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Schahram Dustdar

ICREA, Barcelona, Spain

Schahram Dustdar

ICREA, Barcelona, Spain

Schahram Dustdar is a ICREA Professor au UPF. He has also been Full Professor of Computer Science heading the Research Division of Distributed Systems at the TU Wien, Austria. He holds several honorary positions: Francqui Chair Professor at University of Namur, Belgium (2021-2022), University of California (USC) Los Angeles; Monash University in Melbourne, Shanghai University, Macquarie University in Sydney. From Dec 2016 until Jan 2017 he was a Visiting Professor at the University of Sevilla, Spain and from January until June 2017 he was a Visiting Professor at UC Berkeley, USA.

From 1999 - 2007 he worked as the co-founder and chief scientist of Caramba Labs Software AG in Vienna (acquired by Engineering NetWorld AG), a venture capital co-funded software company focused on software for collaborative processes in teams. Caramba Labs was nominated for several (international and national) awards. One day however a small line of blind text by the name of Lorem Ipsum decided to leave for the far World of Grammar. The Big Oxmox advised her not to do so, because One day however a small line of blind text by the name of Lorem Ipsum decided to leave for the far World of Grammar. The Big Oxmox advised her not to do so, because

Email:chief@nxtai-conference.com

Jinde Cao

Southeast University, China

Jinde Cao

Southeast University, China

Jinde Cao (Fellow, IEEE) received the B.S. degree in mathematics from Anhui Normal University, Wuhu, China in 1986, the M.S. degree from Yunnan University, Kunming, China, and the Ph.D. degree from Sichuan University, Chengdu, China, both in applied mathematics, 1989, and 1998, respectively. He was a Postdoctoral Research Fellow at the Department of Automation and Computer-Aided Engineering, Chinese University of Hong Kong, Hong Kong, China from 2001 to 2002.

Professor Cao is an Endowed Chair Professor, the Dean of Science Department and the Director of the Research Center for Complex Systems and Network Sciences at Southeast University (SEU). He is also the Director of the National Center for Applied Mathematics at SEU-Jiangsu of China and the Director of the Jiangsu Provincial Key Laboratory of Networked Collective Intelligence of China. He is also Honorable Professor of Institute of Mathematics and Mathematical Modeling, Almaty, Kazakhstan.

Prof. Cao was a recipient of the National Innovation Award of China, IETI Annual Scientific Award, Obada Prize and the Highly Cited Researcher Award in Engineering, Computer Science, and Mathematics by Clarivate Analytics. He is elected as a member of Russian Academy of Sciences, a member of the Academia Europaea (Academy of Europe), a member of the European Academy of Sciences and Arts, a member of the Lithuanian Academy of Sciences, a fellow of African Academy of Sciences, and a fellow of Pakistan Academy of Sciences.

James Hendler

Rensselaer Polytechnic Institute Troy, NY USA

James Hendler

Rensselaer Polytechnic Institute Troy, NY USA

James Hendler is the Acting Department Head of the Cognitive Science Department, the Tetherless World Professor of Computer, Web and Cognitive Sciences at RPI and is also director of the RPI-IBM Artificial Intelligence Research Collaboration.

Hendler is a data scientist with specific interests in open government and scientific data, data science for healthcare, AI and machine learning, semantic data integration and the use of data in government. One of the originators of the Semantic Web, he has authored over 450 books, technical papers, and articles in the areas of Open Data, the Semantic Web, artificial intelligence, and data policy and governance. He is also the former Chief Scientist of the Information Systems Office at the US Defense Advanced Research Projects Agency (DARPA) and was awarded a US Air Force Exceptional Civilian Service Medal in 2002. He is the first computer scientist ever to have served on the Board of Reviewing editors for Science. In 2010, Hendler was selected as an “Internet Web Expert” by the US government and helped in the development and launch of the US data.gov open data website. In 2013, he was appointed as the Open Data Advisor to New York State and in 2015 appointed a member of the US Homeland Security Science and Technology Advisory Committee. In 2016, became a member of the National Academies Board on Research Data and Information, in 2017 a member of the Director’s Advisory Committee of the National Security Directorate of PNNL, and in 2021 became chair of the ACM’s global Technology Policy Council. Hendler is a Fellow of the US National Academy of Public Administration, the AAAI, AAAS, ACM, BCS and IEEE.

Marcia C. Linn

University of California, berkeley, USA

Marcia C. Linn

University of California, berkeley, USA

Marcia C. Linn is Evelyn Lois Corey Professor of Instructional Science, specializing in science and technology in the School of Education, University of California, Berkeley(link is external). She is a member of the National Academy of Education and a Fellow of the American Association for the Advancement of Science (AAAS), the American Psychological Association, the Association for Psychological Science, and the International Society of the Learning Sciences (ISLS). She has served as President of the ISLS, Chair of the AAAS Education Section, and on the boards of the AAAS, the Educational Testing Service Graduate Record Examination, the McDonnell Foundation Cognitive Studies in Education Practice, and the National Science Foundation Education and Human Resources Directorate. Awards include the National Association for Research in Science Teaching Award for Lifelong Distinguished Contributions to Science Education, the American Educational Research Association Willystine Goodsell Award, and the Council of Scientific Society Presidents first award for Excellence in Educational Research. Linn earned her Ph. D. at Stanford University where she worked with Lee Cronbach. She spent a year in Geneva working with Jean Piaget, a year in Israel as a Fulbright Professor, and a year in London at University College. She has been a fellow at the Center for Advanced Study in Behavioral Sciences three times. Her books include Computers, Teachers, Peers (2000), Internet Environments for Science Education (2004), Designing Coherent Science Education (2008), WISE Science (2009), and Science Teaching and Learning: Taking Advantage of Technology to Promote Knowledge Integration (2011). She chairs the Technology, Education—Connections (TEC) series for Teachers College Press.

One day however a small line of blind text by the name of Lorem Ipsum decided to leave for the far World of Grammar. The Big Oxmox advised her not to do so, because

Mohand Tahar Kechadi

University of Dublin, Ireland

Jaideep Srivastava

University of Minnesota, Minneapolis, MN, USA

Anind K Dey

University of Washington, Seattle, Washington, USA

Guann Pyng Li

University of California, Irvine, California, USA

Zehui Xiong

Queen's University Belfast, UK

Zehui Xiong

Queen's University Belfast, UK

Zehui Xiong is currently a Full Professor with the School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, United Kingdom. Prior to that, he was with Singapore University of Technology and Design, and Nanyang Technological University (NTU). He received the Ph.D. degree in Computer Science and Engineering at NTU, Singapore. He was a visiting scholar with Department of Electrical Engineering at Princeton University and a visiting scholar with Broadband Communications Research (BBCR) Lab in Department of Electrical and Computer Engineering at University of Waterloo. His research interests include wireless networks, Internet of Things, edge intelligence, semantic communications, generative AI, and Metaverse.

Recognized as a Highly Cited Researcher, he has published more than 250 peer-reviewed research papers in leading journals, with numerous Best Paper Awards from international flagship conferences. He serves as an Editor or Guest Editor for many leading journals such as IEEE Journal on Selected Areas in Communications, IEEE Transactions on Vehicular Technology, IEEE Internet of Things Journal, IEEE Transactions on Cognitive Communications and Networking, IEEE Transactions on Network Science and Engineering. Featured in Forbes Asia 30U30, he serves as the Chair for numerous international conferences. His honors include the IEEE Asia Pacific Outstanding Young Researcher Award, IEEE VTS Early Career Award, IEEE Early Career Award for Excellence in Scalable Computing, IEEE Technical Committee on Blockchain and Distributed Ledger Technologies Early Career Award, IEEE Internet Technical Committee Early Achievement Award, IEEE TCSVC Rising Star Award, IEEE TCI Rising Star Award, IEEE TCCLD Rising Star Award, IEEE ComSoc Outstanding Paper Award, IEEE Best Land Transport Paper Award, IEEE Asia Pacific Outstanding Paper Award, IEEE CSIM Technical Committee Best Journal Paper Award, IEEE SPCC Technical Committee Best Paper Award, and IEEE Big Data Best Influential Conference Paper Award.

Tongliang Liu

The University of Sydney, Australia

Tongliang Liu

The University of Sydney, Australia

Tongliang Liu is an Associate Professor in Machine Learning with the School of Computer Science and The Director of Sydney AI Centre at the University of Sydney. He is broadly interested in the fields of trustworthy machine learning and its interdisciplinary applications, with a particular emphasis on learning with noisy labels, adversarial learning, causal representation learning, transfer learning, unsupervised learning, foundation model safety, and statistical deep learning theory. He has authored and co-authored more than 200 research articles including ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV, AAAI, IJCAI, JMLR, and TPAMI. He is/was a senior meta-reviewer for NeurIPS, ICLR, AAAI, and IJCAI, meta-reviewer for NeurIPS, ICML, ICLR, UAI, AAAI, IJCAI, and KDD, and was a notable AC for NeurIPS and ICLR. He is a co-Editor-in-Chief for Neural Networks, an Associate Editor of IEEE TPAMI, TIP, JAIR, ACM Computing Surveys, and TMLR, and is on the Editorial Boards of JMLR and MLJ. He is a recipient of Young Distinguished Scientist Award from the International Association of Engineers (IAENG) in 2025, CORE Award for Outstanding Research Contribution in 2024, the IEEE AI's 10 to Watch Award in 2023, the Future Fellowship Award from Australian Research Council (ARC) in 2022, the Top-40 Early Achievers by The Australian in 2020, and the Discovery Early Career Researcher Award (DECRA) from ARC in 2018.

Raj Jain

Washington University St. Louis, Missouri, USA

Zhipeng Huang

Suffolk University, Boston, MA

Fred Heiding

Harvard Kennedy School, Cambridge, MA

Fred Heiding

Harvard Kennedy School, Cambridge, MA

Fred Heiding is a postdoctoral research fellow at the Belfer Center’s Defense, Emerging Technology, and Strategy (DETS) program at Harvard Kennedy School. His work focuses on computer security at the intersection of technical capabilities, business implications, and policy remediations. Fred is a member of the World Economic Forum's Cybercrime Center and is on the organizing committee of the Technology and National Security Conference. He is a teaching fellow for the Generative AI course at Harvard Business School and the National and International Security course at the Harvard Kennedy School. Fred has been invited to brief the US House and Senate staff in DC on the rising dangers of AI-powered cyberattacks, and he leads the cybersecurity division of the Harvard AI Safety Student Team (HAISST). His work has been presented at leading conferences, including Black Hat, Defcon, and BSides, and leading academic journals like IEEE Access and professional journals like Harvard Business Review and Politico. He has assisted in the discovery of more than 45 critical computer vulnerabilities (CVEs). In early 2022, Fred got media attention for hacking the King of Sweden and the Swedish European Commissioner.

Fernando Moreira

Universidade Portucalense, Portugal

Fernando Moreira

Universidade Portucalense, Portugal

Fernando Moreira is a researcher and professor affiliated with Universidade Portucalense Infante D. Henrique, Porto, Portugal. He is known for his work in the fields of information systems, artificial intelligence, and data science. His research focuses on areas such as machine learning, decision support systems, and digital transformation. He has contributed to numerous international publications, conferences, and research projects, and is actively involved in advancing technological innovation and interdisciplinary studies. In addition to his research, he is engaged in teaching and mentoring students in computer science and related domains.

Sanjay Padhi

CERN, Geneva, Switzerland

Sanjay Padhi

CERN, Geneva, Switzerland

Sanjay Padhi is a researcher associated with CERN, the world’s leading laboratory for particle physics. His work is connected to advanced scientific research in areas such as high-energy physics, data analysis, and large-scale computing systems. At CERN, he contributes to collaborative international projects involving cutting-edge experiments and technologies that aim to explore the fundamental structure of the universe. His role involves working with complex datasets, scientific instrumentation, and global research teams.

GlobalAI-2026 is dedicated to providing a platform for sharing the latest AI research findings and presenting cutting-edge methodological advancements.

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