Emaan H
- Research Program Mentor

MS at University of California Berkeley (UC Berkeley)

Expertise

Computer Science, Statistics, Machine Learning, Artificial Intelligence, Data Science, Economics

Bio

My name is Emaan and I am currently a student at the University of California, Berkeley. I currently live in the San Francisco Bay Area, but I was born and raised in Southern California. I received a Bachelor of Arts (B.A.) in Computer Science (with a decent helping of statistics courses) and am currently pursuing a Masters of Science (M.S.) in Electrical Engineering and Computer Science with a concentration in ML/AI and Theory. I currently am exploring metrics for evaluating the quality of neural networks with little-to-no data, as well as looking improving optimization bounds related to the "Netflix problem" and matrix completion. I am greatly fascinated by many fields in computer science, including theory, hardware, artificial intelligence/machine learning, and computer security. Additionally, I have an interest in economics, politics, finance, and history.

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Baseball Swing Detection

Often, athletes find that human observation and input is necessary to assess the quality of their "game". Baseball players, golfers, or tennis players without personal trainers and thousands of dollars of equipment might be stuck trying to guess what went wrong with that last swing and how they can improve. Motivated by this, we can consider building a system that uses computer vision to help athletes improve their "game".

Coding skills

Python, Java, C, R, Go, SQL

Languages I know

Farsi (Native), Spanish (Novice), Chinese (Novice)

Teaching experience

I love teaching, and have been on course staff 12 times, 10 times as a TA, for the following courses during my time at Berkeley: - Probability Theory (STAT 134): Group Tutor, Spring 2018 - Computer Architecture (Machine Structures; CS 61C): TA, Summer 2018 - Discrete Mathematics and Probability Theory (CS 70): TA, Summer 2018, Fall 2018, Spring 2019 - Teaching Techniques for Computer Science (CS 375): TA, Summer 2020 - Machine Learning (EECS 189): Reader, Summer 2019 - Efficient Algorithms and Intractable Problems (CS 170): Head TA, Fall 2020; Project TA, Fall 2019, Spring 2020, Spring 2021 - Combinatorial Algorithms and Data Structures (Graduate Algorithms; CS 270): TA, Spring 2021

Credentials

Work experience

UC Berkeley (2018 - Current)

Graduate Student Instructor

UC Berkeley (2020 - Current)

Graduate Student Researcher

Salesforce (2019 - 2019)

Software Engineering Intern

Education

University of California Berkeley (UC Berkeley)

BA Bachelor of Arts (2020)

Computer Science