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Ryan M

- Research Program Mentor

MS at University of California Berkeley (UC Berkeley)

Expertise

Computer Science, Machine Learning

Bio

Hi! I'm a former Berkeley grad student who now works at a national lab doing machine learning research. While at Berkeley my research focused on theoretical neuroscience, and in general I'm very intrigued by the intersection of computer science and neuroscience. I also spent over a thousand hours at Berkeley teaching the first Computer Science class offered in the major in many different capacities, from volunteer tutoring to eventually lecturing for the class! In my free time I like to do many of the stereotypical grad student hobbies: run, hike, boulder, and in general anything that involves being active or exploring the outdoors. I'm also an avid Boston sports fan and very into sports analytics, so I would love to talk with you about any project ideas focused on that. Outside of that, I try to spend a lot of time learning new things in machine learning and neuroscience. Occasionally I get side tracked playing Magic the Gathering...

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.

Designing your own autocorrect algorithm: an introduction to algorithms and machine learning

In this project, we will focus on two big ideas: one in computer science and one in machine learning. The first idea is called dynamic programming and is one of the traditional ways in computer science to implement an autocorrect algorithm. We can design it from scratch (this is a project I made at Berkeley that has been given to 10,000 students and counting) or just focus on the algorithm, depending on how much you're looking to learn. Then we will switch gears and use machine learning in order to implement a more accurate version of autocorrect that is able to be personalized to each user. By the end of this project, you should be comfortable with a class of algorithms that are taught to junior and seniors in computer science classes at Berkeley, as well as the fundamentals of machine learning!

Coding skills

Python

Teaching experience

I taught computer science for most of my time at the University of California, Berkeley. I started out as a volunteer tutor, and after a few semesters of that I joined the course staff for the first computer science class offered in the major, CS 61a, as a TA. Eventually I was promoted to Head TA, during which I designed a project for the class that has been assigned to 10,000 students (and counting!). Finally after graduating as an undergrad I had the opportunity to lecture for the class.

Credentials

Work experience

Lawrence Livermore National Lab (2021 - Current)
Machine Learning Researcher

Education

University of California Berkeley (UC Berkeley)
BA Bachelor of Arts (2020)
Computer Science, Statistics
University of California Berkeley (UC Berkeley)
MS Master of Science
Electrical Engineering and Computer Science

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