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.

Dr. Huang Fei has long been engaged in research and development in natural language processing and artificial intelligence. He currently serves as Chief Scientist and CAIO of AI at Honor Devices. Previously, he was Head of the Tongyi Natural Language Intelligence Lab at Alibaba and Vice President of Alibaba Cloud, as well as an adjunct professor at Zhejiang University. He led teams in the development of the Tongyi large language model system (including AliceMind, PLUG, Qwen, Embedding, DeepResearch, etc.), achieving human-surpassing results in machine reading comprehension, vision-language question answering, and Chinese language understanding, work that was recognized with the SAIL Award at the World Artificial Intelligence Conference. Building on the Tongyi Qianwen model, he guided his team to focus on industry applications, enabling software development (Tongyi Lingma / Qoder), role-based dialogue, office productivity, intelligent judicial solutions, and other industry use cases. Dr. Huang has published over 300 papers in top AI conferences and journals, holds more than 100 international and domestic patents, and has over 50,000 citations on Google Scholar with an H-index of 86. He has served as area chair and journal editor for ACL, TACL, and other academic venues, and as a member of large model expert committees. He has also shared insights and technology perspectives at numerous industry conferences and government-organized seminars. He earned his Ph.D. in Computer Science from Carnegie Mellon University and previously worked at IBM Research and Facebook, where he contributed to and led the development of machine translation systems that help 2 billion Facebook users overcome language barriers.

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.

Chief Product Officer and Senior Vice President at Muxi Integrated Circuit (Shanghai) Co., Ltd., and Visiting Professor at ShanghaiTech University. Expert in artificial intelligence, chip design, and electronic systems, as well as in the development of intelligent computing centers. Holds dozens of personal invention patents and has 20 years of experience in system and chip development, with extensive expertise in large-scale computing chips, GPU computing clusters, AI projects, electronic system design, and domestic and international market operations. Has led multiple high-profile benchmark projects both in China and abroad. In recent years, responsible for the top-level and architectural design of several national large-scale technology projects, intelligent computing/supercomputing centers, and smart city initiatives. Possesses project experience in deploying cutting-edge intelligent technologies across industries, including large GPU computing chips, ultra-large cluster construction, edge AI computing chips, in-vehicle computing platforms, brain-inspired chips, system integration devices, and digital twins.

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.

Bryce Adelstein Lelbach is the Chief Architect at NVIDIA, where he leads the CUDA C++ core libraries team, contributes to the development of the NVC++ compiler, and oversees the technical roadmap for NVIDIA’s compute compilers and libraries. He has over a decade of experience in programming languages, compilers, and software library development. Bryce has long been dedicated to advancing programming language standardization. He serves as an officer of ISO/IEC JTC1/SC22/WG21, the ISO C++ Standards Committee, and chairs the C++ Library Evolution Working Group (LEWG). Previously, he chaired the C++ Tooling Study Group (SG15) and the Library Incubator Working Group (SG18). He is also the chair of INCITS PL22, the U.S. Programming Language Standards Committee. Within the C++ Committee, Bryce has been deeply involved in the design and development of key features such as concurrency primitives, parallel algorithms, executors, and multidimensional arrays. He is also one of the founding developers of the HPX parallel runtime system.

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.

Previously worked in the Middleware Technology Department’s High Availability Architecture Team, where he led the design of key systems such as gray release and geo-distributed active-active architecture, and participated multiple times in Double 11 stability assurance, gaining extensive experience in high-availability systems and architecture. He currently leads the technical architecture and product direction of the AI programming tool Qoder, including the development of products such as the CLI and QoderWork.

Kai Chen is a Leading Young Scientist at the Shanghai Artificial Intelligence Laboratory and Head of the Large Model Center. He has published over 70 papers in top-tier AI conferences and journals, with more than 34,000 citations on Google Scholar. He has been recognized with honors such as the Shanghai Oriental Talent Program (Leading Talent) and Shanghai Young Academic Leader. He leads the development of the InternLM large model, taking on key technical challenges, and has established the “Sinan” evaluation system, which is widely adopted by leading large model companies and research institutions. Previously, he served as the head of the computer vision open-source algorithm system at OpenMMLab, where he made significant contributions to the open-source ecosystem and built strong international influence.

Han Vanholder is a Senior Director of Product Management at NVIDIA, where he is a product lead for NVIDIA Cloud Accelerator (NCX) — the open-source software enablement layer that helps cloud partners build and operate AI infrastructure at scale. His work sits at the intersection of AI Hardware, cloud platform software, and the partner ecosystem, translating NVIDIA's leading AI factory experience into deployable software for cloud providers. He works closely with NVIDIA customers, partners, and engineering teams that are building AI Cloud factories.       Han brings over 15 years of experience building foundational platforms for accelerated computing. Before NVIDIA, he served as Director of Product Management at Google, where he led compute infrastructure products.  He began his career in Silicon Valley at NVIDIA, working across GPU computing and data center platforms, and launching NVIDIA's inference optimized GPU product line. A native of Belgium, Han studied MSc. EE at the KU Leuven and led mobile media and wireline communications products at NXP semiconductors in Belgium, The Netherlands, and Singapore before moving to the San Francisco Bay Area.

Leye Wang is a tenured associate professor at the School of Computer Science, Peking University, and a Boya Young Scholar. He also serves as Deputy Director of the Institute of Software at Peking University and Deputy Secretary-General of the CCF Technical Committee on Pervasive Computing. He has been selected for a national-level young talent program. His research has long focused on mobile crowd sensing and computing, with recent work centered on agent-oriented software engineering. He has published over 100 papers in leading international conferences and journals, with more than 9,000 citations in total, including over 20 papers cited more than 100 times.

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.

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.

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.

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 focuses on the implementation and innovation of artificial intelligence (AI) and cloud computing solutions. With more than 15 years of experience in the cloud computing and internet industries, including roles at Tencent and ByteDance, he has long been dedicated to refining products and solutions. Throughout his career, he has successfully led the go-to-market of multiple products, demonstrating a strong ability to integrate cutting-edge technologies with customer business value to drive tangible business growth.

PhD in Physics from the University of Oxford. Former Postdoctoral Researcher at the Visual Geometry Group (VGG) at the University of Oxford and Senior Software Engineer at Google, where he worked on the large-scale industrial deployment of computer vision and agent technologies. He is currently a Senior Algorithm Expert at Ant Group and the Head of Post-Training Algorithms for the Bailing Multimodal Large Model. As a core contributor, he participated in building the 100B-parameter fully multimodal open-source large model Ming-flash-omni. He is currently focused on post-training for multimodal foundation models, logical reasoning, and next-generation agent technologies.

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 R&D at the Beijing Academy of Artificial Intelligence (BAAI). He holds a Ph.D. from the Chinese Academy of Sciences and completed his postdoctoral research at Peking University. He currently leads the development of several key components within FlagOS, an open-source unified AI software stack, including the large model training-inference integrated framework FlagScale, the unified communication library FlagCX, and the unified plugin ecosystem FlagOS-UniDev. He was among the first in the industry to propose practical, industry-deployable technical solutions for cross-chip heterogeneous training and heterogeneous inference for large models. His research focuses on distributed systems and performance optimization in the fields of artificial intelligence, high-performance computing (HPC), and scientific computing. He previously worked at Huawei and Baidu, where he contributed to the development of core technologies for large-model systems. In 2016, he was part of the team that won China’s first ACM Gordon Bell Prize. He has published more than ten papers in top international conferences and journals, holds multiple domestic and international patents, and has participated in the development of national and international standards related to 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.

Peiyu Wang is the Multimodal Tech Lead at Kunlun Wanwei. His main research areas include multimodal understanding and generation, video generation, and world models. He has participated in releasing a series of open-source models including skywork-r1v (multimodal reasoning), unipic (unified understanding and generation), matrix game (world model), and skyreels (video generation). At the time of release, these models were SOTA open-source models in their respective fields. They have accumulated over one million downloads on Hugging Face and have received widespread recognition from the open-source community. He has deep theoretical knowledge and extensive practical experience in multimodal understanding and generation, video generation, and world models.

He received his bachelor’s and master’s degrees from Huazhong University of Science and Technology and the National University of Singapore. He previously served as L3/L4 Autonomous Driving Team Lead at BMW, Head of AI Lab and Digitalization at Great Wall Motors, and CTO of Caresoft Global. During his time at automotive companies, he led the development of multiple L2–L4 autonomous driving platforms, vehicle vision and voice products, and intelligent cockpit systems, and also led large model pretraining and embodied intelligence research projects at the Great Wall Motors AI Lab. At Caresoft, he led a global engineering team of 2,500 people delivering data and engineering services to more than 20 OEMs, with industry practice focused on large-scale engineering and industrial deployment of autonomous driving and large models in the automotive sector. He currently works at UQI, where he leads product development for industrial mobile robots, L4 autonomous logistics vehicles, and humanoid robots, as well as research and engineering of embodied intelligence algorithms centered on large models.

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.

Wei Wang, Director of the Open-Source Technology Committee at Singularity Intelligence Research Institute, Head of the Open-Source Governance Standards Group at the Electronic Standardization Institute of the Ministry of Industry and Information Technology, Secretary-General of the UN Advisory Committee on Open-Source Innovation, Professor at East China Normal University, and Distinguished Member of the China Computer Federation (CCF). He led the development of China’s first set of open-source governance standards, with research focused on open-source governance and evaluation. He has published over 100 papers in top-tier conferences and journals including ICSE, WWW, and ACL, and has been recognized with national-level innovation talent programs, a second prize in national teaching achievements, and the Special Prize for Shanghai Open-Source Innovation Excellence.

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.

Huang Ning is currently the Head of Product R&D at SiliconHeart Technology (aiXcoder), leading the end-to-end design and development of the aiXcoder intelligent software development system. He graduated from the School of Mathematical Sciences at Peking University and previously led the compiler development of the data-driven programming language “ByLang.” Since then, he has been deeply engaged in the field of “AI + Software Development,” leading teams to develop a variety of general-purpose software engineering agents, including intelligent programming and intelligent testing. He is dedicated to exploring the future of programming languages, program design, and software engineering in the AI era.

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.

Liu Yong, Founder and CTO of Zhongneng Shibei, is a distinguished practitioner and pioneer in China’s industrial intelligence sector. With over two decades of deep expertise in industrial software and intelligent systems, he has led his team to develop the Shibei Industrial Intelligent Operating System—one of the earliest foundational platforms for industrial intelligence in China. He has participated in the formulation of multiple national and industry standards for power sector intelligence, led several benchmark projects in building intelligent systems for the power industry, and stands as an outstanding representative of scientific and technological innovation driving the development of new productive forces.

Wang Haoyu, Professor and PhD Supervisor at the School of Cyber Science and Engineering, Huazhong University of Science and Technology; Young Changjiang Scholar of the Ministry of Education; Huazhong Distinguished Scholar; and Director of the OpenHarmony Technology Club at Huazhong University of Science and Technology. His research focuses on the security of emerging software systems. In recent years, he has published over 130 CCF-A papers and has received multiple provincial and ministerial-level awards, including the First Prize of the Beijing Science and Technology Progress Award.

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.

Yuxiang Ma, Head of Algorithms at the Enterprise Credit Department of Ant Group, with 10+ years of experience leading algorithm initiatives for comprehensive financial scenarios both domestically and internationally. Expertise includes credit risk algorithms for individual and enterprise scenarios, business world models, enterprise assistant agents, AI infrastructure performance optimization, graph models, and device fingerprinting.

Former Head of Algorithms for Ant Group’s Zhixiaobao and Maxiaocai, where he led the development of the core algorithm system for an intelligent financial advisor serving hundreds of millions of users. He was also a founding core member and chief architect of the Baidu App, deeply involved in building Baidu’s mobile ecosystem from the ground up to hundreds of millions of users. With over 15 years of hands-on R&D and architecture experience in AI, he has led teams to win five international AI competition championships and has published more than 20 top-conference papers and patents. During his time at Intel, the SE-OS technology solution and source code he designed and implemented were procured by the U.S. National Security Agency. He is currently focused on algorithm and agent innovation for AI-native applications in healthcare and finance, aiming to deeply integrate cutting-edge large model technologies with specialized domains to build highly reliable and deployable AI-native products that drive industrial intelligence transformation.

DeerFlow project developer with hands-on experience in AI agent application development. Member of the Apache Software Foundation, and initiator of Apache Local Community Beijing.

Researcher and Technical Expert at the Alibaba Cloud Apsara Lab, and a Ph.D. in Computer Science from the Department of Computer Science and Technology at Tsinghua University. His research focuses on high-performance inference systems, large language models, and distributed machine learning training. He is a core contributor and maintainer of features such as PD separation and pipeline parallelism in the SGLang community. He is also a core member and maintainer of the Mooncake community.

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.

Hao-Yang Huang is Director of the Exploration Research Institute at JD.com and Head of the Multimodal Foundation Model Team. He has published more than 40 papers in top AI journals and conferences. Previously at Microsoft Research Asia, he led the development of multilingual and multimodal foundation models used in Microsoft Bing and Microsoft Translator, including Unicoder covering 100 languages and M3P, the world’s first multilingual multimodal pre-training model. His team won first place in the WMT21 Large-Scale Multilingual Machine Translation competition. In 2024, he led the development and open-sourcing of the 30B StepVideo series of video generation models (Step-Video-T2V and Step-Video-TI2V).

Bo Tang, Head of Applied Algorithms at MemoryTensor (Shanghai) Technology Co., Ltd., primarily responsible for the R&D of MemOS and ClawForce products. Previously led the development of the NewsCopilot multi-agent integrated production engine for Xinhua News Agency, deployed during the Two Sessions. Formerly with Microsoft Research Asia, Alibaba, and Meituan; engaged in industry-academia collaborations with New York University and Sun Yat-sen University. Long-term research focus on natural language processing, reinforcement learning, and safe reinforcement learning, with 40+ publications in top-tier international conferences including ICML, NeurIPS, ICLR, and ACL.

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.

Head of Model Performance Optimization at OmnInfer and committer of the MTP SIG. He graduated from the University of Science and Technology of China and the University of Chinese Academy of Sciences. After joining Huawei, he has worked for over a decade in computer networking and AI infrastructure, gaining extensive engineering experience in large model inference optimization. He has been deeply involved in performance optimization for multiple open-source models as well as the Pangu large model on the Ascend platform, supporting high-performance inference services and RL rollout.

A Technical Expert in the Smart Hardware Division at Youdao (a subsidiary of NetEase), and a core developer of the Youdao Longxia project. He is currently responsible for the front-end technology development and management of Youdao’s smart hardware business. Over the past year, he has participated in the development of several smart hardware products, including the Youdao Dictionary Pen, Youdao Q&A Pen, and Youdao Listening Companion. He has also helped deploy multiple AI-powered educational features on Youdao smart devices, such as the XiaoP Teacher assistant, video-based question answering, and an AI-driven mistake notebook. Previously, he led the front-end architecture development and team management for products such as the Youdao Dictionary and Youdao Human Translation service. He has extensive experience in client-side development technologies and in bringing AI applications into real-world products.

Zeyao Han, PhD from the Department of Information and Electronic Engineering at Zhejiang University, is Head of the Application Ecosystem at Moore Threads. He has long been engaged in chip and wireless communication system architecture, AI infrastructure, and AIGC and agent development, focusing on intelligent agent applications on domestic computing platforms, ecosystem incubation and enablement, as well as education and research solutions. He previously served as a wireless communication pre-research system engineer and team lead at Huawei Shanghai Research Institute, architecture lead for the first-generation Kirin SoC at HiSilicon, Assistant Professor and Lab Dean at the School of Microelectronics at Shanghai Jiao Tong University, Senior Manager at Alcatel-Lucent, and Senior Director at Bell Labs in the United States. He also has years of entrepreneurial experience in AI education products and applications of AIGC and large models. He is the author of books including AIGC from Introduction to Practice and AIGC and Intelligent Agent Development in Practice.

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.

Inference Framework Architect at Kunlunxin, with over ten years of experience in software development for AI inference. He specializes in large model inference optimization, operator development, and framework construction. He led the full-stack adaptation, optimization, and deployment of Wenxin Yiyan large model inference on Kunlunxin hardware, and has extensive hands-on experience in industrial-scale AI inference deployment.

Tencent (Hunyuan 3D) Researcher. Completed Ph.D. at the University of Tokyo under the supervision of Professor Tatsuya Harada. Research interests focus on the intersection of 3D computer vision and artificial intelligence, with particular emphasis on 3D object/scene generation, multimodal large models, and world models.

Currently serving as the Head of MiniMax Open Platform and Senior Director of Solutions. Since joining MiniMax in 2023, she has led and delivered multiple large model deployments across real-world industry scenarios, building extensive hands-on experience in LLM engineering and AI agent applications. Prior to MiniMax, Wen Feng worked at ByteDance as an Internet Industry Solutions Expert, where she focused on applying AI technologies to diverse business contexts and designing scalable solutions, developing strong technical insight and execution capabilities for real-world deployment.

Head of Developer Products and Ecosystem at StepFun; Executive Member of the Open Source Technical Committee at CCF; Technical Committee Mentor at OpenAtom Foundation.

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).

Alibaba Cloud Cloud-Native Solutions Architect; Maintainer of the Hiclaw project. The team is responsible for open-source projects such as Higress and Nacos. He leads the implementation of microservices middleware solutions, focusing on API gateways, Nacos, and service governance in cloud-native applications. In the AI era, he spearheads solution development for agent-based systems, covering AI gateways, AI observability, the AgentScope development framework, Nacos, HiMarket, and Agent Sandbox—providing foundational services to support customers in transforming toward AI-native applications.

Tracked and discovered 30+ zero-day vulnerabilities in LLM-related inference and application frameworks; conducted in-depth research and implemented intelligent content safety data flywheels for practical LLM security compliance; translated and published books on AI red teaming; certified instructor at multiple institutions.

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.

Has long been involved in the design, iteration, and implementation of AI applications and workflow products. He has led multiple Dify product version upgrades and the evolution of core capabilities, continuously advancing AI product practices for enterprise scenarios. Previously, he worked on related products at MetaGPT and is frequently invited to share insights with enterprises and community audiences.

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.