NiceguyLang

Education

Khory College of Computer Science

Master of Science in Computer Science

Relevant Course: Machine Learning, AI-Assisted Coding, Data Mining, Algorithm, Program Design Paradigms, Privacy and Security

College of Engineering

Bachelor of Science in Computer Science and Engineering

Relevant Course: Knowledge-based System, Software Engineering, Mobile & Web App Development, Data Structure

AI Research Assistant Internship -- Remote (part-time)

Preprocessed datasets with text content for language model evaluation, ensuring data quality and consistency across test cases
Developed a Python-based evaluation pipeline integrating APIs from 9 large language models, automating benchmark execution and performance analysis on language comprehension and reasoning tasks
Diagnosed and fixed runtime failures in the process, documenting comparative performance metrics

Built a full-stack web app (FastAPI + Next.js 15 / React / TypeScript), transforming a research notebook into a deployable interactive tool with a layered backend separating routers, core compute, and visualization
Collaborated directly with the Principal Investigator and researchers at Oak Ridge National Laboratory to define product requirements, target users, project scope, and development roadmap
Implemented an async job system with polling-based REST endpoints, allowing long-running optimization tasks to execute in the background without blocking requests

Designed and deployed a production trip-planning web app on Vercel + Railway + Supabase with JWT/bcrypt auth, Zod validation, and a documented 10-endpoint REST API
Engineered a real-time departure planning system using HERE Routing and Transit APIs to calculate optimal "leave-by" times for driving and public transit; implemented background jobs for API quota-aware ETA refresh and Web Push departure alerts
Wrote 147 tests to 82.5% coverage and built a 4-stage GitHub Actions CI pipeline (lint, ephemeral-Postgres integration tests, coverage, security audit)

Built a scikit-learn regression pipeline predicting dating-app match counts from 29 features across 1,209 users; benchmarked neural network, Random Forest, KNN, and linear models
Collaborated with a peer for data preprocessing, model implementation, and performance evaluation, demonstrating effective teamwork and technical communication

Built a fault-tolerant LLM pipeline (Python, Gemini 2.5 Flash) that classified 23,703 CFPB complaints (~4.5M words) for residual PII, with checkpoint and rate-limit handling
Manually built a 460-example validation set and applied precision-based statistical correction to raw flags provided by LLM to estimate true leaks
Managed project timeline and delegated tasks as the team leader; facilitated weekly team meetings and resolved technical blockers; presented at all project reviews

Led a team of 4 students in designing a software application for autonomous vehicle ride-sharing services following a plan-driven development
Conducted domain analysis and value chain assessment to identify key challenges and propose technical solution
Authored comprehensive use cases, functional requirements (FR), non-functional requirements (NFR), and acceptance plan
Performed target environment analysis and developed subsystem architecture
Created project estimation and risk management strategy to ensure on-time delivery

Design and developed a searcher for tagged image in reactive programming
Implemented interactive visualizations in Observable Notebook to enable dynamic user exploration of results