Projects

Purpose

Our vision is to build upon growing technologies and research by translating theory into meaningful projects. With self-learning software at the frontier of technology, we can solve relevant problems through our intelligent projects. Check out how we are applying powerful algorithms to build production-ready systems.

Creative Projects

Every semester, our project leaders look for challenging problems to tackle with state of the art techniques. Each team dives deep into their respective fields and designs creative solutions to solve the problem.

Client Projects

We also work closely with industry leaders to develop machine learning solutions. We are always looking for companies to work with us! Check out our industry page for more information.

Recent Projects

A pictionary-like web game with a bot to generate and classify sketches

Building models that detect, contextualize, and identify relationships between humans and objects in images.

A web app where users can upload pictures from their photo album and generate ambient sounds and songs from the image’s scenery and emotion

Merging information between multiple cameras to track objects of interest accurately in 3D spaces

Training state of the art reinforcement learning agents to play the popular game, Super Smash Bros Melee

Project Archives

Animal information and tracking using a CNN with Raspberry Pi to send information to the cloud

Reinforcement learning in competitive environments for simulating intelligence

Universal codebook for image compression using evolutionary-based optimization methods

Fake news detecting Chrome extension incorporating NLP techniques and stance detections

Converting music between different styles/instrumentations using encoder-decoder networks in PyTorch

Post-workout image generation using generative adversarial networks

NBA playoff performance prediction from regular season data using statistical learning and neural networks

Weather forecasting using high-resolution video frame prediction using CNNs and RNNs

Answering visual questions using image and word embeddings and recurrent attention algorithms

Beautifying Berkeley with a #filter created with CycleGAN, an image to image translation neural network

Stock market trend prediction using NLP and time series analysis

Improving existing convolutional neural network architecture for real-time low-light image inferencing

Generative models for reinforcement learning to attain high performance with simplicity

Analyzing exploration and curiosity-based techniques in deep reinforcement learning

Food image generation using generative adversarial networks

Detecting and responding to dangerous driving situation by predicting collisions and road closures

Predicting driver behavior to improve rider experience in autonomous vehicles using kinematics and LSTMs

Multi-Objective Robotics solution for efficient and adaptive robot operation

Meta learning and multi-task learning

Augmenting low-fidelity images of 2D faces using 3D facial reconstruction

Generating jazz melodies in specified styles using Markov chains and clustering

Polyphonic music generation using deep neural networks

Building a human-centric computer vision API that provides optimized algorithms for object detection and tracking

Voice controlled computers using natural language processing