PORTFOLIO / 2026

SOFTWARE + AI ENGINEER

I build intelligent systems that work beyond the demo.

Computer Science at UC San Diego. Building across edge AI, agentic systems, full-stack products, and applied machine learning.

3.98UCSD GPA

90.2%EDGE ML ACCURACY

15.5sAGENTIC WORKFLOW

02ENGINEERING AWARDS

01 / SELECTED WORK

Systems with
measurable outcomes.

01

EDGE AI / IOT / FULL STACK

Thermal Presence Detector

A privacy-first occupancy system that replaces camera monitoring with an 8×8 thermal sensor and on-device inference.

I trained and quantized a TensorFlow Lite Micro model, deployed it to an ESP32, and built the MQTT, FastAPI, MySQL, OAuth, and WebSocket pipeline behind a live monitoring dashboard.

  • 90.2% accuracy
  • 6.5 KB model
  • 10,000 samples
  • C++
  • Python
  • TensorFlow Lite
  • FastAPI
  • Docker
02

MULTI-AGENT SYSTEMS / HACKATHON WINNER

TravelAGNTCY

A coordinated AI travel planner that turns one request into a ranked, complete itinerary—without the usual tab-sprawl.

A supervisor coordinates specialized flight, hotel, activity, and review agents across a LangGraph workflow, with live search and deterministic price-and-rating filters before final synthesis.

  • 15.5s average
  • 20/20 benchmarks
  • Track winner
  • Python
  • LangGraph
  • OpenAI API
  • React
  • Docker
03

APPLIED ML / DATA PIPELINES

Grocery Product Matching

A precision-biased product reconciliation pipeline for finding credible Walmart-to-Wegmans counterparts at catalog scale.

The two-pass matcher combines brand and size normalization, TF-IDF retrieval, deterministic variant gates, and an LLM judge—then documents the precision/recall tradeoffs behind every threshold.

  • 4,817 matches
  • 88 unit tests
  • 2-pass pipeline
  • Python
  • scikit-learn
  • Pandas
  • OpenAI API
04

HEALTHCARE AI / FULL STACK

Clinical Data Reconciliation

An AI-assisted engine for resolving conflicting medication records and surfacing patient-data quality issues across EHR sources.

The application turns structured clinical records into explainable reconciliation decisions, with schema-constrained model output, source reliability rules, rate-limit handling, and end-to-end MIMIC tests.

  • 22 tests
  • JSON-constrained
  • MIMIC-III data
  • FastAPI
  • React
  • Pydantic
  • OpenAI API
  • Docker

02 / EXPERIENCE

Engineering from first principles to production.

2026 — PRESENTPortabase · Open-source contributor

Shipped Azure Blob Storage as a complete backend provider across upload, download, delete, copy, and connect-test operations—plus validation, React setup, registry, and database migration changes.

Merged PR #328 ↗
2026 — PRESENTBreak Through Tech · AI/ML Fellow

Selected from 4,000+ applicants for a year-long AI program and built a fairness-aware income classifier on 32,000+ U.S. Census records.

2024 — 2025De Anza College · C++ & Calculus Tutor

Helped 60+ students strengthen debugging, data structures, calculus, and independent problem-solving through one-to-one instruction.

03 / PROFILE

Jingi Min

I care about systems that are technically rigorous, explainable, and useful in the messy conditions outside a notebook.

EDUCATION

University of California, San Diego

B.S. Computer Science · Expected June 2027

GPA 3.98 / 4.0

CORE TOOLKIT

Python, C++, TypeScript, JavaScript, SQL, FastAPI, React, TensorFlow Lite, scikit-learn, Docker, MySQL, MQTT, LangGraph

RECOGNITION

SanD Hacks AGNTCY Track Winner

ECE140B Demo Day · 2nd Place

BASTA Code2Career Fellow