Mr. Li Jianzhong, Senior Vice President of CSDN, Chief Technologist of Boolan, and Chairman of the Global Machine Learning Technology Conference, has extensive experience and in-depth research on software architecture and product innovation. He has rich experience and in-depth research on software architecture, product innovation, and artificial intelligence. In recent years, he mainly researches on the application of artificial intelligence methodology in the software field based on large language models, and proposes the “ParaShift Cube” for technological innovation, which has attracted a lot of attention from the industry in the related research and speeches.

Junlin Zhang is a director of the China Society for Computational Linguistics and holds a Ph.D. from the Institute of Software, Chinese Academy of Sciences. He currently serves as the Chief Scientist and Head of AI R&D at Sina Weibo. Previously, he was a senior technical expert at Alibaba, leading a new technology team. He is also the author of the technical books *This is a Search Engine: A Detailed Explanation of Core Technologies* and *Big Data Daily Knowledge: Architecture and Algorithms.

Wang Bingning is a Distinguished Researcher and Head of AI Algorithm Research for WeChat Search at Tencent, and formerly Head of Pretraining at Baichuan Intelligence. He earned his Ph.D. from the Institute of Automation, Chinese Academy of Sciences, with research focused on question answering systems and large language models. He previously served as a senior researcher at Sogou and Tencent, with extensive experience in large-scale generative models. He led the creation and release of several large-scale Chinese QA datasets, including ReCO, ComQA, ChiQA, and T2Ranking, as well as the Baichuan series of pre-trained models. The models he led have received over 10,000 stars on GitHub and accumulated more than 20 million downloads on Hugging Face. He has published 12 first-author papers at top international AI and NLP conferences such as ACL, SIGIR, and AAAI, and received the CIKM 2021 Best Paper Runner-Up Award. His doctoral dissertation, “Key Technologies for Machine Reading Comprehension,” won the 2019 Outstanding Doctoral Dissertation Award from the China Chinese Information Processing Society. He also serves as an Executive Committee Member of the Youth Working Committee of the China Chinese Information Processing Society.

Li Yongbin graduated from Tsinghua University and serves as Head of the Qoder and Tongyi Lingma models, as well as an Algorithm Scientist at Tongyi Lab. His research focuses on large model technologies, including post-training, code models, character models, and AI agents. In the AI coding domain, he led the development of the industry-leading Qwen-Coder-Qoder large model and helped build products such as Qoder and Tongyi Lingma. He is also responsible for large model development across multiple application areas, including AI social companionship (Qwen-Character, Tongyi Stardust), AI customer service (Intelligent Customer Service, Tongyi Xiaomi), and AI-powered data analysis. In recent years, he has published over 100 papers at top international conferences, including ICLR, NeurIPS, ICML, ACL, EMNLP, and CVPR. His work has received more than 6,500 citations on Google Scholar, with an H-index of 37. He has also served as an Area Chair for leading international conferences such as ACL, NAACL, and WSDM.

Senior Technical Expert at Alibaba, currently serving as Technical Lead for Qoder Quest and CLI, specializing in AI Coding and developer tool innovation.

Wu Baodong is Vice President of Technology at Infinigence AI. He received his Ph.D. from the Institute of Computing Technology, Chinese Academy of Sciences, and completed his postdoctoral research at Tsinghua University. He is a recipient of the ACM SIGHPC China Outstanding Doctoral Dissertation Award. His long-term research focuses on high-performance computing, parallel computing, cluster scheduling, and large-model training systems. He has published more than ten papers in leading international conferences and journals such as SC, TPDS, IPDPS, and ICDCS, and received a Best Paper Nomination at ICDCS 2020. Previously, at SenseTime, he led the end-to-end development of an AI computing platform from the ground up, achieving unified management and scheduling of over 20,000 GPUs. He currently leads the core technology R&D for Infinigence AI’s one-stop AI platform, where he has built China’s first unified scheduling platform for heterogeneous, geographically distributed, and cross-domain computing resources. The platform manages more than ten types of chips and over 25,000 PFLOPS of compute capacity, and has enabled large-scale deployment of key technologies including fault-tolerant large-model training systems, distributed inference services, and task failure prediction.

Wang Jiaqi is a Research Director at the JD Exploratory Research Institute and Head of the Multimodal Understanding Foundation Model R&D Team. His research focuses on multimodal foundation models for understanding, multimodal generative models, and the construction of benchmarks and datasets in related fields. He has published more than 60 papers in top-tier international journals and conferences, with over 20,000 citations on Google Scholar. Multiple papers have been selected as most influential papers at major international conferences. He has served as an Area Chair for leading conferences including NeurIPS, ICLR, ICML, and CVPR.

Chengqiang Lu is currently Head of AI Search Generation Algorithms at Xiaohongshu. He received his Master’s degree from the University of Science and Technology of China. His main research areas include large model pre-training/post-training, Agents, RAG, and AI4Sci. He has previously worked at Tencent QLab, Alibaba Qwen Team, and Xiaohongshu Search, focusing on algorithm research and real-world applications. He has published dozens of papers in top conferences and journals such as NeurIPS, KDD, AAAI, and ACL, with around 6,000 citations on Google Scholar.

Dr. Liu Shujie is a Principal Researcher at Microsoft Research Asia (MSRA) Hong Kong. He joined MSRA Beijing in July 2012 after earning his Ph.D. from the School of Computer Science and Technology at Harbin Institute of Technology, and transferred to MSRA Hong Kong in October 2024. His research spans spoken language processing, multimodal large language models, and medical AI, with a focus on improving quality of life through artificial intelligence. His work received the IEEE 2025 SPS Best Paper Award. He has published more than 100 papers in top journals and conferences in natural language processing and speech processing, co-authored the book Machine Translation, and contributed to the book Introduction to Artificial Intelligence. He has achieved multiple first-place results in international evaluations for natural language and speech processing, and has served as a reviewer and area chair for numerous international conferences. His research has been successfully integrated into a range of Microsoft products, including Microsoft Translator, Skype Translator, Microsoft IME, XiaoIce, and Microsoft Speech Service.

Head of Developer AI Products at Tencent Cloud, Chief Product Manager, and Senior Technical Product Expert at Tencent. He is responsible for the Tencent CodeBuddy product and has previously led products such as Cloud Studio and Coding DevOps. He served as Product Director at Teambition, Senior Engineer and Architecture Engineer at Autodesk, Development Lead for SuccessFactors HCM, Senior Database Engineer at Sybase, and Core Developer of PowerDesigner. He has extensive industry experience in software architecture design, product management and project engineering management, team agility, and AI-driven R&D efficiency improvement.

Malin is a Technical Director at SenseTime and currently serves as the frontend technical lead for the Raccoon (Xiaohuanxiong) product line. He has long focused on product engineering practices for AI Native Applications. As one of the core technical leaders, he led the development of the Office Raccoon AI PPT online editing system and built an HTML-to-editable-PPT rendering engine. His work provides a scalable and reliable closed-loop interaction framework for the engineering implementation of generative AI products.

He has many years of experience in Silicon Valley and Wall Street, and has worked as an algorithm expert for Uber and Bloomberg, focusing on the research and application of supply chain management, pricing strategy optimization, dynamic pricing, causal inference, and large language models. He is now the Director of Retail Algorithms at Jingdong, responsible for supply chain management strategy optimization, pricing algorithm optimization, price strategy development, and price ecosystem governance. His team won the 2024 INFORMS Prize, the first Asian team to win the prize in the 34 years of its existence.

Yulong Ao is the Head of AI Framework Development at BAAI, a Postdoctoral Fellow at Peking University, and holds a Ph.D. from the Chinese Academy of Sciences. He currently leads the development of the large-model training and inference framework FlagScale and the unified communication library FlagCX, both key components of the open-source unified AI software stack FlagOS. He pioneered industry-ready solutions for heterogeneous large-model training and inference across diverse compute architectures. His long-term research focuses on distributed systems and performance optimization in artificial intelligence, high-performance computing (HPC), and scientific computing. Previously, he worked at Huawei and Baidu, contributing to core technologies in large-model systems. In 2016, he jointly received China’s first ACM Gordon Bell Award. He has published over ten papers in top international conferences and journals, holds multiple domestic and international patents, and has participated in the formulation of national and international standards for operator interfaces and communication libraries.

Huang Jia is an AI researcher at a Singapore-based research institute, specializing in large language models, agent systems, and production-grade AI engineering. A technical author and systems-oriented thinker, he focuses on transforming complex AI capabilities into architectures that are designable, reusable, and deliverable in real-world environments. He is the author of several technical books, including Hands-on AI Agent Development with Large Models, RAG in Practice: Building Applications with Large Models, and GPT Illustrated: How Large Models Are Built. Currently, his research centers on Agent design patterns, MCP/A2A protocols, and the engineering of Agent Skills, with the goal of advancing AI from “capability demonstrations” to fully systematized engineering practices. His open-source course, Claude Code Engineering in Practice, provides a systematic exploration of four core extension mechanisms in agent frameworks (Sub-Agents, Skills, Hooks, and MCP). Through in-depth source code analysis of projects such as OpenClaw, he has proposed a comprehensive framework of 21 Agent design patterns spanning six cognitive dimensions.

Dr. He Wanqing is currently the Vice President of Qingcheng.ai. He previously served as Senior Director at Biren Technology, where he was responsible for Turnkey systems and application optimization. His past roles include Chief Engineer at Intel DCAI, Head of High-Performance Computing at Alibaba Cloud and Senior Technical Expert, CTO of 360 Cloud, and R&D Manager at Motorola and Guodian Power. Dr. He graduated from Shanghai Jiao Tong University in 1999 and has devoted the past 25 years to HPC parallel optimization, cloud computing, and AI application performance tuning. He has also invested significant time in fostering industry-academia-research collaboration within the China Computer Federation (CCF). He has served as a CCF Executive Committee Member, Standing Committee Member of the CCF High Performance Computing Technical Committee, Vice Chair of CCF YOCSEF Headquarters, Vice Chair of ACM Hangzhou, and Chair or Committee Member of the Enterprise Track of the CNCC 2022, 2023, and 2024 Technical Forums. He has been awarded numerous honors, including CCF Honorary Member, CCF Distinguished Speaker, and CCF Outstanding Contribution Award. He has authored three books on parallel development and cloud computing, translated and published five books on the internet, popular science, and engineering technology, and received the 40th Anniversary Outstanding Contribution Award from the Publishing House of Electronics Industry as well as the 2024 Best Translator Award from Cheers Publishing.

Ma Xiaoteng is Chief Scientist at Macaron AI and Director of Mind Lab. His work focuses on training personalized intelligent agents driven by real interactive experience, as well as building reinforcement learning infrastructure platforms. He earned his Ph.D. in the Department of Automation at Tsinghua University, where he also completed his postdoctoral research. He has published more than 30 papers in the field of reinforcement learning, with over 1,400 citations on Google Scholar.

Xu Chenren is a Boya Distinguished Associate Professor (tenured track) at Peking University, Assistant Dean of the School of Computer Science, and Deputy Director of the Institute of Network and High-Efficiency Computing. He received his Ph.D. from Rutgers University in 2014. He previously served as a postdoctoral researcher and research scientist at Carnegie Mellon University, a visiting professor at Keio University in Japan, and a visiting scholar at AT&T Shannon Lab and Microsoft Research. His research focuses on super-perceptual intelligence (embodied intelligent IoT and multimodal-driven scientific and engineering intelligence). He has led projects including the National Science Fund for Excellent Young Scholars, key programs of the National Natural Science Foundation of China, and major national R&D initiatives from the Ministry of Science and Technology. His work on high-performance perception and interconnected systems for mobile IoT has received the CCF First Prize for Technological Invention (2025, ranked 1st), six best paper–type awards at MobiCom, MobiSys, SenSys, and UbiComp, the DAMO Academy Young Fellow Award, Huawei Top Ten Inventions Award, the Okawa Foundation Research Award (Japan), and a gold medal at the Geneva International Exhibition of Inventions. His technologies have been deployed at scale in systems such as Huawei HarmonyOS devices and Alibaba logistics platforms. He currently serves as Associate Editor of ACM IMWUT, Editorial Board Member of Nature Partner Journal Artificial Intelligence, General Chair of UbiComp 2026, Program Chair of UbiComp 2025, Steering Committee Member of UbiComp, General Chair of MobiSys 2025, and has served on the program and organizing committees of SIGCOMM, MobiCom, and NSDI. He is also the Outreach Ambassador of ACM SIGDX (Digital Transformation), Secretary-General of ACM SIGBED China Chapter, and a board member of the Carnegie Mellon University Beijing Alumni Association.

Taofeng Xue is a Staff Researcher at Meituan. He received his master’s degree from the Institute of Software, Chinese Academy of Sciences and joined Meituan as a top-tier talent under the “Beidou” Program. At the forefront of large models and autonomous agents, he led— as first author — the industry-leading **EvoCUA (Evolving Computer Use Agents)** project. In January 2026, EvoCUA achieved a 56.7% success rate and ranked No.1 on the OSWorld open-source leaderboard. Following the full open-source release, the model quickly surpassed 12K+ downloads, and its technical report topped the Hugging Face Daily Paper rankings. Before focusing on foundation model innovation, he accumulated over five years of hands-on experience in large-scale search, advertising, and recommendation systems. He previously served as the Ranking Lead for community search at Meituan Dianping. Combining cutting-edge research vision with strong engineering execution, he has led teams to win the championship in multimodal reasoning at ICCV 2025 and secure global runner-up in multimodal recommendation at RecSys Challenge 2024. He has also published multiple papers at top-tier conferences including ICCV, RecSys, SIGIR, and CIKM. In addition, he is a well-known technical blogger under the name “Mr. Mushroom,” with over 50,000 professional followers, continuously contributing high-value AI insights to the open-source community.

Yin Zhen is a Full-time Mentor at Shanghai Institute of Creative Intelligence and a Professor and PhD Supervisor at the School of Electronic and Information Engineering, Tongji University. He is a recipient of the National High-Level Young Talent Program. Before 2022, he was an Alexander von Humboldt Fellow at the Max Planck Institute for Intelligent Systems in Germany. He received his Ph.D. in Mechanical Engineering from McGill University and his bachelor’s degree in Mechanics from Fudan University. He is the Principal Investigator of the “Everything is Alive” Lab, with research focusing on bio-inspired modular and swarm robotics, intelligent design, and advanced manufacturing. His research has been published as first or corresponding author in top journals and conferences such as Science and Nature Communications, and has been featured by Science, PNAS, CCTV News, Physics World, and other major scientific and professional media outlets.

Passionate about open-source software and communities, with over 20 years of experience in product development, architecture design, and team management across multiple domains including Linux operating systems, distributed systems, storage and high availability, virtualization and cloud computing, containers and cloud-native technologies, and AI infrastructure. Previously held roles such as Chief Architect, Technical Director, and China Technical Lead at renowned multinational corporations and leading domestic ICT enterprises. Additionally, as an independent contributor, initiated open-source projects and successfully promoted them internationally. Currently serves in the CTO Office at Red Hat Asia Pacific, leading the incubation and promotion of AI inference-related open-source communities such as vLLM and llm-d, implementing AI technology strategies, and prioritizing the innovative application and deployment of 100% open-source AI products and solutions across vertical industries.

Responsible for the product strategy, development, and deployment of the intelligent development assistant **CodeFlicker**, dedicated to enhancing engineering efficiency, experience, and developer well-being through AI-powered R&D tools. With extensive hands-on experience in the AI DevOps domain, previously worked at Ant Group and Tencent. Led the end-to-end creation (from 0 to 1) of cloud-native and AI-native R&D products, building intelligent development platforms and successfully driving large-scale adoption in enterprise environments.

He holds a Ph.D. from the Institute of High Performance Computing at the Department of Computer Science, Tsinghua University. He has published dozens of papers in leading international conferences in computer science, including FAST, SIGMOD, SC, ASPLOS, ICDE, ICPP, and Cluster, as well as in international journals such as TPDS and TKDD. He has led one key project under a major national research program. He led the development of the Jiuyuan Intelligent Graph Database for Inference (JYGraph). Built on the domestic Phytium platform, the system achieved top-tier performance in the internationally recognized LDBC benchmark. He also led the development of the Jiuyuan Intelligent Big Data Machine system, which adopts a “storage-for-compute” paradigm to reduce computing costs while improving inference performance. The system has significantly outperformed existing solutions across multiple academic benchmarks and real-world business scenarios.

Baidu front-end architect, head of Baidu front-end CMC, head of Baidu technical organisation committee for web direction. 2023 Participated in Baidu's intelligent development tool Comate's IDE end architecture, model enhancement, etc., and has rich experience in the application of large models in software development such as renewal, generation, Q&A and so on.

Chen Guangda, Head of Planning and Control Algorithms for NetEase Fuxi Robotics. Senior Engineer (Associate Professor Level), Ph.D. in Computer Science from the University of Science and Technology of China, Postdoctoral Fellow at Zhejiang University's School of Control Science and Engineering. Authored multiple papers in premier robotics conferences and journals including ICRA, IROS, and RAL. Specializes in intelligent construction machinery, leading the end-to-end development and deployment of NetEase Lingdong's excavator planning-control system and unmanned loader algorithm system. His technical achievements have resulted in over 50 patent applications (with 12 granted), covering key areas such as autonomous planning, environmental perception, and human-machine collaboration. The “Unmanned Loader System for Mixing Plants” he developed achieved China's first fully unmanned operation across the entire workflow, with a labor efficiency ratio exceeding 120%. It has been successfully deployed in multiple large-scale infrastructure projects nationwide, driving the intelligent transformation of construction machinery.

Algorithm Engineer at Xiaohongshu, currently the lead of the open-source project OpenStoryline. Focused on the design and deployment of conversational video-editing agents and automated creative workflows, dedicated to transforming complex video production processes into interactive intelligent systems. Has published papers at leading conferences such as ICCV and ACM Multimedia. Previously worked on AIGC-related research, including image and video stylization as well as diffusion model acceleration.

Yang Yang, AI R&D Manager for Amazon Web Services OpenSearch in China, is responsible for implementing machine learning capabilities in the open-source search and analytics engine OpenSearch. He also serves as maintainer for multiple plugins within OpenSearch, including ml-commons and neural. The opensearch-neural-sparse series of models he spearheaded has consistently ranked first on Hugging Face's sparse retrieval model leaderboard for several consecutive years. The team's research interests include semantic search, generative intelligent analysis, and search engine infrastructure.

Senior Researcher at Microsoft Research Asia (MSRA) in the AI Inference Group, focusing on natural language processing, large language models, and inference technologies, with a mission to advance the systematic deployment of research from fundamental algorithms to real-world applications. He received both his bachelor's and Ph.D. degrees from Beijing Institute of Technology, with his doctoral dissertation awarded the 2023 Excellent Ph.D. Dissertation Award by the Chinese Information Processing Society (CIPS). He has published over 40 papers in top international conferences and journals in natural language processing and machine learning. His research has been recognized with the runner-up for the Best Paper Award at NeurIPS 2024 and has been applied in core products such as Microsoft Bing Search. He also serves as an Area Chair for leading international conferences including ACL, ICML, NeurIPS, and EMNLP.

Huang Haoyang is the Head of the Multimodal Foundation Model Team at the Image and Multimodal Laboratory, Exploratory Research Institute, JD Group. He has published more than 30 papers in top-tier AI journals and conferences. He previously led the development of multilingual and multimodal foundation models at Microsoft Research Asia, with applications in Microsoft Bing Search and Microsoft Translator. He spearheaded the release of Unicoder, covering 100 languages, and M3P, the world’s first multilingual multimodal pre-trained model, and achieved first place globally in the WMT21 Large-Scale Multilingual Machine Translation competition. In 2024, he led the development of the 30B-parameter StepVideo series of video generation foundation models (Step-Video-T2V and Step-Video-TI2V), which were subsequently open-sourced.

Focusing on large language models (LLMs) and multimodal domains, I spearheaded the development of Kingsoft Office's government-grade large model pre-training framework and played a key role in the development of the Monkey series models and the implementation of multimodal training. I built Kingsoft Office's image translation capabilities from scratch, achieving end-to-end layout understanding and multilingual translation pipelines. I am committed to deeply integrating large model technology with real-world office scenarios to drive the large-scale adoption of intelligent office products.

Han Zeyao received his Ph.D. from the Department of Information and Electronic Engineering at Zhejiang University, where he completed a combined bachelor’s–Ph.D. program. During this period, he participated in joint research projects with the ICCAD Lab at the Department of Computer Science, Tsinghua University, and the VLBI program of the Chinese Academy of Sciences (Shanghai). He previously served as a wireless communication pre-research system engineer (corporate postdoctoral researcher) and team lead at Huawei Shanghai Research Institute, and as the lead architect of the first-generation SoC architecture for HiSilicon’s Kirin chips. He was also an Assistant Professor and Lab Dean at the School of Microelectronics, Shanghai Jiao Tong University, a Senior Manager for system development and protocol standards at Alcatel-Lucent, and a Senior Director at Bell Labs in the United States. In addition, he has many years of entrepreneurial experience developing AI education products and working on AIGC and LLM-related technologies. He is currently the Head of Application Ecosystem at Moore Threads, focusing on upper-layer application development for AI Infrastructure (including Agent Infrastructure), as well as ecosystem incubation, enablement, and solutions for education and research. In the field of artificial intelligence, he has authored *AIGC: From Introduction to Practice* and *AIGC and Agent Development in Practice*. He is currently co-authoring *Practical Guide to General-Purpose GPU Computing: From Environment Setup to Large Model Applications* and *Agent Casebook: Education, Research, Healthcare, and Industry*.

Tang Feihu, Senior R&D Engineer and Developer Relations Lead at Moonshot AI. Former Google engineer, ACM/ICPC Asia Regional Gold Medalist, Microsoft “Programming Beauty” Challenge Champion, and champion of the first Wanxiang Lab Token Economy Design Competition.

Li Yuan is an R&D Engineer and Developer Relations Lead at MiniMax. He graduated from Hong Kong University of Science and Technology and has extensive experience in algorithm engineering at leading internet companies, with a long-standing focus on applying AI technologies to efficiency-driven scenarios. Since joining MiniMax in 2023, he has been deeply involved in the development of key products including Hoshino, MiniMax Agent, and the company’s internal “Intern” project. He led early iterations and optimizations of the Agent product, laying a solid foundation for Agent 2.0, and has actively promoted the open-source of large models and the MiniMax Agent ecosystem. He oversees the end-to-end open-source launch of MiniMax M2.5, which generated tens of thousands of developer applications on its first day. Beyond building the MiniMax developer ecosystem, he shares cutting-edge technical insights through his social media account “Your Yuan AI,” actively advancing the adoption and development of AI technologies across the industry.

Technical Expert at Tsingmicro Intelligent with over 20 years of experience in communications and computing technologies. He previously held key technical roles at Huawei and other leading technology enterprises. He specializes in system-level co-design and compute–chip integration, and served at Huawei as both a Level-19 Technical Expert in System Collaboration Algorithms and a Level-19 Technical Expert in Compute–Chip Integration. He has received numerous top honors, including the President’s Individual Award, Hero Individual Award (equivalent in prestige to a Gold Medal Award), Major Technological Innovation Award, and Gold Medal Team Award. He has contributed to more than 60 domestic and international patents and led breakthroughs in multiple chip architecture innovations. Currently, his work focuses on AI chip hardware–software co-design and reconfigurable super-node optimization. Through system-level innovation, he advances real-world technology deployment, pioneers new computing paradigms, and supports the evolution of the broader industry ecosystem.

Head of Technology for Baidu PaddleOCR and PaddleX. He is responsible for the development of vision and OCR models and has contributed to the development of more than 80 models in the PaddlePaddle PP series, including PP-LCNet, PP-OCR, PP-YOLO, and RT-DETR. He has also participated in multiple computer vision projects within the company and holds over 30 domestic and international patents. He has won more than 10 gold medals or championships in international AI competitions, including several CVPR and ICCV workshop contests, and has been invited to give talks. In 2024, his project“Endangered Species AI Guardian 2.0”* won the **2025 Edison Award for Best New Product (Silver Award).

Yang Ke is a Technical Expert at Approaching AI and a core contributor to the open-source project Mooncake. He earned his Ph.D. from the Institute of High-Performance Computing, Department of Computer Science, Tsinghua University, and his bachelor's degree from Beijing University of Posts and Telecommunications. He was a finalist in the 2013 ACM-ICPC World Finals and has published first-author papers in top systems conferences such as SOSP and ASPLOS. His research interests include distributed systems, parallel computing, and AI infrastructure.

Ming Zhou, Founder and CEO of Lanzhou Technology, is a world-renowned NLP expert with around 100 ACL publications. 110 H-Index. He serves as Vice President of the Computer Society of China. He was the President of the International Society for Computational Linguistics and Vice President of Microsoft Research Asia. Ming Zhou received his Ph.D. from HIT in 1991 and then taught at Tsinghua University. he joined Microsoft Research Asia in 1999 and led NLP research for a long time. in 2021, he founded Lanzhou Technology, which is engaged in the research and development of lightweight macromodels and new-generation NLP products, and was awarded the top prize of the Beijing HICOOL (2021) Entrepreneurship Competition. He is a Fellow of ACL, Fellow of Chinese Computer Society and Fellow of Chinese Society of Artificial Intelligence, and a PhD supervisor at five universities.

The primary research areas focus on foundation models, machine learning, and other artificial intelligence technologies, with a commitment to technological innovation and real-world applications in these fields. Academically, he/she has published over 100 papers at top-tier AI conferences, holds an H-index of 52, and has received three international Best Paper Awards as well as 41 granted U.S. patents. In the fields of cloud computing and big data, as a member of the early core technical team, he/she participated in the development of Feitian, the only domestically self-developed cloud computing operating system, laying the foundation for its large-scale commercial deployment. As one of the founding members of AI initiatives at Alibaba and Ant Group, he/she played a key role in leading and building multiple large-scale AI projects, including personalized recommendation systems for the Double 11 shopping festival, the AI platform PAI, the graph learning system AGL, AI-driven risk control systems, and the intelligent transformation of Alipay. Under his/her leadership, the team ranked first in four international algorithm competitions and received numerous prestigious awards, including the First Prize of the Ministry of Education Science and Technology Progress Award, the Grand Prize of Scientific and Technological Research Achievements from Shaanxi Higher Education Institutions, the CCF Science and Technology Progress First Prize, the Wu Wenjun Artificial Intelligence Science and Technology Progress First Prize, the China Institute of Electronics Science and Technology Progress First Prize, and the Zhejiang Provincial Science and Technology Progress First Prize, significantly strengthening core technological competitiveness.