We are a platform to collect accurate patient information before an appointment. Received Funding from Vanderbilt University and the University of Washington via: Winning Vanderbilt Won'dry Grant.Winning University of Washington NSF I-CORPS Grant. Featured: https://www.vanderbilt.edu/thewondry/microgrant-recipients/#attachment_10254Email contact@dashquill.com to learn more.

Undergraduate Researcher under Dr. Dana Zhang, NSF-CRII for Healthcare Identity. Published three research papers all as the first author in IEEE and ACMWon National Science Foundation (NSF) 2nd place student award for my research paper: https://conferences.computer.org/icdh/2023/student_awards.html.Designed a half-permissioned distributed ledger-based network for the exchange and storage of HIPAA-compliant healthcare information between users and organizations. Designed a standard for the interaction between a public Certificate of Authority and a permissioned Membership Service Provider. Helped define protocols and mechanisms for a secure recovery process that uses multi-signature PKI and delegate association. Helped design the layout for a Decentralized Identity Document (DiD) capable of storing and sharing healthcare data.

CS 2201 TA. Taught and graded students on the fundamentals of data structures.

Apart of Oculus Nimble XR Input team working on Hand Tracking Optimization, coded directly on Hand Tracking EngineDeveloped a feature in C++ and Python, collaborated with Data Science team to identify fast handmovement which would lead to a loss in hand tracking.Utilized OpenCV to build a model to identify high luminance regions in the user environmentBuilt a system in C++ to identity negative correlations in our model’s predicted hand tracking, used byData Science team to investigate Intermittent Hand Flickering vs Prolonged Lose Track

Worked on semi-conductor Pricing Model team to efficiently price to market and reduce deadweight loss. Built scrapers to pull in market data and compile data sets. Built a multitude of models to predict Market Pricing using Categorical Regression, Random Forest Regressors, and Support Vector Machines. Reverse engineered distributor's pricing systems/models. Optimized final models by tweaking hyperparameters and ensuring no overfitting.

Designed and constructed a backend search layer to interpret queries and parse customer intent. Optimized search algorithms focusing on string metrics to improve relevant results and efficiency. Built several RESTful APIs & endpoints to structure workload and help with balance.