CV

Education

• Ph.D in EECS @ UC Berkeley, Fall 2023 - ?
• M.S. in EECS @ UC Berkeley, Fall 2022 - Spring 2023, GPA 4.0/4.0
• B.A. in CS @ UC Berkeley, Fall 2018 - Spring 2022, GPA 4.0/4.0

Industry Experience

• Summer 2024: Machine Learning Researcher Intern @ NexusFlow
• Summer 2020, Summer 2021: Software Engineering Intern @ Amazon
• Summer 2019: Machine Learning Engineer Intern @ SymphonyAI

Programming Languages, Frameworks, and Tools

• Python, Java, C++, C, x86, Julia
• Jax and assorted libraries [1] [2] [3] [4], PyTorch
• Git, Linux, *sh

Publications

Discussed in more detail in my publications page.

Invited Talks, Presentations, and Posters

• Presented on “White-Box Transformers, Structured Denoising-Diffusion, and Closed-Loop Transcription” @ ICASSP 2024 Tutorials, April 14, 2024.
• Presented on “White-Box Transformers and Closed-Loop Transcription” @ Laplace Reading Group, Google DeepMind, April 11, 2024.
• Presented on “White-Box Transformers” @ MoDL Annual Meeting, September 28-29, 2023.
• Presented on “White-Box Transformers” @ ANSR Weekly Meeting, September 1, 2023.
• Presented on “White-Box Transformers” @ Tsao Lab Reading Group, September 13, 2023.

NB: This section only has talks, presentations, and posters not disclosed in my publications page.

Teaching

Discussed in more detail in my teaching page.

Service, Leadership, Outreach

• Participated in the BAIR Undergraduate Mentorship Program, Fall 2023.
• Served on organizing committee for THEORINET Retreat 2023.
• Reviewer for the following publication venues:
  • Conferences and Workshops
    • AISTATS 2025
    • ICLR 2025
    • NeurIPS 2024
    • NeurIPS 2024 Workshops: M3L, SciForDL
    • ICML 2024
  • Journals
    • IEEE JSTSP

Awards

• UC Berkeley College of Engineering Fellowship, 2023, 2024.

NB: This section only has awards not disclosed in my publications page or teaching page.