About

From atoms to tokens: map the supply chain, find the bottleneck, build the loop. #

Bridging atom factories and token factories. Atom factories build AI’s hardware — chips, servers, power. Token factories (data centers) turn that hardware into intelligence. My work lives in the translation between the two — between the physical constraints of supply and the AI workloads that run on top. I’ve worked both ends.

Product = Analysis + Process.

Analysis maps the supply chain and finds the bottleneck. Process turns the answer into a repeatable loop that can scale beyond one person.

Hi, I’m Chung-Hao (CH) Lee 李崇豪 — based in Sydney.

Since 2018, my work has followed one thread: find the physical single points of failure behind complex systems, then build the systems that manage them.

I started on factory floors and grew into AI systems. At Pegatron Suzhou, I led a 15-person cross-functional team operating the Google Home manufacturing line — ~2M AIoT units per year.

As a Supply Chain Analyst at the University of Maryland, I owned the semiconductor portion of a National Defense Industrial Association (NDIA) study — mapping raw-material, supplier, and logistics risk and the single points of failure inside them, using public data only. The work was covered by National Defense Magazine.

At Wistron Taipei — a global Tier-1 ODM for Dell — I brought industrial AI to Dell laptop manufacturing, delivering $1.2M in annual cost savings through AI-driven predictive maintenance across 20B+ telemetry records, scaling to 40B+, and deployed LLM for log analysis at scale. Dell’s SVP of Worldwide Procurement signed the 2023 award for the project I led.

Now at TikTok Sydney, I point the same method at AI itself: I built TikTok Live’s Root Cause Analysis system — process and platform — from 0 to 1, tracing why content-moderation models fail and routing each fix to the team that owns it. Its third generation, RCA Copilot, is an AI agent where humans and agents collaborate in one system.

The through-line isn’t a domain — it’s the method: map the supply chain, find the bottleneck, then design repeatable workflows that close the loop.

Experience #

TikTok — Product Operation Manager, Model Operation (AI/ML) · Sydney · 2025 – present #

I own Root Cause Analysis for TikTok Live’s content-moderation AI — the process, the platform, the models that evaluate it, and the day-to-day operation that keeps production models improving.

RCA process + platform — built both from 0→1 #

• Designed the end-to-end RCA process from scratch: how issues surface, how the right cases are found, how root cause is analysed, and how each finding is routed to the owning team — algorithm, labeling base, engineering, or policy — for the fix.
• Built the platform that operationalizes that process: consolidated data scattered across disconnected systems into one standardized workspace, unifying discovery, investigation, analysis, and issue hand-off in one place. Authored 15+ PRDs across Engineering, Data, Ops, and Policy.
• Cut end-to-end RCA time ~56% across the core team; 40+ active users, 10,000+ monthly queries, adoption spreading beyond RCA to adjacent functions.
• Third generation, RCA Copilot: an AI agent that plans the evidence it needs, retrieves it through purpose-built skills, and traces every model error to a single root cause — humans steering via human-in-the-loop. Evolved from human checklists → decision-tree attribution → agent platform.

AI model building + evaluation pipeline — from 0→1 #

• Built AI models from scratch to clean and validate data at scale (prompt engineering, multi-agent orchestration, agent-looping), producing the high-quality datasets used to evaluate production models.
• Stood up the team’s first systematic, repeatable model-evaluation pipeline: 1M+ cases across 62 iterations at ~99% labeling accuracy over 13 batches.

RCA operation — 35 live models #

• In the system’s early days, ran RCA across all 35 production models moderating live content (nudity, hate speech, bullying, and more) — broad coverage while the process was still forming.

• As the RCA platform matured and the operation scaled across the organisation, my scope focused to owning nudity detection end-to-end in greater depth — raising that model’s F1 score 38% (to 80%+) through multi-agent orchestration with an arbiter agent and describe-then-verify hallucination control.

• Established a recurring Product–Ops–Policy review that turns root-cause findings into owned fixes — replacing case-by-case escalation with a systematic feedback loop from risk discovery to downstream ownership.

• TikTok Spot Bonus Award, 2025 Q4 — for independently leading the RCA platform with strong ownership, and cross-functional delivery.

Wistron — AI Project Manager · Taipei · 2022 – 2024 #

• Worked inside a global Tier-1 ODM for Dell — the supplier side of the hardware supply chain.
• Led a three-phase industrial AI program for Dell laptop manufacturing (smart diagnosis → predictive forecasting → knowledge consolidation) across 6 cross-functional teams and 20B+ telemetry records, scaling to 40B+; also deployed LLMs for log analysis at scale.
• Results: 70% faster debugging · 50% fewer return-to-repairs · $1.2M annual savings.

Pegatron — Factory Project Manager · Suzhou · 2018 – 2020 #

• Led a 15-person cross-functional team operating the Google Home manufacturing line — 2M AIoT units per year.
• Owned end-to-end SMT + FATP process control on the factory floor.

University of Maryland — Supply Chain Analyst & Research Assistant · College Park · 2020 – 2022 #

• Owned the semiconductor portion of an NDIA study on supply-chain risk in defence-critical equipment — mapping single points of failure using public data only; covered by National Defense Magazine.

• Research became the Springer-published MiLB → MLB promotion prediction model, featured in Maryland Today.

Earlier: Substitute Military Service at Taoyuan International Airport (2016 – 2017) — honorably discharged with a Ministry of the Interior certificate of merit.

Education #

• MBA + MS Information Systems — University of Maryland, College Park (2020 – 2022), Smith Fellow Scholarship
• BS + MS — National Tsing Hua University, Taiwan

Selected Achievements #

• TikTok Spot Bonus Award, 2025 Q4 — for leading RCA Copilot 0→1
• Dell Outstanding Leadership & Execution Award, 2023 — presented to the Wistron AI Team for the program I led, signed by Dell’s SVP of Worldwide Procurement
• Wistron Excellent Digital Transformation Project Award, 2023
• Springer-published research — Baseball Informatics: From MiLB to MLB Debut; featured in Maryland Today · UMD Outstanding Graduate Student Award nomination, 2022
• Impact Consulting Fellowship, 1st Place (2021) · Hearst Data Competition, 3rd Place (2022) · Graduate Research Day, 2nd Place (2022)
• VP, Smith Masters Supply Chain Management Association & APICS

Earlier: Scrum Master certified (2023) · NTHU Dean’s List ×3

Built in Public — Extending the Bridge #

• multi-lens-thinking — A six-stage AI reasoning pipeline routing questions through four parallel analytical lenses.
• WikiPolyDraft — Open-source AI-drafted Wikipedia translation tool. First article: Barangaroo (Sydney). Same “AI drafts, human lands it” philosophy — applied to cross-language civic knowledge.
• My Daily Digest — Automated daily intelligence on AI data center infrastructure (NEXTDC, AirTrunk, Equinix AU, AEMC/AEMO grid signals), geopolitical risk, and AI builder updates. Built to keep my own atom × token thesis live.

What I Write About #

Four pillars that hold together everything on this site:

• AI Data Center Economics → Data Center 101 series (14 parts on PUE/WUE/GUE, cooling, power, supply chain, DCIM, RCA).
• Sydney as an AI Infrastructure Nexus → The Global AI Training Pivot: Positioning Sydney as a Strategic Infrastructure Nexus · The AI Supply Chain Dividend.
• Atoms × Tokens — the hardware-AI bridge → cross-cutting essays on supply-chain economics linking Taiwan ODM ecosystems to AI infrastructure deployment.
• Human-AI Collaboration & Agent Design → Beyond the Interface: Designing a Common Language for Humans and AI.

Let’s Talk #

If you’re working on AI infrastructure, data centers, or the supply chains and reliability operations behind them — especially in Sydney — I’d genuinely enjoy comparing notes. Reach me by email or on LinkedIn.