Nathan Mandi's Classroom

Director of Studies


I'm a fresh graduate who really enjoys teaching. In my time at Berkeley, I was a TA for three different CS courses, a total of six times. I hope that being a Director of Studies will help me keep my passion for teaching alive.

The courses I've taught are:

  • CS 170 - Efficient Algorithms and Intractable Problems

  • CS 188 - Artificial Intelligence

  • CS 70 - Discrete Math and Probability Theory

My first recommendation for how to get started would be to look at the course materials for these classes. Typically the content is publicly available online for the current semester, and they cover a broad range of topics in quite a bit of detail.

I focus on these subjects, but I also have a general understanding of other topics in computer science and software development, in case you're interesting in something a bit more broad.

About Me

I grew up mostly in south Florida, but when I came to the Bay Area for college, I immediately knew I would stay on the west coast for a while. In my spare time I enjoy hiking and rock climbing, as well as logic puzzles and video games. I'm also a part of an chorale group at Berkeley - we sing anything from classical music to pop songs.

I now work full-time at Cruise Automation, a recently acquired start-up that is now GM's self-driving car subsidiary. I'm on the Tracking/Prediction team, and my job is to use ML to help the cars predict what other agents around them will do next. It's really exciting!


"Nathan has served as my Teaching Assistant for classes including Discrete Mathematics and Probability Theory (CS70), Efficient Algorithms and Intractable Problems (CS170), and Introduction to Artificial Intelligence (CS188) at UC Berkeley. Having Nathan as my TA was a rewarding experience and his teaching style made attending discussion sections worthwhile. Nathan excels at gauging the level of understanding of a group of students and then building from that level. I always felt he understood what the class was thinking and was preemptively prepared to expand upon any sources of confusion. Thus, it always felt like we were able to have a good dialogue, despite our level of preparedness or understanding of the material. In addition, he is also very talented at explaining concepts to individual students, where his ability to empathize also shines. As a current TA for the same classes, I admire and attempt to imitate his teaching approaches in my weekly sections and office hours."



Berkeley, California


Primary Subjects:

  • Algorithms

  • Artificial Intelligence / Machine Learning

  • Probability / Discrete Math


  • Graduated EECS from UC Berkeley in Fall 2017

  • Berkeley Outstanding GSI award 2016-2017