Devin Sze

I am a Computer Science Master's student at the University of California, Davis where I am researching machine learning, static ensemble pruning, and generative tiemseries models. I graduated from the University of California, Berkeley with a double major in Computer Science and Data Science with an emphasis in Business and Industrial Analytics.

I am currently a computer vision engineer at the Johns Hopkins Applied Physics Lab where I prototyped, developed, and finetuned state-of-the-art live large language models for maritime scene understanding. From 2023 to 2024, I was a machine learning intern at Nokia where I developed several generative ML models that learned the underlying sturcture of a dataset, then generated brand-new, statistically-similar data. During summer 2022, I was a software engineer intern for Amazon Web Services (AWS) where I deployed proof-of-concept A/B Testing and Feature Flagging software packages that measured and analyzed the effectiveness of classification systems. I was also a researcher at the Berkeley Artificial Intelligence Research Lab where I work on the CIRCLES initiative to develop a smart cruise controller for self-driving cars to reduce traffic congestion and improve fuel efficiency using deep reinforcement learning.

I have TA-ed for programming, problem solving, and computer architecture courses at Davis, was a TA for Foundations of Data Science at Berkeley, and am a member of Upsilon Pi Epsilon, the international computer science honor society.

Interests

• Computer Vision
• Generative ML
• Ensemble Pruning
• ML for Autonomous Transportation
• Reinforcement Learning
• Simulation

Education

• University of California, Davis

  M.S. Computer Science

  2023 - 2024

• University of California, Berkeley

  B.A. Computer Science

  B.A. Data Science

  2019 - 2023