Presenters: Prof. Karl-Erik Arzen (Co-Director of WASP and Lund University), Dr. Paul Townend (WASP Graduate School management and Umeå University), and Carl Magnus Bruhner (Linkoping University) Abstract: The Wallenberg AI, […]
Most optimization problems face the challenge of computing an optimum solution requiring superpolynomial time. In particular, they are classified as NP-hard problems that have no polynomial-time algorithm to date. Instead, computer scientists turn to find an approximate solution and create numerous elegant algorithms. However, in the modern era, computational environments have changed drastically, and we […]
Presenter: Chris Jay Hoofnagle, Frederik Zuiderveen Borgesius, Lothar Determann, Pieter T.J. Wolters Abstract: The European Union has enacted a comprehensive cybersecurity framework (the “Framework”) that imposes far-reaching obligations on developers of standalone software and connected products. This Article describes the European legislative approach before turning to a description of the Framework. Anchored by the Cyber […]
Artificial intelligence is moving beyond passive perception toward systems that can understand, interact with, and generate the world. This dissertation studies generalist embodied world models that connect language, vision, action, and 3D scene representations. It explores how multimodal systems can ground human instructions in physical environments, reason over long-horizon tasks, generate coherent text-and-visual content, and […]
Research on fault-tolerance protocols for approximate Byzantine agreement (ABA) has largely focused on ensuring that distributed processes remain consistent despite fewer than 1/3 faulty processes. Yet in many real systems, consistency is only useful when it enables processes to make accurate decisions from replicated, noisy, and potentially adversarially corrupted data relative to an ideal fault-free […]
Join us for an exciting pre-hackathon mixer at University of California, Santa Cruz! Get ready to mingle, form teams, and start brainstorming ideas for your projects before the QBI Hackathon […]
The STEM Culture Festival is returning to UC Santa Cruz on Friday, May 15 from 1-4pm in the Baskin Engineering Courtyard. Join us! This year, we’re expanding with even more performances, activities, and creative ways to celebrate UCSC’s vibrant, diverse, and excellent STEM culture! What to expect: Cuban Dance Master Susana Arenas and her troupe […]
Welcome to the premier physical AI hackathon on the West Coast. We are bringing together the top 200 AI, infrastructure, and hardware engineers to build autonomous, agentic applications on the NVIDIA NemoClaw stack. You aren’t just calling APIs, you are building on enterprise-grade hardware. The Tracks: The Edge Track: 40 exclusive teams will be granted […]
Pattern counting is a fundamental problem in computer science with applications in many domains. For a fixed small pattern H, we are given a large graph G and we are asked to count the number of subgraphs or homomorphisms (edge-preserving maps) of H in G. For practical applications where the input graph can be very […]
Presenter: Arman Zharmagambetov, Meta Abstract: Ensuring the safety of language models (LMs) while maintaining their usefulness remains a critical challenge in AI alignment. Current approaches rely on sequential adversarial training: generating adversarial (harmful) prompts and fine-tuning LMs to defend against them. We introduce a different paradigm: framing safety alignment as a non-zero-sum game between an […]
The annual BE Student Project Showcase celebrates the innovative work and accomplishments of undergraduate engineers in capstone courses and research pathways.
This work addresses improvements in branch prediction mechanism to support high perfor- mance processors. The state of the art aims to balance the prediction latency and prediction accuracy using multi level correcting predictors . Prior published work focusses on scalar designs and prediction accuracy improvement for hard to predict branches employing tailor made, non generic […]
Autonomous Cyber Operations (ACO) agents promise effective security automation with minimal human intervention, yet their deployment raises three interconnected challenges: agents must be realistic (reproducing diverse attacker sophistication), secure (preventing autonomy from becoming an attack surface), and feasible (safely replicating human behavior at full autonomy). We argue that these three properties are requirements for ACO […]
Multimodal large language models (MLLMs) are rapidly becoming general-purpose AI systems, yet their capabilities are advancing faster than our ability to evaluate, improve, and validate their reliability in realistic use. Standard benchmarks mainly measure in-distribution final-answer accuracy, leaving critical gaps in safety, robustness, fine-grained reasoning evaluation, and reliability in real-world agentic settings. My research proposes […]
Presenter: Laura Waller, UC Berkeley Abstract: Computational imaging jointly designs hardware and algorithms to push beyond the classical limits of imaging, enabling measurement of new quantities (e.g. 3D, phase, and super-resolution) with simple, inexpensive hardware. These approaches have already transformed consumer photography; our goal is to achieve a similar transformation in scientific microscopy. In this […]
Modern system software increasingly needs runtime extensibility: userspace applications need safe ways to expose domain-specific extension points, GPU resource management needs workload-specific memory and scheduling policies, and kernel eBPF JIT compilers need different runtime optimizations as workloads and hardware vary. However, built-in policies are safe but difficult to specialize across rapidly changing workloads and hardware […]
Modern datacenter CPUs lose 25–66% of execution cycles to instruction-delivery stalls. This bottleneck persists, despite the recent trend towards accelerators and GPUs, as there is continuing demand by applications that only execute on CPUs. Two workload classes dominate today’s datacenter execution cycles: hyperscale server software (databases, build systems, and content stores), whose large instruction footprints […]
Autonomous systems, such as Autonomous Vehicles (AVs) and drones, are increasingly deployed across a wider array of contexts for both civilian and military use. As these systems become more common, they may be targeted by malicious actors seeking to exploit and abuse them, compromising safety-critical operations. Among the ways to protect these systems simulation based […]
A central goal on the path toward general AI is to build systems capable of deliberative reasoning before action. Such systems should inspect what they know, identify what they need, seek or construct useful information, and revise their reasoning through intermediate cognitive states. This dissertation studies this goal through the lens of Inner Monologue (IM), […]
This dissertation investigates how to make modern AI systems safer as they grow more capable. It addresses two central sources of risk: malicious misuse, in which adversarial users coerce models into harmful behavior, and internal misalignment, in which models themselves pursue goals that diverge from human intent through deception, sandbagging, or other covert behaviors. The […]