Nicholas Tomlin
PhD Student
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:
- Austen Liao (Class of 2025)
- Vivek Verma (Class of 2025)
- Andre He (BS 2024 → CMU PhD)
- Xinyun Zhang (MS 2021 → Waymo)
If you are interested in working with me, please email me or apply through the Berkeley NLP Group and mention my name in your application. You don't need to have previous research experience, but I will prefer students with a strong background in at least one of mathematics, computer science, or linguistics.
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 three-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.