Cleah Winston

B.S. in Computer Science @ University of Washington, Seattle (June 2026)

Robotics Research Student @ UW Robotics

Software Developer @ Neurophys

Teaching Assistant @ Paul Allen School, UW

View My Work Download Resume

About Me

I'm currently pursuing a B.S. in Computer Science with a minor in Business Administration at the University of Washington, Seattle. My work focuses on robotics, LLMs, machine learning, and neural engineering. I'm passionate about leveraging technology to create real-world impact and improve task efficiency. Specifically, I explore reinforcement learning for robot manipulation tasks and the application of LLMs in healthcare.

Publications

Medical Question-Generation for Pre-Consultation

Medical Question-Generation for Pre-Consultation with LLM In-Context Learning

GenAI4Health, NeurIPS 2024 Poster

Caleb Winston, Cleah Winston, Claris Winston, Chloe Winston

Google Scholar
Multimodal Clinical Prediction

Multimodal Clinical Prediction with Unified Prompts and Pretrained Large-Language Models

IEEE International Conference on Healthcare Informatics, 2024

Caleb Winston, Chloe Winston, Cailin Winston, Claris Winston, Cleah Winston

Google Scholar
Repairing Brain-Computer Interfaces

Repairing Brain-Computer Interfaces with Fault-Based Data Acquisition

IEEE International Conference on Software Engineering, 2022

Cailin Winston, Caleb Winston, Chloe N Winston, Claris Winston, Cleah Winston, Rajesh PN Rao, René Just

Google Scholar
Precisely Detecting and Resolving BCI Errors

Precisely Detecting and Resolving BCI Errors With Case Functions

IEEE Engineering in Medicine & Biology Society, 2021

Chloe N Winston, Cailin Winston, Caleb Winston, Claris Winston, Cleah Winston, Rajesh P N Rao

Google Scholar

Research Projects

Learning Recovery-Based Robot Manipulation Policies on Out-of-Distribution Tasks with Diffusion and Offline RL

June 2024 - Present
Robot Learning Lab, WEIRD Lab @ UW

In collaboration with the RLL & WEIRD Labs, I am working on training reinforcement learning (RL) and diffusion-based models for recovery tasks on for robot manipulation tasks. We use data from the Franka Emika robot arm.

Large Language Models for Clinical Predictions

Oct. 2023 – Sept. 2024
UW, Stanford University, University of Pennslyvania 2024 International Conference of Health Informatics, 2024 GenAI4Health (NeurIPS) 2nd @ MD Plus Datathon on value-based care

Along with a team of researchers, I developed a chatbot which collects patient information to curate a history of present illness (HPI).

Improving Robotic Car Navigation Algorithms

Sept. 2022 – May 2024
Affiliation: Robot Learning Lab @ UW 2024 Undergraduate Research Symposium

I trained convolutional neural networks to predict steering angles to follow a road from simulated data from AirSim. I then investigated whether robust training can be achieved with simulated data and less real data, collected from MuSHR cars.

Augmented Reality for Physical Therapy

Sept. 2023 – Feb. 2024
UW CSE, Foster School of Business, UW Medicine Finalist at Holloman Health Innovation Challenge

Along with my team, we developed a prototype for a AR-based system using the Meta Quest Pro that creates a more immersive and interactive form of doing at-home physical therapy. We created a business plan for our product and pitched at the 2024 Holloman Health Innovation Challenge, UW.

Repairing Brain-Computer Interfaces (BCI) with Fault-Based Data Acquisition

April 2021 – May 2022
UW CSE 2022 International Conference on Software Engineering Publication.

We developed a technique to debug brain-computer interfaces real time using focused data acquisition and data labeling techniques. I replicated a cursor-manipulation neural decoder to evaluate our system.

Assessing Neurostimulation as Therapy for Spinal Cord Injury

June 2021 – September 2021
Restorative Technologies Laboratory, UW Publication.

Using ImageJ software, I analyzed images of spinal cord sections to quantify the recovery of vasculature in injured sites following spinal cord injury in rats.We found that optogenetic neurostimulation improved vasculature recovery

Modeling the Human Haptic Code

Sept. 2020 – March 2021
Courtine Paschall, UW BioEngineering 1st @ WSSEF 2021, US Air Force Award, 2nd in Software and Embedded Systems @ 2021 CRSEF More info.

I developed machine learning models to predict objects touched/imagined using EEG data I collected from a user study. I then developed a conditional variational autoencoder to predict the neural data given the tactic labels with the gaol of improving prosthetic neural encoding.

Detecting Driver Distraction Using Neural Decoding and ML

Dec. 2019 – May 2020
Courtnie Paschall, UW BioEngineering 1st @ WSSEF 2020, 2020 Student Scholar Symposium (Sigma Xi) More info.

I designed a ML-based system to predict distracted driving from EEG data. I collected data through a user study where subjects were placed in distracting situations while operating a virtual car. I trained regression models and neural network decoders.

Software Projects

MyScoliCare: An App for Scoliosis Care

Nov. 2018 – May 2019
Conference on Non-Operative Treatment of Childhood Scoliosis, Columbia University More info.

We developed an Android and iOS app for motivating scoliosis patients to complete Schroth therapy and daily bracing. Our app was endorsed by Dr. Manuel Rigo (MD/PhD), the head of the Barcelona Scoliosis Physical Therapy School. Additionally, we have reached over 100 therapists globally and many scoliosis patients.

PriceNet

Nov. 2018 – May 2019
1st place at WSSEF 2019, Naval Science Award, Broadcom MASTERS nominee

I designed a fruit ripeness sensor and a reinforcement-learning system that processes sales data and ripeness sensor data to suggest effective selling prices to minimize fruit wastage. I designed a circuit system that detects the color of fruits based on photoresistor signals.

Investigating Cybersecurity in Driverless Cars

Sept. 2017 – March 2018
1st place at WSSEF 2018, top 300 Broadcom MASTERS nominee

I built a robotic car by programming an Arduino UNO board, to understand the risk of cyberattacks on driverless cars. I designed and conducted experiments to further investigate how cybersecurity is a real issue for autonomous vehicles.

Work Experience

Neurophys [Software Developer]

Aug. 2024 - Present

I am desigining AI-based technology for developing customized, at-home rehabilitation plans for patients recovering from neuro deficits.

Paul Allen School of Computer Science [Teaching Assistant]

Sept. 2023 - Present

I am a 5th time teaching assistant (TA) for machine learning, discrete math, and probability classes for computer science. As part of being a TA, I lead weekly ~30 student sections, assist students through office hours and 1-1 sessions, help with course logistics (e.g., running the website), host review sessions, and proctor exams.

Banyan Computing [Backend Developer Intern]

Sept. 2021 – April 2022

At Banyan, I developed Banyan Processes, a feature that enables users to save Julia scripts to the cloud and schedule them for later execution. Additionally, I implemented features to allow users to manage their cloud spending.

Skills

Languages

Python Java HTML/CSS JavaScript React JS Julia C System Verilog

Libraries

PyTorch Scikit-learn NumPy Pandas AWS

Technical Skills

Machine Learning Website Development Data Analysis Experiment Design