Abishek Anand

M.S. Machine Learning, B.S. CS+ECE @ Carnegie Mellon University

We cannot change the cards we are dealt, just how we play the hand.

Randy Pausch, The Last Lecture

About

I'm an AI researcher and graduate student at the Machine Learning Department of Carnegie Mellon University, pursuing a Master of Science in Machine Learning . Previously, I was an undergraduate student at CMU, double majoring in Computer Science and Electrical and Computer Engineering . Broadly, I'm interested in building technology that makes the world a better place. Recently, I've been interested in challenges in Robotics and AI Safety, and am doing work in this area.

Previously, I've been fortunate to work on a variety of research and engineering projects at NVIDIA, Optiver, and the CMU Machine Learning Department. I have also been a teaching assistant for some of the most popular courses at CMU, including Generative AI, Deep Reinforcement Learning, and Intro. to Computer Systems.

Personally, I enjoy playing tennis and still watch it regularly. In a past life, I played tennis competitively and achieved a 9.6 UTR and qualified for the Texas state championships. You can view my college recruiting video here. I'm also interested in Indian culture, particularly 80s-90s Thamizh film and music.

Timeline

Jan- 2026

Teaching Assistant (10-703/10-403 Deep Reinforcement Learning)

Worked with Professors Katerina Fragkiadaki and Aviral Kumar on teaching the latest topics in RL. This was the course that first got me interested in robotics and one of my favorites at CMU. I also contributed to putting together a brand new textbook for Modern Reinforcement Learning. More on this soon!

Aug-Dec 2025

Teaching Assistant (10-723/10-623/10-423 Generative AI)

Worked with Professors Matt Gormley and Aran Nayebi in my second iteration of teaching this course.

June-Aug 2025

Optiver — Software Engineering Intern (Quantitative Trading Systems)

This was my first exposure to the exciting world of high-frequency trading. I worked on automating a key part of the trading system. This involved interfacing with developers, traders, and researchers. As part of the company intern hackathon, I built an AI tool that sources news headlines from Bloomberg terminal and sends slack updates to relevant traders in real-time with predictions on instrument price movements.

Jan-May 2025

Teaching Assistant (10-723/10-623/10-423 Generative AI)

Worked with Professors Matt Gormley and Pat Virtue on teaching the latest topics in Generative AI. This was my favorite course at CMU and got me really excited about AI. This course takes you from nothing to being able to understand the latest research papers in just a semester (across language, vision, and multi-modal generative models). Highly recommend this course.

Aug-Dec 2024

Teaching Assistant (18-613/18-213 Intro. to Computer Systems)

Worked with Professors Greg Kesden and Vyas Sekar in my second iteration of teaching this course.

June-Aug 2024

NVIDIA — Software Engineering Intern (Cloud Engineering & Services)

First ever real-world engineering experience. I learned a lot about software engineering, distributed systems, and also what I value in a work place. Probably the only work experience I'll have in my life where AI couldn't do anything useful from a coding perspective.

Jan-May 2024

Teaching Assistant (18-613/18-213 Intro. to Computer Systems)

Worked with Professors Greg Kesden and Swarun Kumar on teaching the core systems course at CMU. This was also one of my favorite courses at CMU. The course's only prerequisite is basic knowledge of DSA and will give you a rigorous understanding of all the major topics in computer systems. By the end of it, you'll be fluent in C, assembly, GDB, caches, memory allocation, networking, and a lot more. The projects were really intense and useful. Some of the projects were implementing malloc, a caching web server, and a basic linux shell. I'm glad I took this course pre-chatGPT, so I could truly appreciate the depth of these projects. I've heard students can one-shot the class with LLMs now.

June-Aug 2023

CMU Robotics Institute — Robotics Research Assistant

I did some self study of the 16-350: Planning Techniques for Robotics course at CMU. I also helped a PhD student with their research on a modification to the A-star planning algorithm for more efficient pathfinding. Looking back, I wish I dedicated more time to this project given my current interest in robotics. I was taking 18-213 at the same time, which took up considerable effort.

Jan-May 2023

Teaching Assistant (18-100: Intro. to ECE)

The course is more of an intro to EE than ECE. There is basically zero content that covers programming in any meaningful capacity. The course consists entirely of a variety of breadboard projects. It was through this course that I knew for certain that I was not interested in circuit design. In software, if something is wrong, I definitely did something wrong. However, with hardware, if something goes wrong, it could easily be the case that I did everything correctly but one of the devices I was using was faulty. I really disliked that aspect of circuit design, and chose to specialize more on the software side as a result. However, teaching the course was still a valuable experience, especially this early in my career.

Teaching

Over the years, I've had the chance to take on various teaching roles, and I find that I actually enjoy it quite a bit. Currently, I teach foundational courses in AI and Systems to both undergraduate and graduate students.

In highschool, I was an English tutor for a couple of foreign exchange Japanese students and was also an SAT ambassador for my school district. I would prepare lessons that would help dozens of students prepare for the SAT every week leading up to the exam.

Coursework

Artificial Intelligence: Deep Reinforcement Learning, Generative AI, Deep Learning, Machine Learning, AI Society and Humanity (philosophy dept.)

Computer Systems: Compiler Design, Distributed Systems, Computer Systems, Structure and Design of Digital Systems

CS Theory: Great Ideas in Theoretical Computer Science, Design and Analysis of Algorithms, Parallel and Sequential Data Structures and Algorithms, Functional Programming, Automated Program Verification

Mathematics: Calculus 1-3, Linear Algebra, Probability Theory, Statistical Inference, Concepts of Mathematics (Discrete Math)

Electrical Engineering: Electronic Devices and Analog Circuits, Signals and Systems, Intro. to ECE

Contact

Best way to reach me: abisheka@cs.cmu.edu.