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EZ

Background

Experience

Professional software engineering experience supported by graduate study and substantial end-to-end engineering projects.

Professional Experience

Building systems under real delivery constraints.

Datalynn

Professional Experience

EXACT DATES TO ADD

Software Engineer Intern

  • Built a high-concurrency data collection pipeline with Python, AsyncIO, aiohttp, and Playwright, reducing end-to-end latency by approximately 60% and processing more than 180,000 rows per day.
  • Designed a reusable crawler plugin from requirements through deployment for on-demand data updates and upstream query workflows.
  • Distributed processing across five workers, improving throughput from approximately 0.5 GB/hour to 2 GB/hour.
  • Processed results with Pandas, stored structured data in MySQL, and exposed CRUD workflows through FastAPI APIs.

The exact internship dates are intentionally marked as a placeholder until confirmed from the resume.

Graduate Education

Johns Hopkins University

Master of Science in Electrical and Computer Engineering

Graduate work connects electrical and computer engineering foundations with backend software, intelligent systems, and applied research.

Selected Engineering Experience

Evidence beyond a job title.

Projects that demonstrate system design, implementation, evaluation, and iteration across multiple engineering domains.

Backend Systems · AI Applications

Medical RAG Agent

An end-to-end medical question-answering and patient-record system combining hybrid retrieval, agent routing, short-term memory, long-term memory, and structured medical data storage.

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Distributed Data Systems · Web Automation

Asynchronous Web Crawler and Data Platform

A high-throughput asynchronous web crawling and data-serving system using browser automation, concurrent workers, persistent storage, and REST APIs.

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Applied Research · Computer Vision

Deep Learning for 3D Object Detection

A research project exploring attention-based temporal feature fusion for 3D object detection in autonomous-driving scenes.

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Embedded Systems · Control

Autonomous Arduino Vehicle

An embedded autonomous vehicle using differential drive, sensor-based navigation, and state-machine control.

Read project details