大Z，Meta/Facebook人工智能研究院研究员及高级经理，研究方向为深度强化学习，表示学习和优化。曾获得2021年国际机器学习大会（ICML）杰出论文奖提名（Outstanding Paper Honorable Mentions)，及2013年国际计算机视觉大会（ICCV）马尔奖提名（Marr Prize Honorable Mentions）。 2013-2014年在Google无人驾驶团队任软件工程师。2005年及08年于上海交通大学获本硕学位，2013年于美国卡耐基梅隆大学机器人研究所获博士学位，围棋开源项目ELF OpenGo项目中研究及工程负责人和第一作者。

Junbo Zhao is a Assistant Professor at Zhejiang University, participating in the 100-Young Professor Program. He earned his Ph.D. in Computer Science from New York University in 2019 under the mentorship of Turing Award laureate Yann LeCun. From 2016 to the end of 2018, He worked as a contracted researcher at Meta Foundational AI Research (formerly Facebook AI Research - FAIR). He also worked at NVIDIA in 2015 and contributed to the development of the first end-to-end self-driving car project, which was showcased at GTC 2017 by Jensen Huang. Junbo Zhao has published numerous highly-cited papers in top-tier journals and conferences . He also serves as an area chair or a reviewer for many top-tier AI conferences, including NeurIPS, ICML, ICLR, CVPR, ACL, and ICCV, as well as a few AI+X journals. He has received multiple awards, including the Zhejiang Province Science and Technology Progress First Prize, two WAIC SAIL Awards, and the cover figure of Forbes 30-under-30 in 2022.

郑伟，南开大学统计与数据科学学院教授，国家级青年人才，南开大学百名青年学科带头人，传染病溯源预警与智能决策全国重点实验室成员。蛋白质预测结构文件存储格式ModelCIF的国际标准制定委员会委员。该委员会成员还包括诺贝尔化学奖得主DeepMind课题组、诺贝尔化学奖得主华盛顿大学David Baker教授课题组。 研究领域为基于深度学习及统计能量函数的生物分子及其互作的结构预测，郑伟主持开发的C-I-TASSER、C-QUARK、D-I-TASSER、DMFold等蛋白质单体结构预测算法、蛋白质-蛋白质互作复合物结构预测算法、核酸-核酸互作复合物结构预测算法、蛋白质-核酸复合物结构预测算法、生物分子多构象预测算法等，累计获得被誉为“蛋白质结构预测领域的奥林匹克竞赛”的国际赛事（CASP）的十项冠军，领先包括AlphaFold2、AlphaFold3在内的全球80余个学术界及工业界的课题组。5次受邀在世界蛋白质结构预测大赛赛后国际会议、世界生物医药与人工智能大会做特邀报告。累计在Nature Biotechnology、Nature Methods、Nature Communications、Nature Protocols、Science Advances、Nature Computational Science、Nucleic Acids Research、PNAS等高水平SCI期刊发表文章50余篇。据Google Scholar记录，郑伟的相关研究成果已累计获得3400余次引用。研究成果受诺奖得主、Nature、纽约时报等媒体报道，阅读量超过百万次。担任SCI期刊Molecules杂志特约编辑及Nature Communications、Nature Machine Intelligence、Nature Computational Science等SCI期刊审稿人。郑伟主导开发的算法已经累计服务了超过100个国家的近10万名用户。主持并参与了多个国家级、天津市级人才项目及重点交叉项目。

赵昊，清华大学电子工程系学士/博士，曾任英特尔中国研究院研究员和北京大学联合博士后。赵昊博士专注于几何与认知层面的场景理解及其在机器人中的应用，于计算机视觉与机器人国际期刊和会议(CVPR,ICCV,ECCV,IJCV,CVIU,ISPRS,T-IP,T-MM,NeurIPS,ICLR,RA-L,ICRA,IROS)上发表近30篇论文。赵昊博士是清华大学最大的机器人社团“天空工场”的创始人和负责人之一，曾参与孵化10余家高新技术创业公司。赵昊博士曾获得LSUN, Holistic3D, LID等多项学术竞赛冠军

仉尚航现为北京大学计算机学院任长聘系列助理教授（研究员），博士生导师。于2018年博士毕业于美国卡内基梅隆大学，后于2020年初加入加州大学伯克利分校 Berkeley AI Research Lab (BAIR) 从事博士后研究。其研究方向为开放环境泛化机器学习理论与系统，同时在计算机视觉和类脑智能方向拥有丰富研究经验。在人工智能顶级期刊和会议上发表论文50余篇，并申请5项美中专利。荣获世界人工智能顶级会议AAAI’2021 最佳论文奖，该工作曾列世界最大学术源代码仓库Trending Research 榜单第一，受到十余家媒体报道推广，开源代码被访问7万余次、2600余次Star。作为编辑和作者由Springer Nature出版英文书籍《Deep Reinforcement Learning》，至今电子版全球下载量超十二万次，入选中国作者年度高影响力研究精选，并出版中文译本。Google Scholar引用数3100次，h-index 23, i10-index 35。于2018年入选美国“EECS Rising Star”，曾获得Adobe学术合作基金，Qualcomm创新奖提名。获国际人脑多模态计算模型响应预测竞赛第一名，NeurIPS 2021 Visual Domain Adaptation 竞赛第三名。曾多次在国际顶级会议NeurIPS、ICML上组织Workshop，多次作为国际顶级期刊和会议的审稿人或程序委员，担任AAAI 2022/2023 高级程序委员。 Dr. Shanghang Zhang is a Tenure Track Assistant Professor at the School of Computer Science, Peking University. She has been the postdoc research fellow at Berkeley AI Research Lab (BAIR), UC Berkeley. Her research focuses on OOD Generalization that enables the machine learning systems to generalize to new domains, categories, and modalities using limited labels, with applications to autonomous driving and robotics, as reflected in her over 50 papers on top-tier journals and conference proceedings (Google Scholar Citations: 4321, H-index: 28, I10-index: 38). She has also been the author and editor of the book “Deep Reinforcement Learning: Fundamentals, Research and Applications” published by Springer Nature. This book is selected to Annual High-Impact Publications in Computer Science by Chinese researchers and its Electronic Edition has been downloaded 150,000 times worldwide. Her recent work “Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting” has received the AAAI 2021 Best Paper Award. It ranks the 1st place of Trending Research on PaperWithCode and its Github receives 3,300+ Stars. Shanghang has been selected to “2018 Rising Stars in EECS, USA”. She has also been awarded the Adobe Academic Collaboration Fund, Qualcomm Innovation Fellowship (QInF) Finalist Award, and Chiang Chen Overseas Graduate Fellowship. Her research outcomes have been successfully productized into real-world machine learning solutions and filed 5 patents. Dr. Zhang has been the chief organizer of several workshops on ICML/NeurIPS, and the special issue on ICMR. Dr. Zhang received her Ph.D. from Carnegie Mellon University in 2018, and her Master's from Peking University.

高阳，清华大学交叉信息研究院助理教授，主要研究计算机视觉与机器人学。此前，他在美国加州大学伯克利分校获得博士学位，师从Trevor Darrell教授。他还在加州伯克利大学与Pieter Abbeel等人合作完成了博士后工作。在此之前，高阳从清华大学计算机系毕业，与朱军教授在贝叶斯推理方面开展了研究工作。他在2011-2012年在谷歌研究院进行了自然语言处理相关的研究工作、2016年在谷歌自动驾驶部门Waymo的相机感知团队工作，在2018年与Vladlen Koltun博士在英特尔研究院在端到端自动驾驶方面进行了研究工作。高阳在人工智能顶级会议NeurIPS，ICML，CVPR，ECCV，ICLR等发表过多篇学术论文，谷歌学术引用量超过2000次。

赵行，现任清华大学交叉信息研究院助理教授，博士生导师。他的主要研究兴趣包括计算机视觉和听觉，多模态机器学习，自动驾驶等机器人应用。在此之前，赵行在麻省理工学院取得了博士学位，后于谷歌无人车项目Waymo担任研究科学家。赵行博士的多模态机器学习相关的工作曾被多家主流科技媒体报道，如BBC, NBC, 麻省理工科技评论等。他的工作获得了2015年ICCP最佳论文奖。他本人入选了2020年福布斯中国U30科学精英榜。

杨耀东博士，北京大学人工智能研究院助理教授（博雅学者）、北大元培“通班”2022级班主任。国家人社部高层次留学人才、国家优青（海外）、中国科协青年托举计划获得者。 研究方向为智能体安全交互与价值对齐，科研领域涵盖强化学习、AI对齐、具身智能。发表AI领域顶会顶刊论文一百余篇，谷歌引用近万次，2022年以来位列CSRanking北京大学AI+ML方向学者第一位。 曾获ICCV’23最佳论文奖入围、CoRL’20最佳系统论文奖、AAMAS’21最具前瞻性论文奖、麻省科技评论AI100青年、WAIC’22云帆奖璀璨明星、ACM SIGAI China新星奖。带领华人团队研发多智能体强化学习算法首登Nature Machine Intelligence，碳材料大模型Carbon Copilot发表于Cell子刊Matter，主导Baichuan2、鹏城脑海33B、香港HKGAI大模型对齐工作，曾获NeurIPS’22 机器人灵巧操作比赛冠军。央视一套《焦点访谈》、央视四套《深度国际》、新华网、Financial Times、麻省科技评论报道。现任ICML、ICLR、NeurIPS、AAAI、IJCAI、AAMAS、IROS 领域主席，《Transactions on Machine Learning Research》《Neural Network》执行编委。主持国自然、科技部、北京市科委、校企联合实验室等课题三十余项。曾任伦敦国王大学助理教授、华为英国研究所主任研究员、美国国际集团（AIG）科学部高级经理。 Yaodong is a machine learning researcher with ten-year working experience in both academia and industry of finance/high-tech companies. Currently, he is an assistant professor at King's College London. His research is about reinforcement learning and multi-agent systems. He has maintained a track record of more than forty publications at top conferences/journals, along with the best system paper award at CoRL 2020 (first author) and the best blue-sky paper award at AAMAS 2021 (first author). Before KCL, he was a principal research scientist at Huawei UK where he headed the multi-agent system team in London, working on autonomous driving applications. Before Huawei, he was a senior research manager at AIG, working on AI applications in finance. He holds a Ph.D. degree from University College London, an M.Sc. degree from Imperial College London and a Bachelor degree from University of Science and Technology of China.

2020年10月底加入浙江大学控制科学与工程学院、工业控制研究所孙优贤院士、陈积明教授的“网络传感与控制”课题组，聘为浙江大学“百人计划”研究员，博士生导师。在加入浙大之前，她于2011年在北京师范大学获得本科学位，2014年在清华大学获得硕士学位，2019年在英国帝国理工学院获得博士学位（导师Tae-kyun Kim）。2019年1月加入英国剑桥微软Mixed Reality & AI Lab，从事3D人体重建和跟踪、VR/AR相关的研究和开发工作，参与了微软新一代增强现实眼镜HoloLens2手势跟踪算法开发，主要合作者Andrew Fitzgibbon,Jamie Shotton,Toby Sharp, Tom Cashman等。 叶琦博士是浙江大学终身教授，曾任微软剑桥混合现实与人工智能实验室研究员。她拥有帝国理工学院博士学位、清华大学硕士学位和北京师范大学学士学位。她的研究方向为计算机视觉、计算机图形学和机器人技术的交叉领域，尤其关注3D视觉和嵌入式人工智能。 目前的研究方向包括交互场景和手-物体三维重建、主动视觉、多视角多模态感知、灵巧机器人操作等。相关研究成果已发表于计算机视觉和机器人领域的顶级会议和期刊，例如TPAMI、ECCV、CVPR、ICCV、RAL、ICRA、IROS等。

郝建业博士，现任天津大学软件学院副教授。香港中文大学(CUHK)计算机科学与工程专业博士，麻省理工学院(MIT)计算机科学与人工智能实验室(CSAIL)博士后研究员。 郝建业教授主持参与了国内、香港及国际地区科研项目10余项, 与国际上多个顶尖科研团队（包括麻省理工学院(MIT), 帝国理工学院，香港中文大学，新加坡国立大学等）具有良好的长期合作关系, 并取得了多项国际领先的研究成果。在人工智能领域具有丰富的研究经验，目前已在多智能体系统、 人工智能、 软件工程等领域的多个顶级国际期刊(Journal of Autonomous Agents and Multiagent Systems (JAAMAS), ACM Transactions on Autonomous and Adaptive Systems(TAAS)等) 和国际会议 (IJCAI, AAMAS, FSE, ICSE等)上发表论文30余篇，专著一部。 郝建业教授获得过多个香港地区和国际学术奖项(包括ANAC国际谈判比赛2012年度冠军、2015年度亚军、澳大利亚教育部Endeavor Fellowship、香港中文大学全球杰出研究者）。同时担任多个顶级期刊(包括JAAMAS, TAAS,TOSEM等)审稿人，美国国家科学基金委物联网项目评审专家。

Bo An is a Professor in the College of Computing & Data Science, and Co-Director of Artificial Intelligence Research Institute (AI.R) at Nanyang Technological University, Singapore. He received the Ph.D degree in Computer Science from the University of Massachusetts, Amherst. His current research interests include artificial intelligence, multiagent systems, computational game theory, reinforcement learning, and optimization. His research results have been successfully applied to many domains including infrastructure security and e-commerce. He has published over 100 referred papers at AAMAS, IJCAI, AAAI, ICAPS, KDD, UAI, EC, WWW, ICLR, NeurIPS, ICML, JAAMAS, AIJ and ACM/IEEE Transactions. Dr. An was the recipient of the 2010 IFAAMAS Victor Lesser Distinguished Dissertation Award, an Operational Excellence Award from the Commander, First Coast Guard District of the United States, the 2012 INFORMS Daniel H. Wagner Prize for Excellence in Operations Research Practice, and 2018 Nanyang Research Award (Young Investigator). His publications won the Best Innovative Application Paper Award at AAMAS’12, the Innovative Application Award at IAAI’16, and the best paper award at DAI’20. He was invited to give Early Career Spotlight talk at IJCAI’17. He led the team HogRider which won the 2017 Microsoft Collaborative AI Challenge. He was named to IEEE Intelligent Systems' "AI's 10 to Watch" list for 2018. He is PC Co-Chair of AAMAS’20 and will be General Co-Chair of AAMAS’23. He is a member of the editorial board of JAIR and is the Associate Editor of AIJ, JAAMAS, IEEE Intelligent Systems, ACM TAAS, and ACM TIST. He was elected to the board of directors of IFAAMAS, senior member of AAAI, and Distinguished member of ACM.