开放合作与演讲邀约
黄东浩博士 Dr. Donghao Huang

黄东浩博士

万事达卡研发副总裁兼全球新兴技术负责人 · AI 领域高管学者

资深科技高管，拥有27年以上从业经验，横跨软件工程、Web3、AI/ML/生成式AI 与支付创新领域。融合顶尖企业实战与前沿学术研究， 近期于新加坡管理大学完成人工智能工程博士学位。发表28篇同行评审论文、 发明60余项专利，专注于将前沿AI突破转化为可规模化的金融基础设施。

27+
年技术经验
10
已授权专利
50+
待审专利
28
学术论文
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美国弗吉尼亚州阿灵顿 • donghao.huang@gmail.com
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关于我

科技高管，拥有27年以上软件工程、Web3、AI/ML/生成式AI及支付创新领域的从业经验。目前担任万事达卡新兴技术（AI/Web3）全球研发负责人，并已于新加坡管理大学完成AI工程博士学位。已发表28篇同行评审论文，涵盖大语言模型（LLM）部署、经典ML与风险/预测建模、LLM/ML模型优化与应用、多智能体系统等领域。具备将学术研究成果转化为企业级金融服务解决方案的丰富经验。

教育背景

AI工程博士（EngD） Aug 2023 – May 2026
新加坡管理大学，新加坡
  • 博士论文：Generative AI in Enterprises: Optimizing Applications with Large Language Models（244 页）。主导师：Prof. Zhaoxia Wang；副导师：Prof. Chong Wah Ngo。
  • 荣获2025年IMDA新加坡数字奖学金（研究生）
  • 研究方向：检索增强生成（RAG）、边缘AI、LLM/ML模型优化、多智能体系统、情感分析、推理LLM
  • 在顶级AI会议和期刊发表25篇同行评审论文（AAAI、AAMAS、NAACL、IJCNN、PAKDD、IEEE CAI、IEEE SSCI、IEEE ICDM、IEEE Intelligent Systems、Artificial Intelligence Reviews、ACM Computing Surveys）
  • 专题报道 →
软件工程技术硕士 Jan 2004 – Nov 2007
新加坡国立大学，新加坡
EDB研究与培训计划证书 Sep 2001 – Aug 2002
新加坡国立大学光电子学中心，新加坡
理论物理学理学硕士 Sep 1998 – Jul 2001
北京大学，北京，中国
  • 在物理学期刊发表2篇同行评审论文
工程物理学工学学士 Sep 1989 – Jul 1995
清华大学，北京，中国

职业历程

Aug 2025 – Present 在职
研发副总裁 / 全球新兴技术负责人
万事达卡（美国）
美国弗吉尼亚州阿灵顿
  • 领导AI新兴技术（EmTech）领域的全球研发工作
  • 负责5个战略性"大赌注"项目的新兴技术研究——旨在构建万事达卡下一代支付基础设施和AI驱动商务解决方案的高影响力保密计划
  • 构建并领导对话式支付智能体（CPA / ConvPayMAS）——基于 Google A2A 协议、AP2 三重授权链与 MCP 工具服务的智能体商务支付技术栈；提出智能体成功率（ASR）指标，在18个LLM、9万次任务实例的评测中揭示了隐性工作流偏差。发表3篇论文
  • 领导 GAIME（生成式AI商户信息增强）——面向万事达卡交易描述符的商户信息抽取与实体匹配，日均处理数百万笔交易；以4B微调模型达到现有8B生产基线的准确率，参数量减半且有效推理速度提升1.2倍
  • 主办SENTIRE'25（第15届情感分析与语言关联数据研讨会），与IEEE ICDM 2025同期举行，华盛顿特区
May 2022 – Jul 2025
研发副总裁 / 全球新兴技术负责人
万事达卡亚太区
新加坡
  • 领导新兴技术全球研发：AI / 机器学习 / 生成式AI及Web3
  • 主导Mastercard Assistant Platform (MAP)的新兴技术研究——一套简化客户入门流程的数字助手
  • 率先开发基于LLM的企业级生成式AI应用，用于支付/商务自动化
  • 开发用于发票对账（准确率99.9%）、对话式支付（HMASP）、协作测试生成（CMAS4G2）的多智能体系统及LLM-as-a-Judge评估框架
  • 构建用于ICO成功预测、假新闻检测和海事风险分类的经典ML与预测建模系统 — 涵盖集成方法（随机森林、XGBoost、CatBoost）、深度学习（CNN、RNN、LSTM）和Transformer（BERT、RoBERTa）
  • 开发万事达卡代币化NFT卡解决方案和DigiPay Web3微支付稳定币解决方案
Aug 2011 – May 2022
研发副总裁 / 新加坡研发负责人
万事达卡亚太区
新加坡
  • 创立并领导万事达卡Foundry（万事达卡实验室）新加坡研发团队——全球创新研发部门
  • 推动EMV芯片、物联网、二维码支付、网联汽车、人形机器人、对话AI、AR/VR、区块链、Web3、NFT、DeFi和元宇宙等领域的创新
  • 2016年万事达卡亚太区智慧城市引擎赢得 Smart Sentosa 挑战赛
  • 主要商业化项目：新月城市卡、BharatQR、万事达卡援助网络、软银Pepper商务、SmartWallet等
Jul 2008 – Aug 2011
高级软件工程师 / 团队负责人
PayPal
新加坡
  • 领导巴西市场软件开发团队；限额/验证/合规领域专家
  • 在8个月内交付最大规模欧盟合规项目（欧盟KYB收款限额）；构建中国银联（CUP）集成
1995 – 2008
早期职位
软件工程与研发管理
  • 软件研发经理 — Streaming21，新加坡（2007–2008）
  • 软件开发负责人 — 施密特电子（东南亚），新加坡（2006–2007）
  • 软件工程师 — Unaxis新加坡（2005）
  • 软件工程师 — ASM科技新加坡（2002–2005）
  • 软件工程师 — 北京智达科技，中国（1995–1998）

技术技能

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 编程语言 Python, C/C++, Java, NodeJS, React, Vue, Spring Boot/Cloud, Solidity 云计算 AWS, Azure, Heroku; Microservices, CI/CD, Docker Web3 Blockchain, Smart Contract, IPFS, NFT, DeFi

专利

10项已授权，50+项待审 — 均归属万事达卡。 在Google Patents查看全部 →

已授权专利

专利号 发明名称 授权日期
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

部分待审申请

专利号 发明名称 申请日期
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+项其他待审专利申请，涵盖支付技术、区块链、AI和物联网领域。

学术发表

28篇同行评审论文 — 26篇人工智能领域，2篇理论物理领域。 高亮标注的论文发表于顶级学术平台。

人工智能

  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.

理论物理

  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.

演讲与论坛

受邀在国际技术会议发表主题演讲及参与专家论坛。

受邀演讲与论坛

论文发表演讲

荣誉与奖项

媒体报道精选

志愿服务经历

会长 — 宝严（新加坡）教育学会 Nov 2025 – Present
副会长 — 北京大学校友会（新加坡） Jun 2016 – Jun 2020
导师 — Startupbootcamp金融科技加速器，新加坡 Jan 2015 – Jan 2019
IT与支付顾问 — ConneXions International，新加坡 Mar 2011 – Dec 2015
技术顾问 — 圣安德烈自闭症中心，新加坡 Nov 2006 – Jul 2008

个人兴趣网站

Buddhist Studies (香光庄严)

精心整理的佛教教义、经典、注疏和修行指南——包括梦参老和尚、印光大师等高僧的著作。

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商户匹配 – 实体提取

输入银行原始交易记录，使用微调开源大语言模型提取结构化实体字段。

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