Ethan Tam Email & Phone Number

California, United States

• Neural Systems and Machine Learning Lab
• Developing a transformer-based model to generate more stable proteins using protein sequences and structures

• Building apps for non-profits!

San Francisco, California, United States

• Mobility and Delivery Engineering - Rider Foundations
• Built a full-stack web application using Fusion.js, Typescript, and Tailwind CSS for an internal tool to execute GraphQL queries to a backend router and visualize API relationships. Serving over 50 engineers.
• Deputized test account query executions by creating a middleware layer in a backend router using Go to improve developer testing and debugging experience.
• Enhanced GraphQL schema by adding a new field, constructed handler logic adhering to Glue architecture principles, and wrote comprehensive unit tests for end-to-end testing. Landed feature within first 2 weeks.

• Teach data structures and algorithms concepts to 5 students

• Developed a machine learning model to predict offset values for defocused microscopy image data

• Lead a team of 7 to maintain and develop new features for robust web application serving Berkeley’s high-traffic food pantry
• Github: https://github.com/CalNourish/pantry-webapp

Ashburn, Virginia, United States

• Janelia-Meyerhoff Summer Research Scholar in the Funke Lab
• Designed and developed a self-supervised deep learning-based pipeline for cell tracking in microscopy sequences of C. elegans
• Utilized the convolutional neural network U-Net to identify cell coordinates in volumetric data with 81% accuracy
• Leveraged contrastive learning framework and graph neural network to accurately match cells across sequential time frames
• Conducted relevant literature reviews and synthesized key findings during lab meetings in a concise, understandable manner
• Accepted for poster presentation at the 2023 SACNAS NDiSTEM Conference

• Selected among 4% of candidates for the 2023 Uber Career Prep Program
• Mentored 1x1 by an Uber Software Engineer on data structures and algorithms competencies, soft skills, and technical interview performance

Cattamanchi Lab

• Developed data-cleaning code in R and Stata to correct errors, filter inconsistencies, and validate data in large patient datasets
• Trained and tested machine learning algorithm with CXR dataset to predict pulmonary tuberculosis presence in children’s chest X-ray scans
• Automated and optimized data pipeline to clean and process hundreds of chest X-ray data, improving time efficiency by 94%
• Collaborated with the Cattamanchi Lab, an international team of data scientists, statisticians, and clinical researchers in the 3HP Options Trial and R2D2 TB Network (Rapid Research in Diagnostics Development) projects

B.A. Computer Science, Data Science, 3.8 Gpa

Activities and Societies: SEED Scholars Honors Program, Blueprint, ANova, Computer Science MentorsRelevant Coursework • CS 61A: Structure.

Education record

Activities and Societies: The Apogee Report, MedCats, Arrupe Social Justice Council, Inside SI, The Quill, Symphonic Orchestra, Asian.