Center for Computation and Visualization
Advancing computational research with scientific and computing expertise.
Our Mission
We provide scientific and technical computing expertise to advance computational research and support Brown's academic mission.
Research Support
We partner with researchers, combining diverse expertise across disciplines to transform complex projects into groundbreaking discoveries.
Compute Infrastructure
We maintain secure, high‑performance computing infrastructure, along with file-storage-and-transfer solutions and virtual computing environments to support research and innovation.
The CCV Impact
Featured Projects
CCV AI Tools provides a set of generative AI tools that are built and deployed in-house at Brown for all members of the Brown community. These tools include:
- LibreChat (under construction): A chat interface that lets you talk to multiple AI models in a private, customizable way
- Transcribe: Transcribe audio files in over 20 different languages to text using state-of-the-art AI models such as Google Gemini and OpenAI Whisper.
- Ask Oscar (under construction): An AI assistant that can answer questions based on documentation of CCV and other Brown services.
The Gearshift Fellowship is a car-driving game where players take the role of a driver and aim to complete five missions, each with distinct goals and challenges, while collecting as many reward points as possible. Developed with HTML, CSS, and JavaScript, the experiment and data collection run on jsPsych and are built on Honeycomb, an open-source template that integrates cognitive science and web development, enabling researchers to create psychophysiological tasks that interface with lab equipment such as EEG.
Our team supported early software development for the Gearshift Fellowship prototype, a research platform conceptualized and designed by Dr. Nadja Ging-Jehli to study adaptive decision-making.
IceFloeTracker.jl is an open-source Julia package for tracking Arctic Ocean ice floes using data from the Aqua and Terra Earth-observation satellites. It detects floe trajectories and rotation rates to infer ocean currents and eddies, providing datasets that validate and inform ocean models within broader climate research. A built-in workflow manager scales analyses from regional studies to the entire Arctic over decade-long timescales.
SOMA is an app from Brown University researchers designed to help people with acute and chronic pain. By allowing you to track symptoms and daily activities, SOMA provides insights into your pain and recovery patterns. You can use this data for your own understanding or share it with your healthcare provider to help guide your treatment. Available for free on the App Store and Google Play, SOMA is designed to empower you with a better understanding of your pain.
This project implements a comprehensive pipeline and application designed to assist researchers in identifying, labeling, and counting cells in mouse brain scans. Utilizing pre-trained deep learning models, the system analyzes 3D image data to automatically segment cells and generate structured results. This automated approach significantly reduces manual effort, accelerates research workflows, and improves consistency by minimizing human bias in segmentation and labeling processes, enabling neuroscience researchers to focus on analysis and interpretation rather than time-intensive manual cell identification.