Computer Science / Data Science Research
Deep Reinforcement Learning: With Dr. Zacharski I focused more on a particular instance of Reinforcement Learning where deep neural networks are used. During this time, I built out a Reinforcement Learning library written in PyTorch. This library helps me have a test bed for trying out different algorithms and attempts to create my own.
Reinforcement Learning: Currently studying the fundamentals of reinforcement learning with Dr. Davies. We went over the fundamentals such as value functions, policy functions, how we can describe our environment as a markov decision processes, etc.
Programming Languages: Studying the design of programming languages. So far I made an implementation of the SLOTH programming language, experimenting with what I want my own programming language to be syntatically and paradigm wise.
Before this study, I worked though a book called “Build your own Lisp” and my implementation of a lisp like language is below.
Competitive Programming: Studying algorithms and data structures necessary for competitive programming. Attending ACM ICPC in November with a team of two other students.
Worked on an independent study on the topic of Cluster Analysis. This is where you try to group similar observations without knowing what the labels are. I am studying under the guidance of Dr. Melody Denhere, the link below gives you more of a description of the project along with my course notes.
For the two projects below, I worked on Quantum Research in a physics lab with a fellow student Hannah Killian and an advisor Dr. Hai Nguyen. I mostly assisted with the software support for the project and assisted in the mathematics in whatever way I can.
In order to circumvent the frustrations I had with simulation code taking a while, I applied and received funding to build out a Beowulf cluster for the Physics department. Dr. Maia Magrakvilidze was the advisor for this project.