uc

The University of California Open Source Repository Browser (UC ORB) is a discovery tool designed to map and classify open source projects across the UC system. This project is a collaboration with the UC Network of Open Source Program Offices (OSPOs), which brings together six UC campuses (Santa Cruz, Berkeley, Davis, Los Angeles, Santa Barbara, and San Diego) to support open source research, promote sustainability, and establish best practices within academic environments.

FairFace: Reproducible Bias Evaluation in Facial AI Models via Controlled Skin Tone Manipulation Bias in facial AI models remains a persistent issue, particularly concerning skin tone disparities. Many studies report that AI models perform differently on lighter vs.

ReasonWorld: Real-World Reasoning with a Long-Term World Model A world model is essentially an internal representation of an environment that an AI system would construct based on external information to plan, reason, and interpret its surroundings.

Recent advancements in Large Language Models (LLMs) have transformed various fields by demonstrating remarkable capabilities in processing and generating human-like text. This project aims to explore the development of an open-source framework that leverages LLMs to enhance discovery across specialized domains.

Parallel I/O is a critical component in high-performance computing (HPC), allowing multiple processes to read and write data concurrently from a shared storage system. HDF5—a widely adopted data model and library for managing complex scientific data—supports parallel I/O but introduces challenges in I/O reproducibility, where repeated executions do not always produce identical results.

We are interested in developing navigation aids for visually impaired people (VIP) using AR/VR technologies. Our intended use is primarily indoors or outdoors but within private confines e.g. person’s backyard. Using AR/VR headsets or smart glasses allows navigation without using a cane and frees the users’ hands for other tasks.

CarbonCast is a machine-learning-based approach to provide multi-day forecasts of the electrical grid’s carbon intensity. Developed in Python, the current version of CarbonCast delivers accurate forecasts in numerous regions by using historical source production data of a particular geographical region, time of day/year, and weather forecasts as features.

Vector Embeddings Dataset Topics: Vector Embeddings LLMs Transformers Skills: software development, apis, scripting, python Difficulty: Moderate Size: Medium or Large (175 or 350 hours) Mentors: Jayjeet Chakraborty To benchmark vector search algorithms (aka ANN algorithms), there are several datasets available but none of them represent actual real world workloads.

Brahma is a lightweight framework for building collaborative and cross platform WebXR based experiences using Three.js for the front-end and a simple Node.js/WebSocket script on the backend. It was created at the Social Emotional Technology Lab to facilitate the development of novel collaborative interfaces and virtual environments capable of loading scientific datasets.

WildBerryEye leverages Raspberry Pi and YOLO object detection models to monitor pollinizers like bees and hummingbirds visiting flowers. This initiative aims to enhance environmental research by automating data collection and analysis of pollinator activities, which are crucial for ecological assessments and conservation efforts.