Trenton Chang

Stanford, CA/Logan, UT · (435) 225-1659 ·

I am a Master's student in Computer Science, Artificial Intelligence track at Stanford University. I am experienced in data analysis, machine learning, and deep learning, and have done relevant projects in the areas of computer vision, healthcare, image processing, sports, and more. I am passionate about responsible usage of AI and analyzing human-AI interaction. Please feel free to reach out via email - I love talking about my projects!


Stanford University

Master of Science
Computer Science - Artificial Intelligence Track

GPA: 3.97

January 2020 - June 2021 (expected)

Stanford University

Bachelor of Arts
American Studies - Concetration in Asian American Representation

GPA: 3.97

September 2016 - June 2020 (expected)


Kuzushiji-to-Text Image Transcription

Independent Project

Bounding box regression and classification on over 3000 scanned, expert-labeled images of Japanese calligraphy pages. Objective is OCR on Japanese calligraphy. I researched multiple architectures in the image-to-text domain, from R-CNN techniques to image captioning architectures. Baseline model is a CNN with VGG-19 feature extraction that serves as an encoder, which is then fed into a LSTM decoder with self-attention. Baseline results have approx. 40% training classification accuracy. Currently working on Faster R-CNN bounding box regression approach.

July 2019 - present

Classifying Activity from Single-Channel EEG Data

Final Project, CS 229: Machine Learning, Stanford University

Implemented multiple classification algorithms and signal processing techniques on the UCI Epilepsy dataset. Baseline models included softmax regression and k-nearest neighbors, which achieved moderate accuracy. Best model was a 1D CNN, borrowing from a text sequence classification architecture. Algorithms were tested based on raw time-series data as well as frequency data extracted by the Fourier transform and the spectral entropy of the singal. My contribution to the group was proposing and implementing the Fourier transform as a feature extraction technique, and creating a Hidden Markov Model for classification.

October 2019 - December 2019

A Transfer-Learning Approach for Few-Shot Vid2Vid

Final Project, CS 230: Deep Learning, Stanford University

Built on NVIDIA's Vid2Vid photorealistic video-frame generation architecture, trying a transfer learning approach to few-shot. My contribution was desgining and implementing a novel training scheme that refined pre-trained generator weights by minimizing various divergences (L1, L2, SSIM) between unseen images and the generator output. Results showed high optical stability but low realism: the model was generally able to learn the location of objects, but not the appearance.

October 2019 - December 2019

KRYPTOS: Cryptography In Python

Independent Project

Implemented Caesar cipher and Vigenere cipher encryption and decryption tools. Created a stream cipher analysis tool, and a stream cipher solver for attacking multi-time pads (key resuage) based on maximizing the number of alphanumeric character "hits" given proposed key bits.

Jan. 2019 - Feb. 2019; August 2019

Chess Engine

Independent Project

Implemented a chess engine (minimax agent) and GUI in Java, with AI vs. AI, human vs. AI, and human vs. human modes.

Dec. 2017 - Jan. 2018

Canny Edge Detection

Independent Project/Assignment Extension

Implemented Canny and Sobel edge detection algorithms in C++.

Oct. 2017


Residential Counselor/Teaching Assistant

Stanford Pre-Collegiate Studies

Led 2 labs of ~20 students each in the Artificial Intelligence course at Stanford Pre-Collegiate Studies, reviewing concepts like search algorithms, game-playing algorithms (e.g. minimax), and reinforcement learning. Supervised and advised projects in computer vision, price prediction, sentiment analysis, and more. Wrote problem set and code solutions (Python and Unity C#) for student reference.

June 2019 - August 2019

Project Manager Intern

Dr. Michael McCullough

Intern for Dr. Michael McCullough. Developed business strategy and execution for his non-profit ventures.

Project 1: stealth

Supervised a remote team of 6 interns from Harvard and Stanford, managing deadlines, workflow, conflict resolution, etc. Organized market research about attractive markets for quickly commercializing new healthcare technology. Analyzed disjoint and vague data/business reports in English, Spanish, Japanese, and Chinese.

Project 2: BrainMind

Front-end web development for our website. Developed a custom email-automation marketing script for internal use. Researched top neuroscience companies and influencers in the field.

Project 3: RegenMed Systems

Contributed to market validation for the hematopoietic stem cell/bone marrow market. Researched the hematopoietic stem cell/bone marrow supply chain Identified use cases and market sizes for various applications of hematopoietic stem cells/bone marrow

Project 4: Global Leadership Incubator

Coordinated and standardized the admissions process for scholars seeking higher education in the U.S. via the Global Leadership Incubator's scholarship and sponsorship program Conducted video-call interviews with prospective candidates. Reviewed, evaluated, and redesigned the organization website UI/UX.

May 2018 - November 2018


Programming Languages & Frameworks
  • Machine Learning
  • Deep Learning
  • Natural Language Processing
  • Artificial Intelligence
  • Computer Systems and Organization
  • Design and Analysis of Algorithms
  • Regulating Artificial Intellgence
  • Digital Media and Society


Though I consider an afternoon spent on arXiv with a large cup of coffee to be an excellent leisure activity, when not thinking about AI, I enjoy making music. I am a jazz pianist and songwriter, and am heavily involved in the music side of musical theatre at Stanford.

My past musical theatre credits include Gaieties 2019: Midterm Impossible (Composer, Lyricist, and Music Director), Cabaret (Pianist), The Addams Family (Pianist), Gaieties 2018: Jane Stanford and the Chamber of Secrets (Pianist), The Wiz (Music Director and Pianist), Gaieties 2017: Bearanormal Activity (Pianist), Ragtime (Rehearsal Pianist), and Pippin (Assistant Producer).

Other interests include bullet chess (find me @tchainzzz), watching sports, and getting 8 hours of sleep every night -- it's really good for productivity!