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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Head of the AI Reasoning Group and Principal Research Manager of the Systems Group at Microsoft Research Asia. His research interests focus on the pretraining and applications of large language models. He has published over 80 papers at top international conferences, including ICLR, NeurIPS, ICML, OOPSLA, COLM, ACL, EMNLP, NAACL, WWW, SIGIR, IJCAI, AAAI, and CIKM. His work Rho-1 received the NeurIPS 2024 Best Paper Runner-Up Award, and Autoverus received the OOPSLA 2025 Distinguished Artifact Award. The generative models he developed have been widely deployed in Microsoft’s advertising platforms and Bing Search. He has led several major research projects, including Poolingformer, RikiNet, DKMR², and APOLLO, which have achieved multiple first-place rankings on benchmarks such as Google NQ, Google TyDiQA, CommonGen, and FinQA. He has also served as an Area Chair or Senior Program Committee member for EMNLP 2021 and 2022, IJCAI 2023 and 2024, ACL 2023, and LREC-COLING 2024.

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.