Nitish Dashora

Nitish Dashora

he/him/his

AI Researcher

Teaching

Undergraduate Student Instructor (CS 188)

Undergraduate course, UC Berkeley, EECS, 2022

I taught CS 188 - Introduction to AI with Stuart Russell for 3 different semesters contributing specifically by giving discussion sections, writing exam questions, debugging projects, grading work, and running office hours. This course introduced the basic ideas and techniques underlying the design of intelligent computer systems. A specific emphasis was on the statistical and decision-theoretic modeling paradigm. Current course offering here.

Course Reader (EECS 16B)

Undergraduate course, UC Berkeley, EECS, 2021

I graded assignments for EECS 16B - Designing Information Devices and Systems II with Anant Sahai for 1 semester. This course walks students through advanced circuitry; this first module of the class introduces students to the frequency domain, a tool critical in circuitry and analyzing many real-world systems. In the next module, students understand stability and controllability of systems, pertinent concepts for robotics. In the final module, students develop fundamental linear algebra building blocks, like SVD, to set them up to implement classification via PCA, a prominent algorithm in machine learning. Current course offering here.

Academic Intern (CS 70)

Undergraduate course, UC Berkeley, EECS, 2021

I worked on staff for CS 70 - Introduction Discrete Math and Probability Theory with Satish Rao for 1 semester contributing as a discussion assistant. This course covers logic, infinity, and induction; applications include undecidability and stable marriage problem. Modular arithmetic and GCDs; applications include primality testing and cryptography. Polynomials; examples include error correcting codes and interpolation. Probability including sample spaces, independence, random variables, law of large numbers; examples include load balancing, existence arguments, Bayesian inference. Current course offering here.