The future has landed
And there are no hoverboards or flying cars.
Just coders. Lots and lots of coders.
For starters, I'm a Computer Science and Math double major at the College of William & Mary, Class of 2027.
I absolutely love anything related to low-level systems and math. These two subjects often live as distant cousins, but they prove to be totally paramount to each other. I seek to understand them and their intersection, and how they can be applied to improve the world.
Also, I'm pursuing rigorous projects to hone my skills to the max. I believe the only way to know you have learned something is to do it, and intelligent determination (with a certain nonzero amount of stubbornness) is the only way to get you there. Feel free to check out my work experience and projects below.
@ The Johns Hopkins Applied Physics Laboratory
Will contribute to the development of C++ and Python software systems supporting air and missile defense research at the Johns Hopkins University Applied Physics Laboratory. Work will involve collaborating with multidisciplinary teams of software engineers, applied mathematicians, and domain scientists to design, implement, and test performance-critical systems.
@ DisinfoLab William & Mary
Worked with a team of trained software engineers to fight disinformation in the global political landscape. Co-authored a research report analyzing public sentiment trends, published in The Diplomatic Courier. Helped with initial development of Fact Forecast, a fact-checked news platform.
Have a look, I'm sure something will pique your interest.
I developed a Waze-inspired routing engine in C++ using Dijkstra's algorithm, the A* algorithm, and a custom multithreaded A* algorithm I created. I containerized this project with docker, and deployed it using Flask API.
I implemented in C++ multiple forms of the matroid (an algebraic structure from combinatorial optimization) and showed empirically that matroids can solve many seemingly unrelated problems.
Researching various topics in high performance computing such as SIMD parallel instructions, optimization on CPU and GPU architectures, parallel and distributed computing, multi-threaded algorithms, memory and cache cache-efficient code optimizations in C/C++.
In Python I developed tools to gather (using the Youtube API) and clean Youtube comment data. Then I constructed a sentiment analysis tool that uses bert-base-cased huggingface transformer model. Analysis was published in The Diplomatic Courier.
Contributing to the in-progres development of Fact Forecast. Created multiple RSS feed gatherers to help data collection. Setting up EK (Elasticsearch-Kibana) stack utilities to aid the backend development.
Studying and implementing various concurrent patterns and techniques in C++. Focused on creating performance-optimized concurrent data structures.
- Edsger Dijkstra