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

Develop an NLP model for a legal billing software company to answer client questions

Create quantum machine learning models to generate natural language using parameterized quantum circuits and category theory NLP.

Generate rock climbing moves using RNNs and Transformers. Climbing made easy.

Generate video game worlds in Blender with NeRFs and style transfer.

Project Archives

Extract from black-boxed models and adversarially attack various architectures using replicated models

Convert pictures of food to fancy plated versions through a novel transformer architecture and latent diffusion models

Efficiently train and deploy machine learning models with limited memory

Train a model to generate audio in your own voice, using signal processing techniques, GANs and autoencoders

Create a web app where users can generate their own lofi and game beats to study/chill to using transformers and LSTMs

Use different unsupervised/clustering models to detect anomalies in high-dimensional sensor data

Train an imitation learning agent to recreate stylized motions on simulated characters

Transfer styles of pokemon sprites onto pet images using GANs and contrastive learning

Create Geoguessr bot that predicts GPS locations given image using CNNs and LSTMs

Humanize computer music to match the lifelikeness of real performance with VAEs and transformers

Develop an intelligent Mario Kart agent that can replicate the skill and technique of a human player using behavior cloning algorithms

Converting rap lyrics to Shakespearian-style text using Transformers and RNNs. The 1500's never looked so dope.

Creating high-quality 3D reconstructions from photos of our own. Each member will choose variable scenes and items to reconstruct with NeRF and various follow up methods.

Experiment with a VQ-VAE based network for converting audio to the style of another audio file

Create a voice conversion model framework for voice assistants, implementing data generation, spectral analysis, and an Amazon Lex-based web app


Artificially stain various cellular samples using cutting edge style transfer techniques

Build a production ready virtual assistant chatbot with robust machine learning pipelines and slack integration

Enable semantic search through images and other mediums in a zero-shot manner with CLIP

Few-shot meta learning to learn handwriting styles and generate similar handwritten text using GANs

Experiment on multi-agent reinforcement learning for playing the popular sport, soccer

Apply Computer Vision techniques to improve tiny object detection on measuring roof debris and damage

Build an encoder for images that can perform few-shot training across CV tasks using unsupervised learning

Explore adversarial models to track sleep stages by comparing results from watch and radio frequency data to brain wave data

Develop a profitable trading strategy for the market today based on common technical indicators

Create an AI web app using Monte Carlo sampling, deep and reinforcement learning to play heads up and nine handed no-limit Texas Hold'em poker

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

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