開放合作與演講邀約
黃東浩博士 Dr. Donghao Huang

黃東浩博士

萬事達卡研發副總裁兼全球新興技術負責人 · AI 領域高管學者

資深科技高管，擁有27年以上從業經驗，橫跨軟體工程、Web3、AI/ML/生成式AI 與支付創新領域。融合頂尖企業實戰與前沿學術研究， 近期於新加坡管理大學完成人工智能工程博士學位。發表28篇同行評審論文、 發明60餘項專利，專注於將前沿AI突破轉化為可規模化的金融基礎設施。

27+
年技術經驗
10
已授權專利
50+
待審專利
28
學術論文
下載簡歷 LinkedIn GitHub 學術主頁 ORCID ResearchGate 電郵
美國維吉尼亞州阿靈頓 • donghao.huang@gmail.com
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關於我

科技高管，擁有27年以上軟體工程、Web3、AI/ML/生成式AI及支付創新領域的從業經驗。目前擔任萬事達卡新興技術（AI/Web3）全球研發負責人，並已於新加坡管理大學完成AI工程博士學位。已發表28篇同行評審論文，涵蓋大語言模型（LLM）部署、經典ML與風險/預測建模、LLM/ML模型優化與應用、多智能體系統等領域。具備將學術研究成果轉化為企業級金融服務解決方案的豐富經驗。

教育背景

AI工程博士（EngD） Aug 2023 – May 2026
新加坡管理大學，新加坡
  • 博士論文：Generative AI in Enterprises: Optimizing Applications with Large Language Models（244 頁）。指導教授：Prof. Zhaoxia Wang；共同指導教授：Prof. Chong Wah Ngo。
  • 榮獲2025年IMDA新加坡數位獎學金（研究生）
  • 研究方向：檢索增強生成（RAG）、邊緣AI、LLM/ML模型優化、多智能體系統、情感分析、推理LLM
  • 在頂級AI會議和期刊發表25篇同行評審論文（AAAI、AAMAS、NAACL、IJCNN、PAKDD、IEEE CAI、IEEE SSCI、IEEE ICDM、IEEE Intelligent Systems、Artificial Intelligence Reviews、ACM Computing Surveys）
  • 專題報導 →
軟體工程技術碩士 Jan 2004 – Nov 2007
新加坡國立大學，新加坡
EDB研究與培訓計劃證書 Sep 2001 – Aug 2002
新加坡國立大學光電子學中心，新加坡
理論物理學理學碩士 Sep 1998 – Jul 2001
北京大學，北京，中國
  • 在物理學期刊發表2篇同行評審論文
工程物理學工學學士 Sep 1989 – Jul 1995
清華大學，北京，中國

職業歷程

Aug 2025 – Present 在職
研發副總裁 / 全球新興技術負責人
萬事達卡（美國）
美國維吉尼亞州阿靈頓
  • 領導AI新興技術（EmTech）領域的全球研發工作
  • 負責5個戰略性「大賭注」專案的新興技術研究——旨在構建萬事達卡下一代支付基礎設施和AI驅動商務解決方案的高影響力保密計劃
  • 構建並領導對話式支付智慧體（CPA / ConvPayMAS）——基於 Google A2A 協議、AP2 三重授權鏈與 MCP 工具服務的智慧體商務支付技術棧；提出智慧體成功率（ASR）指標，在18個LLM、9萬次任務實例的評測中揭示了隱性工作流偏差。發表3篇論文
  • 領導 GAIME（生成式AI商戶資訊增強）——面向萬事達卡交易描述符的商戶資訊抽取與實體匹配，日均處理數百萬筆交易；以4B微調模型達到現有8B生產基線的準確率，參數量減半且有效推理速度提升1.2倍
  • 主辦SENTIRE'25（第15屆情感分析與語言關聯資料研討會），與IEEE ICDM 2025同期舉行，華盛頓特區
May 2022 – Jul 2025
研發副總裁 / 全球新興技術負責人
萬事達卡亞太區
新加坡
  • 領導新興技術全球研發：AI / 機器學習 / 生成式AI及Web3
  • 主導Mastercard Assistant Platform (MAP)——一套簡化客戶入門流程的數位助理
  • 率先開發基於LLM的企業級生成式AI應用，用於支付/商務自動化
  • 開發用於發票對帳（準確率99.9%）、對話式支付（HMASP）、協作測試生成（CMAS4G2）的多智能體系統及LLM-as-a-Judge評估框架
  • 構建用於ICO成功預測、假新聞檢測和海事風險分類的經典ML與預測建模系統 — 涵蓋整合方法（隨機森林、XGBoost、CatBoost）、深度學習（CNN、RNN、LSTM）和Transformer（BERT、RoBERTa）
  • 開發萬事達卡代幣化NFT卡解決方案和DigiPay Web3微支付穩定幣解決方案
Aug 2011 – May 2022
研發副總裁 / 新加坡研發負責人
萬事達卡亞太區
新加坡
  • 創立並領導萬事達卡Foundry（萬事達卡實驗室）新加坡研發團隊——全球創新研發部門
  • 推動EMV晶片、物聯網、QR碼支付、網聯汽車、人形機器人、對話AI、AR/VR、區塊鏈、Web3、NFT、DeFi和元宇宙等領域的創新
  • 2016年萬事達卡亞太區智慧城市引擎贏得 Smart Sentosa 挑戰賽
  • 主要商業化專案：新月城市卡、BharatQR、萬事達卡援助網絡、軟銀Pepper商務、SmartWallet等
Jul 2008 – Aug 2011
高級軟體工程師 / 團隊負責人
PayPal
新加坡
  • 領導巴西市場軟體開發團隊；限額/驗證/合規領域專家
  • 在8個月內交付最大規模歐盟合規專案（歐盟KYB收款限額）；構建中國銀聯（CUP）整合
1995 – 2008
早期職位
軟體工程與研發管理
  • 軟體研發經理 — Streaming21，新加坡（2007–2008）
  • 軟體開發負責人 — 施密特電子（東南亞），新加坡（2006–2007）
  • 軟體工程師 — Unaxis新加坡（2005）
  • 軟體工程師 — ASM科技新加坡（2002–2005）
  • 軟體工程師 — 北京智達科技，中國（1995–1998）

技術技能

AI/ML/GenAI LLMs (GPT-4/5, Claude, Gemini, Llama, Qwen, DeepSeek-R1, Mistral, Phi, Nemotron), PyTorch, Transformers, PEFT, LoRA/QLoRA, LlamaFactory, Unsloth, RAG, LangChain, LangGraph, Autogen, Ollama, FAISS, Chroma, Prompt Engineering, Few-shot Learning, NLP, Sentiment Analysis, Agentic AI, Edge AI Deployment, Energy-efficient Inference GPU/Hardware NVIDIA H100, L40, A40, RTX 4080/4090/A6000, Jetson AGX Orin, DGX Spark; Apple M-series 程式語言 Python, C/C++, Java, NodeJS, React, Vue, Spring Boot/Cloud, Solidity 雲端運算 AWS, Azure, Heroku; Microservices, CI/CD, Docker Web3 Blockchain, Smart Contract, IPFS, NFT, DeFi

專利

10項已授權，50+項待審 — 均歸屬萬事達卡。 在Google Patents查看全部 →

已授權專利

專利號 發明名稱 授權日期
US12417452B2 Smart chip payment acceptance 2025-09-16
US12217246B2 Method and system for use of an EMV card in a multi-signature wallet for cryptocurrency transactions 2025-02-04
US11715100B2 Electronic system and computerized method for verification of transacting parties to process transactions 2023-08-01
US11615406B2 Method and system for providing a service at a self-service machine 2023-03-28
US10535034B2 Item delivery management systems and methods 2020-01-14
US10482499B2 Method for conducting a transaction 2019-11-19
US10423949B2 Vending machine transactions 2019-09-24
US10083427B2 Method for receiving an electronic receipt of an electronic payment transaction into a mobile device 2018-09-25
US9836729B2 Method and system for conducting a payment transaction and corresponding devices 2017-12-05
US8712914B2 Method and system for facilitating micropayments in a financial transaction system 2014-04-29

部分待審申請

專利號 發明名稱 申請日期
WO2026063867A1 Method and system for seamless cross-network physical-digital (phy-gital) experience 2024-09-18
US20260080407A1 Method and system for seamless cross-network physical-digital (phy-gital) experience 2024-09-06
WO2024058723A1 Digitization of payment cards for web 3.0 and metaverse transactions 2022-09-16
US20230059546A1 Access control system 2021-08-17
EP4356332A2 Method and system for mediated cross ledger stable coin atomic swaps using hashlocks 2021-06-17
US20210406887A1 Method and system for merchant acceptance of cryptocurrency via payment rails 2020-06-24
US20210158316A1 Electronic system and computerized method for controlling operation of service devices 2019-11-22
US20200175489A1 Method and system for QR code originated vending 2017-05-24
WO2017200643A1 Method and system for allocating and transacting with multiple non-financial commodities 2016-05-18
US20180025332A1 Transaction facilitation 2016-07-20

…以及40+項其他待審專利申請，涵蓋支付技術、區塊鏈、AI和物聯網領域。

學術發表

28篇同行評審論文 — 26篇人工智慧領域，2篇理論物理領域。 醒目標示的論文發表於頂級學術平台。

人工智慧

  1. Huang, D., Drietomský, T., Barrett, B. & Wang, Z. (2026). How Small Can You Go? LoRA Fine-Tuning 270M–8B Models for Merchant Information Extraction in Financial Transactions. Accepted for publication in 2026 IEEE International Conference on Data Mining (ICDM 2026), Shenyang, China.
  2. Teo, N., Huang, D. & Wang, Z. (2026). A Survey of Commonsense Reasoning in LLMs. ACM Computing Surveys, vol. 58, no. 14, pp. 1–34 (2026).
  3. Chua, J. K., Huang, D. & Wang, Z. (2026). A Novel Hierarchical Multi-agent System for Payments Using LLMs. In: Wong, R. C.-W., et al. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2026. Lecture Notes in Computer Science, vol. 16598, pp. 28–39. Springer, Singapore.
  4. Huang, D. & Wang, Z. (2026). Task Complexity Matters: An Empirical Study of Reasoning in LLMs for Sentiment Analysis. In: Wong, R. C.-W., et al. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2026. Lecture Notes in Computer Science, vol. 16600, pp. 288–299. Springer, Singapore.
  5. Huang, D., Chua, J. K. & Wang, Z. (2027). Beyond Task Success: Measuring Workflow Fidelity in LLM-Based Agentic Payment Systems. In: Long, C., et al. (eds) Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2026. Lecture Notes in Computer Science, vol. 16603, pp. 357–362. Springer, Singapore.
  6. Huang, D., Pai, P. & Wang, Z. (2027). Entity Matching with LLMs at Scale: Accuracy, Cost, and Reasoning Effects. In: Long, C., et al. (eds) Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2026. Lecture Notes in Computer Science, vol. 16603, pp. 112–124. Springer, Singapore.
  7. Huang, D., Chew, S. & Wang, Z. (2027). CMAS4G2: A Locally Deployed Cooperative Multi-agent System for Gherkin Acceptance Test Generation. In: Long, C., et al. (eds) Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2026. Lecture Notes in Computer Science, vol. 16603, pp. 156–167. Springer, Singapore.
  8. Huang, D. & Pandey, M. (2026). An Agentic Voice-Based Assistant for Interactive Conversation and Guidance in Real-World Environments. Proceedings of the 25th International Conference on Autonomous Agents and Multiagent Systems (AAMAS '26), Paphos, Cyprus, pp. 4167–4169. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC.
  9. Chua, J. K., Tse, C. H., Huang, D. & Wang, Z. (2026). ConvPayMAS: Conversational Payment Multi-Agent System with Agent-to-Agent Protocol and Three-Mandate Verification. Proceedings of the 25th International Conference on Autonomous Agents and Multiagent Systems (AAMAS '26), Paphos, Cyprus, pp. 4071–4073. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC.
  10. Huang, D., Malwe, G. & Wang, Z. (2026). When Agents Fail to Act: A Diagnostic Framework for Tool Invocation Reliability in Multi-Agent LLM Systems. 2026 9th International Conference on Artificial Intelligence and Big Data (ICAIBD), Chengdu, China, pp. 492–497. IEEE.
  11. Huang, D., Chew S., Dutkiewicz A. & Wang, Z. (2026). LLM-as-a-Judge for Scalable Test Coverage Evaluation: Accuracy, Operational Reliability, and Cost. AAAI 2026 Workshop on Next-Gen Code Development with Collaborative AI Agents.
  12. Huang, D., Teo, N., Chekuru, A., Deutschman, E. & Wang, Z. (2025). Deploying Reasoning LLMs for Sentiment Analysis: Architecture Trade-offs on Consumer Hardware. 2025 IEEE International Conference on Data Mining Workshops (ICDMW), Washington, DC, USA, pp. 2048–2055. IEEE.
  13. Samuel, S., Huang, D., Hong, J. T. Y. & Wang, Z. (2025). Integrating LLM Sentiment Analysis into Machine Learning for Soccer Betting. 2025 IEEE International Conference on Data Mining Workshops (ICDMW), Washington, DC, USA, pp. 2156–2164. IEEE.
  14. Huang, D. & Wang, Z. (2025). Explainable Sentiment Analysis With DeepSeek-R1: Performance, Efficiency, and Few-Shot Learning. IEEE Intelligent Systems, vol. 40, no. 6, pp. 52-63, Nov.-Dec. 2025.
  15. Huang, D., Ng, D., Wang, Z., Pen, H. & Cambria, E. (2025). Evaluating the Impact of LLM-Manipulated Content on Fake News Detection. In: Yuan, S., Malliaros, F. D. & Zheng, X. (eds) Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2025. Lecture Notes in Computer Science, vol. 15835, pp. 375-386. Springer Nature Singapore.
  16. Teo, N., Huang, D., Cambria, E., Wang, Z. (2025). Large Language Models for Logical Fallacy Detection. In: Yuan, S., Malliaros, F. D. & Zheng, X. (eds) Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2025. Lecture Notes in Computer Science, vol. 15835, pp. 387-398. Springer Nature Singapore.
  17. Huang, D. & Wang, Z. (2025). LLMs at the Edge: Performance and Efficiency Evaluation with Ollama on Diverse Hardware. 2025 International Joint Conference on Neural Networks (IJCNN), Rome, Italy, pp. 1-8. IEEE.
  18. Huang, D., Nguyen, T. S., Liausvia, F. & Wang, Z. (2025). RAP: A Metric for Balancing Repetition and Performance in Open-Source Large Language Models. NAACL 2025 (Long Papers), pp. 1479-1496.
  19. Huang, D., Malwe, G., Varshney, R., Tse, A. & Wang, Z. (2025). Scalable Invoice Reconciliation for SMEs: Edge-Deployed LLMs in Multi-Agent Systems. 2025 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI), Chennai, India, pp. 1–6. IEEE.
  20. Huang, D. & Wang, Z. (2025). Optimizing Chinese-to-English Translation Using Large Language Models. 2025 IEEE Symposium on Computational Intelligence in Natural Language Processing and Social Media (CI-NLPSoMe), Trondheim, Norway, pp. 1–7. IEEE.
  21. Huang, D. & Wang, Z. (2025). Logical Reasoning with LLMs via Few-Shot Prompting and Fine-Tuning: A Case Study on Turtle Soup Puzzles. 2025 IEEE Symposium on Computational Intelligence in Natural Language Processing and Social Media (CI-NLPSoMe Companion), Trondheim, Norway, pp. 1–5. IEEE.
  22. Wang, Z., Huang, D., Cui, J. et al. (2025). A review of Chinese sentiment analysis: subjects, methods, and trends. Artificial Intelligence Review, 58, 75 (2025).
  23. Huang, D., Fu, X., Yin, X., Pen, H. & Wang, Z. (2024). Automating maritime risk data collection and identification leveraging large language models. 2024 IEEE International Conference on Data Mining Workshops (ICDMW), pp. 433–439. IEEE.
  24. Huang, D., Hu, Z. & Wang, Z. (2024). Performance Analysis of Llama 2 Among Other LLMs. 2024 IEEE Conference on Artificial Intelligence (CAI), pp. 1081-1085. IEEE.
  25. Huang, D. & Wang, Z. (2024). Evaluation of Orca 2 Against Other LLMs for Retrieval Augmented Generation. In: Wang, Z. & Tan, C. W. (eds) Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2024. Lecture Notes in Computer Science, vol. 14658, pp. 3–19. Springer Nature Singapore.
  26. Huang, D., Samuel, S., Hyunh, Q. T. & Wang, Z. (2024). From Tweets to Token Sales: Assessing ICO Success Through Social Media Sentiments. In: Wang, Z. & Tan, C. W. (eds) Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2024. Lecture Notes in Computer Science, vol. 14658, pp. 57–69. Springer Nature Singapore.

理論物理

  1. Lin, W. B., Huang, D. H., Zhang, X. & Brandenberger, R. (2001). Nonthermal production of weakly interacting massive particles and the subgalactic structure of the universe. Physical Review Letters, 86(6), 954.
  2. Huang, D. H., Lin, W. B. & Zhang, X. M. (2000). Remark on approximation in the calculation of the primordial spectrum generated during inflation. Physical Review D, 62(8), 087302.

演講與論壇

受邀於國際技術會議發表主題演講及參與專家論壇。

受邀演講與論壇

論文發表演講

榮譽與獎項

媒體報導精選

志願服務經歷

會長 — 寶嚴（新加坡）教育學會 Nov 2025 – Present
副會長 — 北京大學校友會（新加坡） Jun 2016 – Jun 2020
導師 — Startupbootcamp金融科技加速器，新加坡 Jan 2015 – Jan 2019
IT與支付顧問 — ConneXions International，新加坡 Mar 2011 – Dec 2015
技術顧問 — 聖安德魯自閉症中心，新加坡 Nov 2006 – Jul 2008

個人興趣網站

Buddhist Studies (香光庄严)

精心整理的佛教教義、經典、注疏和修行指南——包括夢參老和尚、印光大師等高僧的著作。

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商戶匹配 – 實體提取

輸入銀行原始交易記錄，使用微調開源大語言模型提取結構化實體欄位。

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