AI Frontier: Data, Agents & Robots at TechWeek SF
Join us for an immersive SF Tech Week experience hosted by the Silicon Valley AI Pioneer Club and UC Santa Cruz GenAI Center — where AI builders, investors, innovators and […]
The Computer Science and Engineering (CSE) department housed within the Baskin School of Engineering spans multiple areas of research including theory, systems, AI/ML, architectures, and software. In cooperation with other departments on campus, CSE also offers a strong research group in bioinformatics, computational biology, biomolecular engineering, and human genome mapping. The CSE department enjoys a close relationship with the Electrical and Computer Engineering, Applied Mathematics, and Statistics departments. Faculty members carry out joint research projects, supervise students, and teach courses for these departments.
Join us for an immersive SF Tech Week experience hosted by the Silicon Valley AI Pioneer Club and UC Santa Cruz GenAI Center — where AI builders, investors, innovators and […]
Here is a chance to meet tech recruiters in person! If you are interested in pursuing a career in science, technology, engineering, mathematics or research, then take advantage of this opportunity to meet recruiters from companies looking to fill various positions (both technical and non-technical). Learn more about internships and full-time career opportunities. Undergraduate students, […]
Join us for this virtual info session on the 2025–26 CITRIS Aviation Prize, an exciting multi-campus student competition inviting teams to design innovative solutions for the future of air mobility across the University of California. The session will cover this year’s competition guidelines, key dates and requirements, and available resources. Attendees will also have the opportunity […]
Presenter: Hans Boehm, Google Abstract: C++11 extended the language to include threads, defining a concurrency memory model to specify the semantics of shared variables, including “atomic” variables that can be accessed without mutual exclusion. Although this followed Posix threads by more than a decade, and the revision of the Java memory model by a few […]
Speaker: Koushik Sen, UC Berkeley and Google DeepMind Abstract: Coding has emerged as an important application area for large language models (LLMs), with a proliferation of code-specific models and their applications across various domains and tasks such as program repair, performance optimization, debugging, test generation, documentation, and security hardening. In this talk, I will describe […]
Presenter: Roozbeh Mottaghi, University of Washington Abstract: Data has revolutionized progress across AI fields like natural language processing and computer vision. Yet, in robotics, data collection remains a significant challenge: robots must interact with complex, dynamic environments, making the process slow, costly, and difficult to scale. In this talk, I will discuss how simulation is […]
The United Nations (UN) and the Baskin School of Engineering at the University of California, Santa Cruz, are collaborating to bring the “Reboot the Earth” hackathon to the West Coast for the first time. This is a social event bringing together aspiring developers to create open source software solutions that address the climate crisis, including […]
Modern AI systems demand low-latency high-quality retrieval and serving over billion-scale keys and vectors. This proposal studies learned hashing and overlay networks to co-locate semantically related items and steer queries with minimal coordination. We first present LEAD, to our knowledge the first use of order-preserving learned hash functions in distributed key-value overlays, enabling efficient range […]
Presenter: Luis Lamb, Catholic Institute of Technology Abstract: Neurosymbolic AI brings together the statistical nature of machine learning with the formal reasoning capabilities of symbolic AI. It seeks to offer a balanced approach to contemporary AI technologies, by combining the ability to learn from data, with the capacity to reason upon knowledge acquired from an environment. […]
This dissertation focuses on designing and proving performance guarantees on algorithms when there is uncertainty in the input. The uncertainty could be from the user being unsure or future inputs that have not arrived yet. We look at different methods in which algorithms can be designed to be competitive against the optimal. One of the […]