| CARVIEW |
Select Language
HTTP/2 301
server: GitHub.com
content-type: text/html
location: https://druvpai.github.io/teaching/
access-control-allow-origin: *
expires: Mon, 29 Dec 2025 12:01:28 GMT
cache-control: max-age=600
x-proxy-cache: MISS
x-github-request-id: 8C1F:328FD3:8C7BB6:9DA9C7:69526B3F
accept-ranges: bytes
age: 0
date: Mon, 29 Dec 2025 11:51:29 GMT
via: 1.1 varnish
x-served-by: cache-bom-vanm7210055-BOM
x-cache: MISS
x-cache-hits: 0
x-timer: S1767009089.808535,VS0,VE214
vary: Accept-Encoding
x-fastly-request-id: 33b275b24fed27c2b2555bacb0b9b5b292cb487d
content-length: 162
HTTP/2 200
server: GitHub.com
content-type: text/html; charset=utf-8
last-modified: Mon, 29 Dec 2025 08:40:39 GMT
access-control-allow-origin: *
etag: W/"69523e87-2b9b"
expires: Mon, 29 Dec 2025 12:01:29 GMT
cache-control: max-age=600
content-encoding: gzip
x-proxy-cache: MISS
x-github-request-id: A700:444BC:8CD543:9E0504:69526B40
accept-ranges: bytes
age: 0
date: Mon, 29 Dec 2025 11:51:29 GMT
via: 1.1 varnish
x-served-by: cache-bom-vanm7210055-BOM
x-cache: MISS
x-cache-hits: 0
x-timer: S1767009089.052192,VS0,VE203
vary: Accept-Encoding
x-fastly-request-id: a03ac8cec8cc243a721bd47d9a0f21dd3f70167d
content-length: 3689
Teaching - Druv Pai

Druv Pai
Ph.D. student @ UC Berkeley developing theory for large-scale empirical deep learning.
- Bay Area, CA, USA
- Github
- Google Scholar
Teaching
I have been fortunate to be on course staff for four separate courses, all offered by the EECS department at UC Berkeley. These were:
- EE 226A (Random Processes in Systems).
- The course is a graduate course in probability and stochastic processes, teaching the fundamentals of measure-theoretic probability, stochastic state-space models, Markov processes, martingales, and other stochastic processes.
- I was the sole TA in Fall 2024.
- EE 127 (Optimization Models In Engineering).
- The course is a first course in optimization theory and practice, teaching the fundamentals of convexity, unconstrained optimization, constrained optimization, duality, linear and quadratic programming, and various applications.
- I was a Discussion TA in Fall 2020 and the Head Content TA in Fall 2022, Spring 2023, and Spring 2024.
- EE 16B (Designing Information Systems and Devices II).
- The course is a second course in linear algebra for engineers and a survey course for many sub-fields of electrical engineering, such as circuits, device physics, control theory, signal processing, and data analysis.
- I was a Content TA in Spring 2021 and Fall 2021 and a Head Content TA in Spring 2022.
- CS 170 (Efficient Algorithms and Intractable Problems).
- The course is a first course in algorithm theory, teaching fundamental algorithmic ideas such as divide-and-conquer, graphs, trees, and dynamic programming, as well as more advanced ideas such as network flows and approximations to NP-hard problems.
- I was a Reader in Spring 2020.
In the course of the above appointments, I earned the following awards:
- In 2022, I was given the UC Berkeley Outstanding Graduate Student Instructor Award (~60 recipients/year).
- In 2023, I was given the UC Berkeley EECS Department Outstanding TA Award (~5 recipients/year).
As a Reader, my responsibilities included:
- Grading homework and exams.
As a Discussion TA, my responsibilities included all of the above, plus:
- Teaching either one or two discussion sections each week.
- Teaching review sessions at least twice a semester in preparation for exams.
- Running two or more open office hours a week.
As a Content TA, my responsibilities included all of the above, plus:
- Composing homeworks and discussion worksheets each week, as well as the solutions.
- Composing a midterm and final exam.
As a Head Content TA, my responsibilities included all of the above, plus:
- Leading large-scale initiatives, such as design of a course project, or thorough and detailed lecture notes. (Example course notes for EE 127.)
- Managing a team of Graduate Student Content TAs.
- Handling administrative work (e.g., website administration) and logistics when and where required.