Biography
I’m an undergraduate student at the University of Michigan, majoring in Computer Science. I’m passionate about deep learning models, web technologies and entrepreneurship.
I’m interested in both the academia and the entrepreneurial world. I co-founded Collage, an EdTech startup to assist students with course scheduling. I previously served as a research assistant at the U-M Minji Lab and Direct Brain Interface Lab.
Feel free to contact me at zhangzzc@umich.edu. I’m always open to a coffee chat.
Interests
- Multimodal Learning
- Adversarial Attacks
- Explainable AI
Education
B.S. in Computer Science, 2026
University of Michigan-Ann Arbor
Experience
Co-Founder & CTO
Applying LLMs, prompt engineering and recommendation algorithms to transform college experience
Research Intern
Developed MIA-Sort, an efficient sorting algorithm that reads a dataset of 4 billion chromosome genome-scale metabolic models (GEMs) fragments and ranks them in different schemes
Core Member
Helped to build MWalk, an Android mobile app written in Java that tracks U-M students’ walking workouts, speed and distance, using Health Platform API and Firebase
Research Intern
Deployed the branch logics of the brain-computer interface survey instrument in Qualtrics hosted on JavaScript Form Engine and implemented the automated user interaction functionalities in JavaScript and JavaScript APIs
Projects
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GenHint won the MHacks 2024 Honorable Mention of Best Developer Tool Track. Unlike conventional AI coding assistants like GitHub Copilot, GenHint does not give you codes directly. Instead, it generates code templates with “TODO” comments and explains each subproblem for you. Download GenHint at VS Code Extensions.
An AI-driven education technology platform that uses LlamaIndex, Scikit-Learn, Pandas, React Mantine, Flask, Natural Language Toolkit, LangChain, Heroku CI/CD Pipeline, and OpenAI API (GPT4-o & DALL-E Models) to personalize class schedules and career exploration, enhancing user engagement and academic planning
A scalable Python library that sorts gigantic genomic datasets like ChIA-Drop efficiently in different schemes
