Resume
A brief history of where I’ve been and what I’ve built so far.
Education
University of Maryland, College Park
B.S. in Computer Science
August 2017 — May 2021
Technical Skills
Languages: JavaScript, TypeScript, SQL, Python, Java 8
Backend: Node.js, Express, REST APIs, OAuth 2.0, PostgreSQL, Redis, NPM, WebSockets, Microservices
Frontend: React, React Native, HTML/CSS, Material UI, D3.js
Cloud & Serverless: AWS (RDS, S3, Lambda, API Gateway, Kinesis, CloudWatch Logs & Alarms), Docker
Tooling & DevOps: Git, Buddy CI, Linux, Retool, Metabase, Figma, Postman, Agile/Scrum
Experience
Smartcar
Software Engineer II
Dec 2021 — May 2025 | Mountain View, CA (Remote)
- Owned development of dozens of full-stack API features connecting 35+ car brands, enabling developers to interact with connected vehicles through a unified, consent-based interface
- Built a sliding window rate-limiting system to prevent traffic bursts and reduce upstream errors, improving API stability and reliability for developers
- Engineered real-time ingestion pipelines for streaming vehicle data, integrating Firehose/Kinesis data into analytics tools for observability
- Developed Backend-for-Frontend service to support a redesigned Developer Dashboard, enabling data-driven UX features and customer usage analytics, boosting dashboard engagement by 30%
- Regularly contributed to cross-functional project planning, writing and scoping tickets, and mentoring junior teammates on debugging, automated testing (Selenium, Jest, Mocha), monitoring, and log instrumentation
- Promoted twice in less than 3 years - setting a company record
USC Information Sciences Institute (ISI), AI Division
Summer Research Intern
May 2018 — Aug 2019 | Los Angeles, CA
- Collaborated with researchers at a global neuroimaging consortium to design a structured knowledge base with semantic search capabilities via SPARQL — enabling neuroscience teams worldwide to query and explore interconnected research data
- Designed data transformation logic for T2WML, a tool for mapping tabular data to Wikidata, enabling ingestion of large CSV datasets (e.g. 2M+ rows) into structured knowledge graphs
Deep Brain Neurotech Lab
Research Intern & Peer Mentor
Aug 2017 — Jan 2019 | College Park, MD
- Built and simulated biologically realistic neuronal networks in NEURON using Python, modelling biochemical neural activity under an FDA M-CERSI grant to support non-invasive treatments for neurodegenerative disorders (e.g., TMS, EMS)
- Partnered with clinical researchers to identify and resolve data inconsistencies in 3D neuroimaging outputs, refining simulation results for accuracy and reliability
- Trained and mentored 40+ students, facilitating peer learning and tool usage