• Built Java (Spring) MVC backend to make optimized work schedules for healthcare providers• Designed PostgreSQL schema to accommodate long-term support and scheduling rule changes• Developed TypeScript (React) frontend with best-practice UI/UX principles for seamless user navigation• Implemented with Spring Data JPA and Hibernate to balance scalability with rapid development

• Implemented mixed-integer program in C++ to build optimized schedules for healthcare providers• Led onboarding project to streamline the codebase and introduce new interns to IBM's CPLEX library• Automated the optimization of a hierarchy of metrics, reducing the time to build a schedule by 70%• Facilitated communication using Jira and Agile methodology between developer teams• Contributed over 10000 lines of reviewed code to an established C++ codebase using Git• Designed entity-relationship diagrams, code diagrams, and pseudocode for documentation

• Revamped Excel data processing using Python (Pandas and NumPy), increasing efficiency by over 90%• Developed a user interface using Tkinter to increase accessibility to the data processing tool• Improved existing C++ tool by maximizing the equity in night shifts for trauma unit attending schedules• Shadowed doctors and medical assistants to better understand our collaborators' perspective• Handled sensitive health information following HIPPA guidelines

• Implemented color animation web app with Typescript (React) to improve human color perception• Enhanced responsiveness by leveraging Remix server-side rendering, reducing loading time by 30%• Maintained SQL Server database with Prisma to manage configurations for color-blind individuals

• Automated Zoom attendance logging to Google Sheets using C++ driven program• Organized annual research conference and hosted Genes & Health Contest• Guided members through a year-long bioinformatics research program to publish an abstract• Kept the official WordPress-driven website up to date

• Lectured on microarray gene expression, GEO2R, STRING-db, KEGG, and Gene Ontology• Used R and the Random Forest machine learning model to predict miRNA gene targets• Guided students in navigating Linux in the remote Great Lakes Computing Cluster to process next-generation sequencing data and visualize mutations in IGV• Streamlined biotechnology sequencing camp curriculum to include more shell script

• Discussed ways to adapt computational biology methods like Hi-C, focusing on the development of coding frameworks for visualizing and interpreting 3D genome mapping data• Presented analysis on restriction enzymes and their role in the ChiP-Seq research pipeline• Reviewed hypergraph algorithms (line, clique, and bipartite expansions) to evaluate their efficiency at representing genomic loci interactions• Performed regular maintenance of S2 cell cultures in preparation for experiments