I am a Researcher at Alibaba (Beijing) specializing in Ranking & Recommendation Systems, Supply Chain Optimization, and LLM & Agent Optimization. My work centers on designing and deploying robust, large-scale recommendation engines and intelligent agent workflows that power high-concurrency, complex commercial ecosystems. Driven by a passion for pushing the frontiers of Deep Learning and Generative AI, I explore how large language models and autonomous agents can revolutionize user understanding and industrial decision-making. My research and engineering expertise spans LLM alignment, parameter-efficient fine-tuning, and multi-agent collaboration, alongside traditional paradigms like multi-task learning, cross-domain transfer learning, and large-scale revenue optimization.

I hold an M.S. in Computer Architecture from the Institute of Computing Technology (ICT), University of Chinese Academy of Sciences (UCAS), which instilled in me a strong foundation in high-performance systems and computational efficiency, and a B.S. in Software Engineering from Shandong University (SDU). To stay at the vanguard of scientific discovery, I actively engage with the global research community as a regular reviewer for premier AI, information retrieval, and data mining venues, including KDD, RecSys, and SIGIR. My career is defined by cultivating a symbiotic relationship between academic rigor and industrial scale. I excel at translating complex, theoretical breakthroughs into robust, production-grade software, while simultaneously leveraging real-world production challenges to inspire novel algorithmic formulations. This closed-loop approach allows me to consistently deliver measurable improvements in user experience and business efficiency, securing sustainable, long-term technological advantages.

我是阿里巴巴（北京）的研究员，专注于排序与推荐系统、供应链优化以及大语言模型（LLM）与智能体（Agent）优化。我的工作聚焦于设计和部署鲁棒的大规模推荐引擎与智能体工作流，为高并发、复杂的商业生态提供支撑。我对深度学习和生成式 AI 的前沿探索充满热情，致力于研究大语言模型和自主智能体如何革新用户理解与工业决策。我的研究与工程能力涵盖 LLM 对齐、参数高效微调、多智能体协作，以及多任务学习、跨域迁移学习和大规模收入优化等传统范式。

我获得了中国科学院大学计算技术研究所（ICT, UCAS）的计算机体系结构硕士学位，这为我在高性能系统和计算效率方面奠定了坚实基础，以及山东大学（SDU）的软件工程学士学位。为保持在科学前沿的敏锐洞察，我积极参与全球学术社区，担任 KDD、RecSys、SIGIR 等顶级 AI、信息检索和数据挖掘会议的审稿人。我的职业生涯致力于构建学术严谨性与工业规模之间的共生关系：一方面，我擅长将复杂的理论突破转化为稳健的生产级系统；另一方面，我善于从真实生产环境的挑战中提炼出新颖的算法方案。这种闭环方法使我能够持续在用户体验和商业效率方面带来可衡量的提升，确保可持续的长期技术竞争优势。