REU participant at Worcester Polytechnic Institute, Data Science department. Created algorithm for a novel kind of LSTM (a type of Recurrent Neural Network) to allow for early but accurate prediction of time series data. Tested and demonstrated efficacy of algorithm for improving patient outcomes in the ICU. Published the results of the work. First author on paper that won award for 2nd Best Paper at the 2019 MIT URTC.

Using PHP and HTML/CSS, developed membership website that gives up-to-date chess openings information in video and PGN format to chess players. Worked in transcontinental team to create framework and test. Collaborated with founder to create marketing strategy.

REU participant at University of North Texas, in the Computer Science department. Using Keras and Tensorflow, developed and tested neural networks used for testing the effectiveness of polynomial approximations of activation functions. Contributed to implementation of homomorphic encryption library FV-NFLlib.