Qiang Yang is a Fellow of the Engineering Institute of Canada and the Royal Institution of Canada, Chief Artificial Intelligence Advisor of Microfinance, Professor Emeritus of the Hong Kong University of Science and Technology, Chairman of AAAI-2021, and Former Chairman of the Board of Governors of the International Joint Committee on Artificial Intelligence (IJCAI). Donald E. Walker Distinguished Service Award for 2023. He is also the founding editor-in-chief of two top international journals, ACM TIST and IEEE TRANS on BIG DATA, and a Fellow of several international societies, including CAAI/AAAI/ACM/IEEE/AAAS, etc. His research interests include transfer learning and federated learning research and applications, and he has published books such as Transfer Learning, Federated Learning, Privacy in Computing, and Federated Learning in Action. Computing” and ‘Federated Learning in Practice’.

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.

Jun Zhu, Bosch Professor of AI at the Department of Computer Science, Tsinghua University, IEEE Fellow, Deputy Director of the Institute of Artificial Intelligence at Tsinghua University, Director of the Human Intelligence Laboratory at the Department of Computer Science, and Founder and Chief Scientist of ShengShu. He is mainly engaged in the research of basic theory and efficient algorithms of machine learning. He has been awarded the China Association for Science and Technology (CAST) QiuYue Outstanding Youth Award, the Scientific Exploration Award, the First Prize of Natural Science of the Chinese Computer Society, the First Prize of Natural Science of Artificial Intelligence of Wu Wenjun, and the Outstanding Paper Award of the International Conference of ICLR, etc. He has been selected for the National High-level Talent Program, the Young Scientist of the Chinese Computer Society, and the Chinese Pioneer of the MIT TR35.

Dr. Kenny Kefeng Li, founder and CEO of Beijing Digitforce Technology Co., Ltd., is a prominent leader in enterprise digital transformation within the retail and financial sectors, bringing extensive practical experience in digital transformation. Dr. Li previously held several key positions, including Vice President of JD Group, Chairman of the Technology Committee, and Head of Technology for JD Mall, where he led large technical teams of thousands and successfully spearheaded JD's digital transformation. He also served on the Executive Committee of Ping An Group and as CTO of Ping An Fintech, where he played a crucial role in developing user and data systems and the financial technology cloud platform, providing "technology + business" digital transformation solutions for financial institutions such as banks, insurance companies, and investment firms. Additionally, he was the General Manager of Mobile Baidu and a founding member of Baidu Cloud Computing, where he led Mobile Baidu to achieve over 100 million daily active users and contributed to the development of Baidu Cloud OS. Dr. Li is also a recipient of the Beijing Science and Technology Progress Award.

Yi Wu, Assistant Professor at Institute of Cross-Information Studies, Tsinghua University, was a full-time researcher at OpenAI before returning to China, with research interests in deep reinforcement learning, multi-intelligent body learning, inference models, human-computer interaction, etc. He received his Ph.D. degree from the University of California, Berkeley, USA, under the supervision of Prof. Stuart Russell in 2019; and he received his undergraduate degree from the Institute of Cross-Information Studies, Tsinghua University, China, in 2014. Experimental Class of Computer Science (Yao class), representative works include reinforcement learning generalizability early work Value Iteration Network, multi-intelligence body learning highest citation algorithm MAPPO/MADDPG, OpenAI multi-intelligence body hide-and-seek project, etc., and has also won the top conference NIPS2016 best paper award and the ICRA2024 best demo award finalist.

Dr. Nan Duan, Tech Fellow at StepFun, leads a team of researchers to build multimodal fundamental models centered on language and video. Previously, he was a Senior Principal Researcher and Research Manager of the Natural Language Computing team at Microsoft Research Asia (2012-2024). Dr. Duan is an Adjunct Doctoral Professor at the University of Science and Technology of China and Xi'an Jiaotong University, and an Adjunct Professor at Tianjin University. He focuses on natural language processing, code intelligence, multimodal base models, and intelligences.

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.

Ph.D. from the Department of Computer Science and Technology at Tsinghua University, selected for the 2023 MIT TR35 (China) list, and recipient of multiple honors including the National Scholarship and the Zhong Shimo Scholarship, the highest honor in Tsinghua's Department of Computer Science. Has published over ten papers at top-tier conferences such as ICML, NeurIPS, ICLR, and CVPR. Among these, the paper Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models was awarded the ICLR 2022 Outstanding Paper Award, a world-class academic accolade. This marked the first paper at this top-tier machine learning conference to win an award while being solely authored by a mainland China-based institution.

Yongbin Li graduated from Tsinghua University and is currently the head of the Dialogue Intelligence and Code Intelligence at Alibaba’s Tongyi Lab. His research focuses on large model technologies, such as Post-Training, Character Model, Code Model, and Agents. He is also responsible for the large model technologies of several products, including Tongyi Xingchen (character dialogue, emotional companionship, and digital humans), Tongyi Lingma (coding assistant and AI programmer), Tongyi Xiaomi (intelligent customer service), and Tongyi Tingwu (audio and video assistant). Since 2020, he has published over 90 papers in top international conferences (such as ICLR, NeurIPS, ICML, ACL, EMNLP, and CVPR) in the fields of pre-training, multimodality, dialogue/code, and large models. He has also served as an area chair for top international conferences such as ACL, NAACL, and WSDM.

Dr. Chunchao Guo is the 3D leader of Tencent Hunyuan. Dr. Chunchao has been engaged in advertising AI, generative big model research and landing work, has published more than ten papers in various journals and conferences, such as CVPR, and won 20 championships in domestic and international technical competitions, and has won the Outstanding Paper Award of the National Image Graphics Academic Conference in one work. Led the team to develop the industry's first batch of 3D-DiT models, which are applied to games, maps, social networking and other scenarios. He released the first open-source model that supports both text-generated and graph-generated 3D, which has gained wide attention both at home and abroad.

He received his undergraduate degree from the Department of Computer Science, Nanjing University, and his master degree from the Department of Computer Science, Shanghai Jiaotong University. He has several papers published in machine learning conferences such as ICML, NIPS, and KDD. He has worked in Alibaba Dharma Academy and Ali B2C retail business, responsible for algorithmic work in the direction of operational decision-making. Now he is responsible for the homepage recommendation algorithm in the community technology department of Xiaohongshu, and his main work includes cross-business traffic regulation and mixed scheduling, building a recommendation system around community interaction, crowd-based recommendation system and other directions.

He is in charge of the machine translation and big model business of Netease Yodao, undertakes a number of technical projects, provides AI technical support for Yodao Translator, Yodao Zhiyun, Dictionary Pen, etc., and serves nearly one hundred million users; he has published a number of papers in international top academic conferences in the field of NLP, and serves as a reviewer for top conferences such as ACL, EMNLP, etc., and owns a number of invention patents under his authorization.

Siyu Zhu is a researcher, long-time full professor and doctoral supervisor at the Institute of Artificial Intelligence Innovation and Industry, Fudan University, with research interests in video and 3D generative modeling. He has published more than 60 papers in international conferences and journals such as CVPR, ICCV, ECCV, and PAMI. During his Ph.D., he co-founded Altizure, a 3D vision company, which was later acquired by Apple Inc. and served as the Director of AliCloud Artificial Intelligence Lab from 2017 to 2023. He has served as ICCV/AAAI domain chair/program committee member, and won the Distinguished Engineer Award from the Chinese Computer Society.

Guang Liu, Technical Lead at BAAI's Data Research Team, directs the OpenSeek project. He is the architect behind the Aquila large language model series and the Infinity dataset family. His current research centers on Agentic Data Systems, innovating synthetic data generation for next-generation AI training.

Senior Machine Learning Specialist, Algorithm Engineering Direction at DEVO, mainly responsible for the R&D work related to DEVO's algorithm platform. He is responsible for the R&D of algorithmic platform in DEVO. He has been working in DEVO from 0 to 1 to build a universal large model training and inference platform. He used to work for Tencent, Ali and other big internet companies, and joined DEVO in 2022, focusing on big model related technology, including inference acceleration and application scenarios, and has published many high quality big model related articles in DEVO's technical public number, such as: using multi-Lora to save the cost of deploying big models, KubeAI big model inference acceleration practice, and DEVO's best practice of accessing the big model platform.

Duan Xiaohan, Trae IDE Architect at ByteDance, is committed to the practice of big language model in R&D engineering, building AI coding assistant based on big language model; meanwhile, he is also committed to advancing the process of IDE cloud-based, integrating with the R&D infrastructure platform, and providing a one-stop intelligent R&D experience for developers.

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.

Dr. Jiaqing Liang, a young associate researcher at the School of Big Data, Fudan University, focuses on cognitive intelligence research in knowledge graph and big models. He has published more than 50 papers in top conferences and journals such as TKDE, AAAI, etc. The knowledge graph and big model application platform developed by him has been invoked more than 1.7 billion times, and he owns nearly 20 patents. He was awarded the first place in Information Extraction Competition of Language and Intelligent Technology Competition. The Chinese big model CuteGPT developed by CuteGPT has been applied in many companies. He has won many honors such as Gold Medal in ACM-ICPC Regional Competition, TopCoder Open Top 150 in the world, and Scientific and Technological Progress Award in Wu Wenjun Artificial Intelligence Award.

He graduated from Chinese Academy of Sciences with a master's degree in 2018, and has been engaged in research in the direction of code intelligence since graduation, focusing on code model training and application landing. He joined Racer in 2024, and is responsible for the algorithm research and development of KwaiCoder big model Pre-training, Post-training and Code Agent, etc. At present, his self-developed code big model is better than the open source SOTA base model. Recently, he focuses on the exploration and implementation of cutting-edge LLM algorithms, and constantly breaks through the performance bottleneck of the code base model.

He graduated from Peking University in 2017, and has practical experience in NLP, search and recommendation fields. Since joining Baichuan Intelligence, he has been engaged in text pre-training, SFT, code agent and multi-modal pre-training, and recently focused on the exploration of algorithms for omni-modal models, especially the end-to-end model for speech. Currently, the open source Baichuan-Omni-1.5 multimodal model has achieved the best balance of text capability, image/video comprehension, speech comprehension and generation effect.

Dr. Haosheng Zou is currently a senior expert of 360 Smart Brain algorithm, leading the open source projects Light-R1 and 360-LLaMA-Factory. he graduated his PhD from Prof. Zhu Jun's group in TSAIL at Tsinghua University, and his undergraduate degree is from the Department of Electronics at Tsinghua University. He was a reinforcement learning researcher at Mihalyu and Fourth Paradigm before Big Model, and is the author of the TF version of tianshou.

Kai Qiu is a senior researcher at Microsoft Research Asia, graduated from University of Chinese Academy of Sciences. His research interests include image and video generation, post-training of large multimodal models, and reinforcement learning of large language models. He has published several articles in conferences and journals such as CVPR, ICCV, AAAI, ACM Multimedia, Pattern Recognition and so on. The related research results have been used in several Microsoft products, including Bing Ads, Windows Copilot, and so on. He is a reviewer for CVPR, ICCV, ECCV, ACM MM, AAAI, IJCV and other conferences and journals. The related technologies have been granted Chinese and US patents.

Xinbing Liang, DeepWisdom algorithm researcher, The first author of the OpenManus project, MetaGPT open source core contributor, and one of the authors of the paper Data Interpreter /Self-Supervised Prompt Optimization. He received his undergraduate degree from Guangzhou University and postgraduate degree from East China Normal University. His main research direction is AI Agent, and he has rich practical experience in the field of intelligent bodies, and is committed to promoting the open source and popularization of AI technology.

Liang Hu is a professor and doctoral director of School of Computer Science and Technology, Tongji University. He was selected as one of the National Overseas High-Level Young Talents and Shanghai Overseas High-Level Talents. He received his PhD degree in Computer Application Technology from Shanghai Jiaotong University and his PhD degree in Analytics from the University of Technology Sydney (UTS), Australia, respectively. He has presided over and participated in a number of national research projects. His research interests include artificial intelligence, recommender systems, data science, privacy computing, big models, and cross-disciplinary integration of next-generation intelligence technologies. He has published more than 100 papers, many of which are groundbreaking in the field. He serves as a program committee member of many high-level international conferences on AI (IJCAI, AAAI, ICDM, CIKM, KDD, CVPR, ICML, NeurIPS, etc.), and a reviewer of more than ten famous international journals, including ACM CSUR, IEEE TKDE, ACM TOIS, IEEE TPAMI, etc. He has also served as a member of the program committee of the International Conference on Artificial Intelligence (IJCAI), and a reviewer of more than ten famous international journals. He hosted two IEEE ICAACE 2023/ICAACE 2024 international conferences in 2023 and 2024, and served as the conference chair. In addition, Prof. Liang Hu serves as an executive member of the Special Committee on Granular Computing and Knowledge Discovery of the Chinese Society for Artificial Intelligence, and an executive member of the Special Committee on Collaborative Computing of the Chinese Computer Society. He is also the visiting professor of China Ship Nine Academy, the chief expert of the expert workstation of Shenlan Artificial Intelligence (Shanghai) Co., Ltd. and the chief expert of the expert workstation of Shanghai 263 Communication Co., Ltd. He actively promotes the process of combining industry, academia and research and the proposed methodology has been transformed and landed to be applied in the actual projects in different fields such as e-commerce, healthcare, taxation, finance and transportation and solved some of the core problems.

Yanzhi Wang is currently an associate professor and faculty fellow at Dept. of ECE at Northeastern University, Boston, MA. He received the B.S. degree from Tsinghua University in 2009, and Ph.D. degree from University of Southern California in 2014. His research interests focus on model compression and platform-specific acceleration of deep learning applications. His work has been published broadly in top conference and journal venues (e.g., DAC, ICCAD, ASPLOS, ISCA, MICRO, HPCA, PLDI, ICS, PACT, ISSCC, AAAI, ICML, NeurIPS, CVPR, ICLR, IJCAI, ECCV, ICDM, ACM MM, FPGA, LCTES, CCS, VLDB, PACT, ICDCS, RTAS, Infocom, C-ACM, JSSC, TComputer, TCAS-I, TCAD, TCAS-I, JSAC, TNNLS, etc.), and has been cited above 18,000 times. He has received six Best Paper and Top Paper Awards, and one Communications of the ACM cover featured article.

Ying Wen is a long term faculty track associate professor and PhD supervisor at the School of Artificial Intelligence, Shanghai Jiaotong University. His research interests involve multi-intelligent body learning, reinforcement learning and the application of game theory in it. He received his Ph.D. and research master's degree from the Department of Computing, University College London, UK, in 2020 and 2016, respectively. He was selected as one of the Shanghai Overseas High-level Talents, and presided over the topics of the National Key Research and Development Program as a responsible person, and the Shanghai Young Science and Technology Talents Yangfan Program. More than 40 of his research results have been published in ICML, NeurIPS, ICLR, IJCAI, AAMAS and other top international conferences in related fields, and he has won the best system paper award in CoRL 2020 and the best paper award in AAMAS 2021 Blue Sky Track. He has served as a PC member or reviewer for many consecutive years for prestigious international conferences/journals such as ICML, NeurIPS, IJCAI, AAAI, IROS, ICAPS, Operational Research, etc.

Xiao Han, Founder and CEO of Jina AI. Founded in 2020, Jina AI is headquartered in Berlin, Germany with R&D centers in San Francisco, Beijing and Shenzhen. The company specializes in deep learning-based search technology development, providing cutting-edge open source pedestal models for enterprise-class search, retrieval augmented generation (RAG) and intelligent agent systems. The company's core product line consists of three cores: Reader, Embeddings and Reranker. These products excel in multilingual processing and multimodal systems and have gained wide recognition and adoption in the international market. Prior to founding Jina AI, Xiao Han worked as a researcher at Tencent AI Lab. His published academic papers have received over 10,000 citations on Google Scholar.

D. degree from Harbin Institute of Technology-Microsoft Research Asia, was awarded the title of “Microsoft Scholar” in 2015, and was the single champion of Blizzard Challenge 2023 International Speech Synthesis Competition, and is now responsible for the research, development and implementation of speech recognition and synthesis, voice interaction, and music technology in the whole scenario of rednote. R&D and landing. FireRed, a comprehensive solution for speech/music technology based on big model. He has published dozens of papers in conferences and journals in the field of speech, such as ICASSP, INTERSPEECH, IEEE TASLP, and SPEECH COMMUNICATION.

He has been working in Ant Group for ten years, and his main research directions include: logic learning, causal learning, automatic learning, big model, etc. He has published more than 70 papers in NeurIPS, ICML, KDD, SIGIR and other conferences. He has led and participated in many core platforms and projects within Ant, participated in the development of Ant Bailing big model, and led the development of big model offline reasoning framework flood : https://github.com/alipay/PainlessInferenceAcceleration. Received ccf2020 Award of Excellence in Scientific and Technological Progress, Wu Wenjun 2023 First Prize of Scientific and Technological Progress and so on.

Co-founder of InfinFlow and a seasoned entrepreneur, has for years spearheaded Infrastructure R&D across search engines, database engines, cloud infrastructure, and big data architecture. With extensive AI expertise in advertising, recommender systems, and computer vision (notably developing InsightFace, a top facial recognition algorithm), he has successfully led the digital transformation of multiple large enterprises and robustly supported internet services boasting over 10 million daily active users and 200 million daily dynamic search requests.

He is currently the General Manager of Data Intelligence Products at Digitforce. Previously, he was the Senior Quantitative Operations Leader at a top-tier internet company. With years of experience in data mining and user operations strategy design in the retail and financial industries, he has built full-chain digital operations platforms for several large enterprises, covering goal setting, data diagnosis, strategy design, and optimization review.

He is a member of the framework group of ByteDance AI development platform, graduated from Peking University, focusing on the design and implementation of large model application development frameworks, and is one of the core developers of the Eino framework (https://github.com/cloudwego/eino).

Shuai Lu, a researcher at Microsoft Research Asia, graduated from Peking University in 2021. His research area is code intelligence and natural language processing, and he is committed to automating software development with big model technology to empower program developers. His main research interests are code generation, code big models, program automation verification, etc. His research results have been published in NeurIPS, ICLR, ACL, ICSE, FSE and other academic conferences, with more than 5000 Google Scholar citations.

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.

Ancheng Wu , CTO of Jianyu Manufacturing, a technical expert with more than 20 years of R&D experience, has authored "Neural Network and Deep Learning", "Deep Learning Algorithms in Practice", "The Secret of Trading - Making the First Bucket of Money with Algorithms" and other books. He has deep technical accumulation and wide technical stack in the fields of artificial intelligence, big data and deep learning; he has different application system landing experience in the algorithmic direction of text, speech, recommendation and image; he owns 11 patents in algorithmic category; he has won the first place in reading comprehension competition Squad2 single model; in the field of big model, he has led a series of important projects, including ChatGPT-like big language base model training and optimization, as well as applications in finance, insurance, cultural creation and Chinese medicine, etc. He has led the team to complete the training of language models from 1.3B to 13B, and carried out the fine-tuning of business data from 30B to 63B large models.

Zhiyi Liu, a leading AI scientist in China, researcher of Shanghai Collaborative Innovation Center for Social Governance of Artificial Intelligence, and researcher of Qingyuan Research Institute of Shanghai Jiaotong University, has been deeply researching and practicing AI for more than ten years, including intelligent computing, spatial intelligence, and super AI alignment. He is a member of the AI Ethics Committee of the Chinese Society for Artificial Intelligence (CSAI) and a member of the Special Committee on Embodied Intelligence (SCEI), the Executive Director of the Center for Computational Law and Artificial Intelligence Ethics at Shanghai Jiao Tong University (SJTU), an invited researcher at the Antai Center for AI and Marketing Research at SJTU, and the Director of the Special Committee on AI Ethics at the Shanghai Open Source Technology and Information Association (SOSTIA). In 2024, he was selected by Forbes China as one of the “Top 10 AI Influencers”, and in 2024, he was selected as one of the Huawei Cloud Developer Experts. He is an ethical expert of IEC/SMB/SEG12, a member of the technical committee of the 4th IEEE International Conference on Computer Communication and Artificial Intelligence (CCAI 2024), an expert of the National AI Standard Overall Group, a member of the Trusted AI Expert Committee of the AIIA Consortium, an expert member of the Shanghai Association of Artificial Intelligence Technology, and an expert member of the Shanghai Artificial Intelligence Technology Association. He is an expert member of Shanghai Artificial Intelligence Technology Association. His academic monographs include Intelligent Economy, Digital Economics, and Enlightenment of Intelligence: General Artificial Intelligence and Consciousness Machines, etc. He has published more than ten Chinese and English monographs and translated many monographs of overseas scholars, and his works have been selected as the “New Development in China” by Springer Nature Publishing Company. His work has been selected for the Springer Nature Publishing “China New Development Award” (2023).

The technical leader of the Little Raccoon family of SenseTime Technology, leading the whole process of the application landing of the Little Raccoon family, has a deep understanding of the AI application landing and rich practical experience. With the code model as the product AI capability base, the Raccoon family on the one hand provides AI programming assistant products for the native developer scenario, Code Raccoon; on the other hand, it also breaks the circle of the code capability as an AI tool, expands the boundary of the product capability, and provides AI productivity applications for the office crowd, Office Raccoon. This also makes the Little Raccoon family become a highly distinctive AI productivity series products in China.

Dr. Haosheng Zou is currently a senior expert of 360 Smart Brain algorithm, leading the open source projects Light-R1 and 360-LLaMA-Factory. he graduated his PhD from Prof. Zhu Jun's group in TSAIL at Tsinghua University, and his undergraduate degree is from the Department of Electronics at Tsinghua University. He was a reinforcement learning researcher at Mihalyu and Fourth Paradigm before Big Model, and is the author of the TF version of tianshou.

Joined Kingsoft Office in 2019. Currently, he is the person in charge of AI application algorithms in Kingsoft Office R&D center division, and has rich practical experience in algorithm landing in recommender system, document structuring and other aspects. Currently responsible for some AI application R&D and landing work within Kingsoft Office WPS AI text, form and presentation.

Yiming Chen, Postdoctoral Fellow of Institute of Automation, Chinese Academy of Sciences, Beijing & Visiting Scholar of McGill University, Canada, his main research interests are NLP, computer vision, edge computing and so on. He won the champion of CCF (China Computer Federation) Action Recognition Algorithm Competition 2022, the champion of Kaggle International Algorithm Image Caption Matching Competition, and was invited to make a special sharing at ICLR2022, the top conference of Artificial Intelligence Class A. He has been invited to participate in one national level oceanic project, and has completed one national level oceanic project. He has participated in and completed one national level ocean project. He has published more than 10 international top academic papers and more than 20 authorized patents. He has served as a tutor for special projects at Tsinghua University, and as an extracurricular tutor for Northeastern University, New Oriental, Taitze Technology, and many other colleges and universities (companies).

Specialized in R&D efficiency, he has more than 10+ years of practical experience in developer tool building, enterprise R&D collaboration platform architecture and implementation. In Ali, he has led the construction and commercialization of the self-developed code hosting platform 0-1, led the team to explore the field of code intelligence and Cloud IDE, and pushed the transformation and landing of the Cloud Effect 5.0 all-platform public-proprietary integration architecture, and is also the initiator and promoter of Alibaba's P3C open source code statute detection tool. He is also the initiator and promoter of Alibaba's P3C open source code statute detection tool. Currently, he is mainly committed to exploring the effective landing practice of AI Agent in TONGYI Lingma‌ products, and further improving the intelligent coding experience of developers.

Baojian Zhou is a Young Associate Researcher at School of Big Data, Fudan University.He received his Ph.D. degree from the State University of New York at Albany in 2020, followed by a postdoctoral fellowship at Stony Brook University (2020-2021). He has long been engaged in theoretical research work on large-scale graph machine learning and data mining, especially on dynamic graph representation learning and acceleration algorithms on graphs. In recent years, he has achieved a number of research results in the research directions of anomaly subgraph detection, graph structure constraint optimization, graph machine learning, and anomaly detection for dynamic graph representation learning on large-scale graph data mining. The research results have been published in more than 20 papers in international data mining and machine learning conferences, such as ICML, NeurIPS, KDD, IJCAI, AAAI, ICDM, CIKM, and TKDE.

Xuan Xia, graduated from Shanghai Jiao Tong University with a PhD in 2017. Now he is an associate researcher at Embodied Artificial Intelligence at Shenzhen Institute AIRS, and a high-level talent in Shenzhen. He mainly conducts research on embodied intelligence, multimodal learning, defect detection, and generative modeling. He has presided over the National Natural Science Foundation of China, the Natural Science Foundation of Guangdong Province, and the China Postdoctoral Science Foundation, and participated in many national, provincial, and municipal foundation projects as well as several joint projects with enterprises. He has published more than 20 papers and applied for more than 10 invention patents.

Zhangchi Feng, the core developer of LLaMA Factory, has a master degree from Beijing University of Aeronautics and Astronautics. He has published many papers in ACM MM, KDD and other conferences. He is the recipient of National Scholarship and Outstanding Graduate of Beihang University. He has been invited to deliver keynote speeches at KDD, China Networking Conference and other top academic conferences.

Ganqu Cui, a young scientist in Shanghai Artificial Intelligence Laboratory, graduated from the Department of Computer Science of Tsinghua University with a Ph.D., supervised by Associate Professor Liu Zhiyuan. His research interests include large language model alignment and reinforcement learning techniques. He has published more than ten papers in ICML, NeurIPS, ICLR, ACL, KDD and other top international AI conferences and journals, with more than 8000 citations in Google Scholar.

Currently, he is responsible for the development of related large model application technologies in ebay advertising department, including SFT, RFT, RLHF, RAG, Inference, online agent system, etc. He has many years of research and practitioner experience in the field of deep learning and large model. He has many years of experience in the field of deep learning and big models, and has published many papers in international machine learning conferences, and served as a reviewer for AAAI, KDD, and other international conferences.

He graduated from Shanghai Jiaotong University with a master's degree, specializing in AI. He used to work for Tencent, mainly focusing on the development of customized AI inference engine and engineering landing, and now works for eBay machine learning platform department, focusing on the construction of eBay cloud native AI inference platform. As the main leader, he led the development of LLM zero code deployment solution based on triton server, LLM auto scale solution based on k8s, and LLM benchmark automation tool. He is always committed to promoting the practical application of AI technology, and strives to create greater value for enterprises through technological innovation.

Zhenxiao Luo is a Sr. Staff Software Engineer at Pinterest, responsible for big data real-time processing engine, monitoring platform, and big model data preprocessing. Prior to joining Pinterest, Mr. Luo worked at Cloudera, Uber, Twitter, and Facebook, where he was responsible for the development and operation of big data engines and machine learning platforms. Zhenxiao Luo is a Presto committer, Presto Technical Steering Committee member, and graduated from Fudan University with a bachelor's degree, and graduated from University of Wisconsin Madiso with a PhD on leave.

CAMEL AI core member, Eigent AI engineer. He is the core developer and maintainer of two 10,000 star open source projects, camel and owl, and has worked for Ping An Technology, Central Statistics Office of Ireland, and BASF China Digital Center.

D. program at the School of Electronic Engineering, Beijing University of Posts and Telecommunications (BUPT). His research interests focus on training-free controlled image editing generation and AI image forensics. His papers are included in CCF-A conference journals such as ACM MM and IEEE TIP, and he won the Replay Grounding Track in CVPR2022 SoccerNet workshop competition. He has experience in fine-tuning the domain of large language model pendant, and has deep research experience in signal processing, image processing, representation learning, natural language processing and cue word engineering. Currently working as an intern in the Multimedia Cognitive Learning Lab at China Telecom Artificial Intelligence Lab, his research interests currently involve lens-controllable video generation, generative image forensics and AI governance.