformers Learn Generalizable Chain-of-Thought Reasoning via Gradient Descent

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Yuejie Chi, Yale Abstract: Transformers have demonstrated remarkable chain-of-thought reasoning capabilities, yet, the underlying mechanisms by which they acquire and extrapolate these capabilities remain limited. This talk presents a theoretical analysis of transformers trained via gradient descent for symbolic reasoning and state tracking tasks with increasing problem complexity. Our analysis reveals the coordination of multi-head […]

  • TILOS-SDSU ExpandAI Workshop

    Qualcomm Conference Center (Jacobs Hall first floor) 9736 Engineers Ln, La Jolla, CA, United States

    <!-- --> Agenda 1:00 – 1:10 pm: Welcome and opening remarks 1:10 – 1:30 pm: Invited talk by Dr. Lily Weng, Assistant Professor, Halıcıoğlu Data Science Institute and Department of Computer Science and Engineering, UC San Diego 1:30 - 1:50 pm: Invited talk by Dr. Reza Akhavian, Associate Professor and Jim Ryan Endowed Chair in Construction Engineering […]

  • TILOS-SDSU Seminar: Autopilots Need Parachutes: Reliability Lessons from LLM-Automated Embedded AI Systems

    Lamden Hall 341 (SDSU) and Virtual San Diego, CA, United States

    Roberto Morabito, EURECOM Abstract: Embedded AI systems are becoming increasingly complex to develop and maintain, requiring specialized workflows that span data processing, model conversion, optimization, and deployment across heterogeneous hardware platforms. Recently, large language models have emerged as a promising tool to automate parts of this lifecycle. In this talk, I present recent work investigating […]