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Jeffrey C

- Research Program Mentor

PhD candidate at Princeton University

Expertise

Machine Learning

Bio

I'm a PhD student in machine learning and a strong believer in the value of breadth > depth. AI pulls from an enormous number of fields: probability, linear algebra, algorithms, computational neuroscience, statistical physics, information theory, etc. etc. etc. I like to build ML systems with a bit of whimsy and flair, and my favorite part of the experience is forming spicy (and often novel) connections between ideas in wildly different disciplines. Please reach out if you're interested in AI and like to let your personality shine through in your work! My technical background includes a BS/MS in Computer Science from UPenn and a business degree from Wharton. I've worked in software at EA Games, Palantir, and IBM, and I used to be an adjunct lecturer for deep learning at UPenn. I currently moonlight as a quant at Vise (employee #4), which recently became a unicorn startup.

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Robot Ed Sheeran: Making an AI Composer

Current state-of-the-art ML for music (see: OpenAI, Google Magenta) is bad at learning long-form structure. I believe this is because their approach of swallowing and vomiting MIDI files does not reflect the vast amount of prior information we have as humans: we have ears that pick up on the subtle ways that pitches interact, and we're hard-wired to understand linguistic structures. Let's build a better AI with these inductive biases and generate some funk!

Coding skills

Python (scientific stack, PyTorch)

Teaching experience

I taught CIS 160: Mathematical Foundations of CS (set theory, probability, graph theory) at UPenn for 3 years. I created and taught CIS 700: Deep Learning at UPenn in 2019, which is Penn's only deep learning course; it is now a core requirement for 3 separate degree tracks and is the highest-rated ML offering at Penn. I also mentored students in COS 485: Deep Learning at Princeton in 2020.

Credentials

Work experience

Vise (2020 - Current)
ML Engineer
Palantir (2019 - 2020)
ML Engineer

Education

University of Pennsylvania (UPenn)
BA Bachelor of Arts (2019)
Computer Science
University of Pennsylvania (UPenn)
MS Master of Science (2019)
Data Science
University of Pennsylvania (UPenn)
BS Bachelor of Science (2019)
Business
Princeton University
PhD Doctor of Philosophy candidate
Computer Science

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