

Nicholas Tomlin
PhD Candidate
Berkeley EECS
nicholas_tomlin@berkeley.edu
Advising
I enjoy teaching and mentoring students and have worked with a number of undergrad and masters students during my time at Berkeley. I have worked most closely with the following students:
- Georgia Zhou (Ongoing, BS 2026)
- Angela He (Ongoing, BS 2025)
- Maggie Huan (Ongoing, MS 2025)
- Nishant Bhakar (Ongoing, BS 2025)
- Austen Liao (BS 2024 → ServiceNow)
- Vivek Verma (BS 2024, MS 2025 → OpenAI)
- Andre He (BS 2024 → CMU PhD)
- Lily Zhang (MS 2021 → Waymo)
Because I am graduating soon, I'm unfortunately unable to take on new advisees at this time.
I also co-wrote a blog post on applying to NLP PhD programs and am happy to give advice to prospective applicants. Finally, I am a big fan of Chris Olah's research taste exercises and am happy to provide feedback on potential projects and research directions for early career researchers.
Teaching
During Summer 2023, I was the instructor for Berkeley CS188: Introduction to Artificial Intelligence, which is a mid-level undergrad class covering search, probability, inference, and machine learning basics. I was also a teaching assistant for Berkeley CS288: Natural Language Processing during Spring 2022. I have also been a four-time summer instructor for the AI4ALL program at Berkeley.
At Brown University, I was a teaching assistant for CSCI 1570: Design and Analysis of Algorithms, MATH 1530: Abstract Algebra, and CLPS 0030: Introduction to Linguistic Theory. I typed thorough notes for abstract algebra, which are available here. I was also a grader and tutor for assorted introductory math classes.