Available for collaboration & speaking
Dr. Donghao Huang

Dr. Donghao Huang

VP of R&D & Global Emerging Technology Lead at Mastercard · Executive-Scholar in AI

A senior technology executive with 27+ years of experience across software engineering, Web3, AI/ML/GenAI, and payments innovation. Combining elite enterprise execution with cutting-edge academic research, I recently completed a Doctor of Engineering in AI at Singapore Management University. Author of 28 peer-reviewed papers and inventor of 60+ patents, I specialize in translating advanced AI breakthroughs into scalable financial infrastructure.

27+
Years in tech
10
Patents granted
50+
Patents pending
28
Publications
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Arlington, VA, USA • donghao.huang@gmail.com
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About Me

Technology executive with 27+ years of experience across software engineering, Web3, AI/ML/GenAI, and payments innovation. Currently leading global R&D for Mastercard Emerging Technology (AI/Web3), having recently completed a Doctor of Engineering in AI from Singapore Management University. Author of 28 peer-reviewed research papers spanning LLM deployment, classical ML and risk/predictive modeling, LLM/ML model optimization and applications, and multi-agent systems. Proven track record of translating academic research into enterprise-scale financial services solutions.

Education

Doctor of Engineering (EngD) in AI Aug 2023 – May 2026
Singapore Management University, Singapore
  • Doctoral dissertation: Generative AI in Enterprises: Optimizing Applications with Large Language Models (244 pp.). Supervisor: Prof. Zhaoxia Wang. Co-supervisor: Prof. Chong Wah Ngo.
  • Awarded IMDA SG Digital Scholarship (Postgraduate) 2025
  • Research focus: RAG, Edge AI, LLM/ML model optimization, multi-agent systems, sentiment analysis, reasoning LLMs
  • Published 25 peer-reviewed papers at top AI conferences and journals (AAAI, AAMAS, NAACL, IJCNN, PAKDD, IEEE CAI, IEEE SSCI, IEEE ICDM, IEEE Intelligent Systems, Artificial Intelligence Reviews, ACM Computing Surveys)
  • Featured story →
Master of Technology in Software Engineering Jan 2004 – Nov 2007
National University of Singapore, Singapore
Certificate, EDB Research and Training Programme Sep 2001 – Aug 2002
Centre for Optoelectronics, NUS, Singapore
Master of Science in Theoretical Physics Sep 1998 – Jul 2001
Peking University, Beijing, China
  • Published 2 peer-reviewed papers in physics journals
Bachelor of Engineering in Engineering Physics Sep 1989 – Jul 1995
Tsinghua University, Beijing, China

Career Timeline

Aug 2025 – Present Current
VP, R&D / Global EmTech Lead
Mastercard (U.S.)
Arlington, VA, USA
  • Lead global R&D initiatives in AI Emerging Technology (EmTech) domains
  • Lead EmTech research for 5 strategic "Big Bets" projects — high-impact, confidential initiatives aimed at shaping Mastercard's next-generation payment infrastructure and AI-powered commerce solutions
  • Built and led the Conversational Payment Agent (CPA / ConvPayMAS) — an agentic-commerce stack on Google's A2A protocol, the AP2 three-mandate chain and MCP tool servers; introduced the Agentic Success Rate (ASR) metric, which exposed silent workflow deviations across 18 LLMs and 90,000 task instances. 3 papers published
  • Lead GAIME (GenAI Merchant Enrichment) — LLM-based merchant information extraction and entity matching over Mastercard transaction descriptors at millions of transactions daily; matched the incumbent 8B production baseline with a 4B fine-tune at half the parameter count and 1.2× faster effective inference
  • Organized and hosted SENTIRE'25 (15th Workshop on Sentiment Analysis and Linguistic Linked Data) co-located with IEEE ICDM 2025, Washington DC
May 2022 – Jul 2025
VP, R&D / Global EmTech Lead
Mastercard Asia/Pacific
Singapore
  • Lead global R&D in Emerging Technology: AI / Machine Learning / Generative AI and Web3
  • Led EmTech research for Mastercard Assistant Platform (MAP) — a suite of digital assistants simplifying customer onboarding
  • Pioneered enterprise GenAI applications using LLMs for payments/commerce automation
  • Developed multi-agent systems for invoice reconciliation (99.9% accuracy), conversational payments (HMASP), cooperative test generation (CMAS4G2), and LLM-as-a-Judge evaluation frameworks
  • Built classical ML and predictive modeling systems for ICO success prediction, fake-news detection, and maritime risk classification — spanning ensemble methods (Random Forest, XGBoost, CatBoost), deep learning (CNN, RNN, LSTM), and transformers (BERT, RoBERTa)
  • Developed Mastercard Tokenized Card NFT solution and DigiPay Web3 micropayment stablecoin solution
Aug 2011 – May 2022
VP, R&D / Head of Singapore R&D
Mastercard Asia/Pacific
Singapore
  • Founded and led Singapore R&D team in Mastercard Foundry (Mastercard Labs) — global innovation and R&D division
  • Drove innovation across EMV Chip, IoT, QR Payments, Connected Car, Humanoid Robots, Conversational AI, AR/VR, Blockchain, Web3, NFT, DeFi, and Metaverse
  • Won Smart Sentosa Challenge 2016 with Mastercard Asia-Pacific’s Smart City Engine
  • Key commercialized projects: Crescent City Card, BharatQR, Mastercard Aid Network, SoftBank Pepper commerce, SmartWallet, and more
Jul 2008 – Aug 2011
Senior Software Engineer / Team Lead
PayPal
Singapore
  • Led software development teams for Brazil market projects; SME in limits/verification/compliance
  • Delivered largest EU compliance project (EU KYB Receiving Limit) in 8 months; built China UnionPay (CUP) integration
1995 – 2008
Earlier Roles
Software Engineering & R&D Leadership
  • Software R&D Manager — Streaming21, Singapore (2007–2008)
  • Leader, Software Development — Schmidt Electronics (S.E.A.), Singapore (2006–2007)
  • Software Engineer — Unaxis Singapore (2005)
  • Software Engineer — ASM Technology Singapore (2002–2005)
  • Software Engineer — Beijing Zhida Technology, China (1995–1998)

Technical Skills

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

Patents

10 granted, 50+ pending — all assigned to Mastercard. View all on Google Patents →

Granted Patents

Patent No. Title Granted
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

Selected Pending Applications

Patent No. Title Filed
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

… and 40+ additional pending patent applications across payment technology, blockchain, AI, and IoT domains.

Publications

28 peer-reviewed papers — 26 in Artificial Intelligence, 2 in Theoretical Physics. Highlighted papers appear at top-tier venues.

Artificial Intelligence

  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.

Theoretical Physics

  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.

Speaking & Panels

Invited keynotes, conference talks, and panel appearances at international technology events.

Invited Talks & Panels

Paper Presentations

Awards & Recognitions

Selected Media Coverage

Volunteering Experience

President — Bao Yan (Singapore) Education Society Nov 2025 – Present
Vice President — Peking University Alumni Association (Singapore) Jun 2016 – Jun 2020
Mentor — Startupbootcamp FinTech, Singapore Jan 2015 – Jan 2019
IT and Payment Consultant — ConneXions International, Singapore Mar 2011 – Dec 2015
Technology Consultant — St. Andrew's Autism Centre, Singapore Nov 2006 – Jul 2008

Hobby Websites

Buddhist Studies (香光庄严)

A curated collection of Buddhist teachings, sutras, commentaries, and practice guides — including works by Master Mengcan, Master Yinguang, and more.

Visit →

Merchant Matching – Entity Extraction

Enter a raw bank transaction to extract structured entity fields using fine-tuned open-weight LLMs.

Try it →