Xiaoquan KongAI Engineer & Researcher I build AI systems that work at scale—from research prototypes to production platforms serving millions. My work focuses on agentic AI, retrieval-augmented generation, and reinforcement learning. At Baidu and Alibaba, I built conversational AI systems deployed across millions of vehicles serving large-scale production workloads. I hold a MEng from Duke University and am a Google Developer Expert in Machine Learning. Email: xiaoquan.kong@duke.edu / GitHub / LinkedIn / Google Scholar |
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Research Interests
- Agentic AI Systems: Multi-agent architectures, tool use, agent coordination
- Retrieval-Augmented Generation: Multi-modal RAG, evidence-based reasoning
- Reinforcement Learning: RLHF for LLM alignment, offline RL, model-based RL
- Production ML Systems: Scalable deployment, low-latency inference, system optimization
Research & Development
Reinforcement Learning Curriculum Development
Duke University
Designed curriculum for graduate RL course (AIPI 531) covering tabular methods to modern RLHF. Built complete alignment pipeline from scratch—reward modeling, PPO training, safety evaluation—demonstrating significant improvements in model safety. Students implement core algorithms from first principles, learning to align language models with human preferences.
Educational AI Development
Duke CREATE (Center for Research & Engineering of AI Technology in Education)
Developing QUBIT, an AI programming assistant that teaches through explanation rather than direct code generation. Implementing scaffolded prompting and constraint-based hints to guide students through problem-solving while maintaining engagement.
Selected Projects
A minimal implementation (~300 lines) exposing the complete control flow of agentic systems. By avoiding framework abstractions, it reveals how tool-calling and multi-agent coordination actually work—enabling developers to understand and modify agent behaviors at the implementation level. Supports major LLMs via LiteLLM.
PyTorch-compatible ML framework built from scratch—autodiff engine, neural networks, optimizers. Designed for understanding deep learning fundamentals with drop-in replacement capability.
Enterprise-grade RAG processing text, images, videos, and audio with evidence-based answer generation. Built with Vertex AI, Pinecone, and Gemini-1.5-Pro for auditable decision-making.
Suite of Chinese NLP tools including spaCy models, character decomposition library, and educational tokenizer. Widely adopted in industry and academia with strong community engagement.
Professional Experience
Baidu (Intelligent Vehicle Systems)
Architected production RAG system serving large-scale queries with high user satisfaction. Implemented hybrid retrieval combining vector and keyword search with advanced reranking, significantly improving accuracy and coverage through context-aware chunking strategies.
Built Agentic AI architecture with multi-agent orchestration and multi-turn dialogue. Fine-tuned large language models using parameter-efficient methods, achieving production-grade accuracy and low latency through rapid prototyping and A/B testing.
Geely (Automotive Manufacturer)
Led voice assistant migration from rule-based to deep learning NLU, significantly improving user satisfaction. Built MLOps pipeline for production inference, reducing latency and increasing throughput. Scaled across multiple automotive brands, powering over one million vehicles worldwide.
Alibaba (Ele.me Food Delivery)
Led engineering team building intelligent customer service system at scale, significantly reducing agent workload and delivering substantial cost savings. Pioneered neural semantic matching for intent understanding and response retrieval. Launched internal NLU platform adopted by multiple production teams.
Books
Xiaoquan Kong, Guan Wang • Packt Publishing, 2021 • [Amazon]
Production-grade chatbot development. Foreword by Alan Nichol (Rasa Co-founder & CTO).
Guan Wang, Xiaoquan Kong • BroadView Press, 2024 • [JD.com]
Traditional NLP to modern LLM applications. Foreword by Ines Montani (spaCy Co-founder).
Selected Publications
550+ citations, h-index: 7 • [Google Scholar]
Ren-Yan Duan*, Xiaoquan Kong*, et al. • PloS ONE, 2014
Min-Yi Huang*, Xiaoquan Kong*, et al. • PeerJ, 2016
* denotes equal contribution
Honors & Awards
- Google Developer Expert in Machine Learning, 2018 - Present
- TensorFlow Addons Codeowner, Led development of CRF module for NLP
- Baidu Chief AI Architect, First cohort, 2019
- Google Summer of Code Mentor, TensorFlow team, 2022
Community & Open Source
- GitHub: Active contributor with significant community engagement across multiple repositories
- Open Source: Key contributor to TensorFlow, spaCy, Rasa, Google Agent Kit
- Speaking: Regular speaker at technical conferences and workshops on AI/ML topics
Education
Duke University