Currently a Quantitative Analyst at Pattern Research. Pattern Research is a quantitative asset management firm that specializes in trading cryptocurrencies across all asset classes. My previous work experience includes interning at Akuna Capital and Bluefin Trading. More details in my resume below, feel free to check it out!
I graduated with a Masters in Data Science at the University of Pennsylvania in December 2019. The master's courseload included courses covering all fields of machine learning and statistics. Received my bachelor's of Engineering degree in Digital Media Design six months earlier in May of 2019. Digital Media Design is a unique Computer Science degree which emphasizes Computer Graphics related study.
I enjoy programming in a wide variety of languages such as Python, C/C++, R, and even Swift. I also have experience with relational databases and have worked with MySQL, Postgresql, and SQLite. I have also worked with many data science packages and frameworks such as PyTorch, Tensorflow, Pandas and more.
My courseload has given me deeper insights into hypothesis testing and the mathematics behind it, maximum likelihood estimation, and regression as it applies to the world. These days you can find me reading Algorithmic Trading: Winning Strategies and Their Rationale as I seek to learn more about Time Series Analysis and its applications in finance.
Mastering in Data Science has allowed me to delve deep into the theory and applications of machine learning and beyond. My undergraduate senior design project involved reimplementing Chen et al.'s 2018 CVPR paper on using a Convolutional Neural Network to brighten dark images with almost no noise, but using iPhones.
Developing apps has been a hobby of mine for more than three years. I have been able to grow this hobby using my graphics knowledge to implement the first physically based pathtracer run on an iPhone. Code and Sample Renders are available on Github.