• Developed neural network in TensorFlow to model the optimum traffic density for the free flow of vehicles between two consecutive ramp meters on the freeway, which will help reduce congestion and vehicular accidents by 50%

• Designed a graph-based network, utilizing Neo4j, Python, and Wi-Fi signal triangulation, for contact tracing of Covid-19 on the UCSD campus to decrease the spread of the virus amongst 40,000 students

• Devised a graduation requirements application, using React, Node.js, and Neo4j, to help students identify bottleneck courses and different paths to graduation based on graph-search algorithms

• Developed relations with advisors and mentors to facilitate the growth of the organization and acted as Project Manager in charge of instituting partnerships with the Big 5 consulting firms through networking events