Wei-Ting Liu
NTU Information Management + Trans-disciplinary Bachelor Degree.
Full-stack engineer with an AI-native mindset, building data-driven products.
Open to every chance and place to learn.
Full-stack engineer moving into reinforcement learning R&D, currently designing a dual-loop RL system at ABConvert that trains agents to optimize Shopify stores while closing the sim-to-real gap. In parallel, researching multi-agent RL for decentralized epidemic surveillance, benchmarking MARL against supervised baselines across 26 simulated regions.
Grounded in shipped product work: migrated a 10-page marketing site to Next.js at a 97 Lighthouse SEO score, built internal analytics dashboards that cut manual metric lookups by ~70%, and led AI adoption workshops that moved 80% of a research center's staff from chat-based AI use to building their own tools. B.B.A. student in Information Management and the Trans-disciplinary Program (College of Innovation) at NTU.
ABConvert — Reinforcement Learning R&D Intern
Shopify A/B Testing SaaS
- Designed a dual-loop RL system that trains agents to optimize Shopify stores, aiming to build an accurate, real-world-calibrated simulator that closes the sim-to-real gap.
NTU Insight Center — AI Intern
- Developed an internal service-design product and led AI adoption workshops, moving 80% of staff from chat-based AI use to building their own website products.
ABConvert — Software Engineer Intern
Shopify A/B Testing SaaS
- Migrated abconvert.io (10 pages) from Webflow to a self-hosted Next.js app, reaching a 97 Lighthouse SEO score and enabling custom interactive components.
- Built internal dashboard features (experiment research, visualization, analysis) from a cross-team needs survey, eliminating ~70% of manual metric lookups for Customer Success and the CEO.
ABConvert — Startup Generalist Summer Intern (Product/AI)
Shopify A/B Testing SaaS
- AI-native generalist: LLM-assisted workflow to compress spec → implementation loop; shipped Next.js + TypeScript frontend (SSR/ISR, streaming UI) at startup pace.
Multi-Agent RL for Decentralized Epidemic Surveillance
Advised by Wayne Lee
- Built a CTDE multi-agent RL framework (MAPPO/QMIX) modeling Brazil's 26 states as agents alerting on dengue from case counts and Google Trends, benchmarked against an information-parity baseline and a supervised oracle.
- Found MARL systematically underperforms the baseline across algorithm, reward, cost, and environment variations; ruled out five candidate explanations, isolating the bottleneck to RL sample efficiency rather than the surveillance signal. Manuscript in preparation, targeting Oct 2026.
National Taiwan University
B.B.A. in Information Management · Double Major: Trans-disciplinary Program (College of Innovation) · Leadership Program
Next.js 15, TypeScript, React, Tailwind CSS, Spotify Web API, shadcn/ui. Real-time multiplayer music guessing game with 1,300+ active users; host pastes any Spotify playlist URL and the app fetches tracks via Spotify Client Credentials, running a round-by-round quiz with audio clips, live scoring, and answer validation.
ABConvert.io Website Migration
Next.js, TypeScript. Migrated abconvert.io (10 pages) from Webflow to a self-hosted Next.js app, reaching a 97 Lighthouse SEO score and enabling custom interactive components.
Open to internship and full-time opportunities in SWE, AI/ML, and product engineering.