Ian Horrocks is a Professor of Computer Science at the University of Oxford and a Fellow of Oriel College. His research focuses on knowledge representation, description logics, automated reasoning, and semantic web technologies. He has held academic positions at the University of Manchester (2003–2007) and served as Chief Scientist at Cerebra Inc. (2001–2006). Horrocks earned his BSc (1st class), MSc, and PhD in Computer Science from the University of Manchester (1981–1997). His work includes foundational contributions to ontology languages (e.g., OWL) and reasoning systems such as HermiT and ELK. He has supervised over twenty doctoral students and postdoctoral researchers. His honors include Fellowships from the Royal Society (2011), ECCAI (2009), and the British Computer Society (2005). He serves as Editor-in-Chief of the Transactions on Graph Data and Knowledge and leads initiatives in semantic web standards and knowledge graph applications. Key Roles: Editor-in-Chief (Journal of Web Semantics), Co-Chair (W3C OWL Working Group) Grants: EPSRC Senior Research Fellowship (2005), numerous international collaborations Labs: Oxford Semantic Technologies, involvement in projects like RDFox and PAGOdA
Peter Druschel is a Professor and founding Director of the Max Planck Institute for Software Systems (MPI-SWS) in Saarbrücken, Germany. He holds adjunct professorships at Saarland University and the University of Maryland. His research focuses on distributed systems, operating systems, and privacy-preserving technologies. He earned his Ph.D. from the University of Arizona in 1994 and has held roles at Rice University since 1994, including Professor of Computer Science (2002–2005). Education: Ph.D. in Computer Science, University of Arizona (1994) Research Interests: Distributed systems, operating systems, network security, accountable computing, and privacy technologies. Current projects include privacy compliance in data systems (Thoth), secure communication (EbN), and privacy-aware image capture (I-Pic). Awards: SIGOPS Mark Weiser Award (2008) NSF CAREER Award (1995) Member of Academia Europaea and German Academy of Sciences Leopoldina Grants & Leadership: Leads the ERC Synergy Project imPACT, chairs the Max Planck Society’s Chemistry, Physics, and Technology Section, and collaborates with institutions like Cornell and Google. Advises on policy issues related to technology and privacy. Labs/Teams: Distributed Systems Group at MPI-SWS, collaborations with Microsoft Research and MIT. Current team includes students and postdocs working on privacy, security, and distributed systems.
Andrea C. Ferrari is a Professor of Nanotechnology at the Department of Engineering, University of Cambridge, UK. He holds multiple leadership roles, including Director of the Cambridge Graphene Centre and EPSRC Centre for Doctoral Training in Graphene Technology, and serves as Science and Technology Officer for the EU Graphene Flagship. Education: PhD, University of Cambridge (2001) Laurea in Nuclear Engineering, Politecnico di Milano (1997) Ferrari’s research focuses on graphene, 2D materials, and their applications in nanotechnology, photonics, optoelectronics, and Raman spectroscopy. His work bridges fundamental studies and industrial translation, emphasizing scalable synthesis and characterization techniques. His publications span over 390 peer-reviewed articles, including groundbreaking studies on graphene photonics, quantum emitters, and advanced optoelectronic devices. These works are highly cited, with an H-index of 115 and over 116,000 total citations. Scientific Awards: IMR-Lee Hsun Lecture Award (2018) Nanosmat Award (2017) Knight Officer of the Order of the Star of Italy (2017) ERC Synergy Grant (2013) EU-40 Materials Prize (2011) Royal Society Wolfson Research Merit Award (2010) ERC Starting Grant (2008) Philip Leverhulme Prize (2005) Ferrari has secured over £60M in research funding, including leadership roles in the EU Graphene Flagship and the EU Quantum Technology Flagship. He is a Fellow of the Optical Society, Materials Research Society, Institute of Physics, and American Physical Society.
Nori Franco serves as Professor in the Department of Physics at the University of Michigan and Chief Scientist at RIKEN's Theoretical Quantum Physics Laboratory in Japan. His dual appointments reflect his significant contributions to both American and Japanese academic communities, with continuous service at Michigan since 1990 and at RIKEN since 2002. His research spans quantum information, condensed matter physics, and quantum optics, with particular focus on light-matter interactions, superconducting qubits, optomechanics, and quantum open systems. Franco's work bridges theoretical foundations with experimental implementations, especially in circuit quantum electrodynamics and quantum computing applications. Analysis of his recent publications reveals a strong emphasis on non-Hermitian quantum systems, quantum control techniques, and applications of quantum information science to fundamental physics problems. His research group consistently produces highly cited work, with publications appearing in top journals across quantum physics and condensed matter disciplines. Scientific Awards: Charles Hard Townes Medal (2024) - sole recipient for fundamental contributions to quantum optics and quantum information processing Research Doctorate Honoris Causa from University of Messina (2024) Highly Cited Researcher for eight consecutive years (2017-2024) Member of Academia Europaea (2023) Willis E. Lamb Medal (2023) for quantum electronics research Throughout his career, Franco has secured significant research funding and mentored numerous students and postdoctoral researchers. His work has received international recognition through invitations to deliver prestigious lectures including the Stanislav Ulam Lecture and Sir Nevill Mott Lecture in 2024. His research group maintains strong collaborations across multiple continents, reflecting his global impact on quantum physics. At RIKEN, Franco leads the Quantum Information Physics Theory Research Team within the Quantum Computing Center, directing cutting-edge theoretical work that complements experimental efforts in quantum computing hardware development.
Zhou Zhi-Hua is a Professor at Nanjing University's Department of Computer Science & Technology, serving as Standing Deputy Director of the National Key Lab for Novel Software Technology and Founding Director of LAMDA (Institute of Machine Learning and Data Mining). He holds simultaneous fellowships from ACM, AAAI, AAAS, IEEE, IAPR, IET/IEE, and CCF, reflecting his exceptional contributions to computational intelligence. His educational background includes: B.Sc. in Computer Science from Nanjing University (1996) M.Sc. in Computer Science from Nanjing University (1998) Ph.D. in Computer Science from Nanjing University (2000) Zhou's research pioneers fundamental advances in machine learning theory and applications. His seminal work on ensemble methods established new frameworks for classifier combination, while innovations in multi-label learning and anomaly detection addressed critical challenges in complex data analysis. His research bridges theoretical rigor with practical implementations across diverse domains including biometrics, data mining, and computer vision, resulting in over 150 publications and 18 patents. His textbooks "Ensemble Methods" (2012) and "Machine Learning" (2016) have become standard references in the field. Analysis of his publication trajectory reveals sustained leadership in core machine learning challenges: evolving from neural network ensembles (2002) through semi-supervised learning breakthroughs (2005) to foundational work on multi-instance learning (2012) and theoretical margin analysis (2013). His recent focus demonstrates increasing sophistication in handling complex data structures while maintaining theoretical soundness. His scientific excellence is recognized through: National Natural Science Award of China (2013) PAKDD Distinguished Contribution Award (2016) IEEE ICDM Outstanding Service Award (2016) IEEE CIS Outstanding Early Career Award (2013) Microsoft Professorship Award (2006) Simultaneous fellowships from 7 major international societies Zhou provides extraordinary service to the academic community as Executive Editor-in-Chief of Frontiers of Computer Science and Associate Editor-in-Chief of Science China Information Science. He founded the ACML conference and has chaired premier events including ICDM'16 and PAKDD'14. His leadership extends to serving as General Chair for ICDM'16, Program Chair for IJCAI'15 Machine Learning Track, and Area Chair for multiple top conferences. The available text does not specify student advising details or research grants. He directs LAMDA research group at Nanjing University, which has established itself as a global powerhouse in machine learning research, and contributes significantly to the National Key Lab for Novel Software Technology's mission of developing next-generation intelligent systems.
Francesco Locatello is a tenure-track Assistant Professor at the Institute of Science and Technology Austria (ISTA), leading the Causal Learning and Artificial Intelligence lab. He is also an AI Resident at the Chan Zuckerberg Initiative. He holds a PhD from ETH Zürich, co-advised by Gunnar Rätsch and Bernhard Schölkopf. His research focuses on causal representation learning, score matching, and object-centric learning, with applications in machine learning and AI. His work has been recognized with prestigious awards, including the ICML 2019 Best Paper Award and the Hector Foundation Award (2023). Education: PhD in Machine Learning, ETH Zürich (advisors: Gunnar Rätsch, Bernhard Schölkopf) Research Interests: Causal Learning, Causal Representation Discovery, Score Matching Algorithms, Object-Centric Learning, Robust Generalization in AI, and Applications in Vision and Reinforcement Learning. Recent Work Trends: His publications emphasize causal mechanisms in neural representations, scalable causal discovery methods, and improving model generalization through latent space analysis. Recent studies explore geometric representations, mechanistic neural networks, and OOD detection using relative angles. Awards: ICML 2019 Best Paper Award Hector Foundation Award for Outstanding Achievements in Machine Learning (2023) Google Research Scholar Award (2024) Advising & Teams: Supervises a dynamic lab with students and postdocs across ISTA, ELLIS, and partner institutions. Notable advisees include Dingling Yao (ISTA), Riccardo Cadei (co-advised with Cordelia Schmid), and Marco Fumero (now a postdoc at ISTA). Collaborates with leading researchers like Arthur Gretton, Max Welling, and Volkan Cevher. Labs & Initiatives: Leads the Causal Learning and AI lab at ISTA, contributing to ELLIS programs and fostering interdisciplinary collaborations in causal AI.
Univ.-Prof. Torsten Möller, PhD is a Professor at the University of Vienna and serves as Head of the Research Group Visualization and Data Analysis and Head of the Research Network Data Science. His work spans data visualization, visual analytics, and human-computer interaction, with a focus on biomedical, environmental, and societal data applications. Academic rank: Professor Research group: Visualization and Data Analysis Network: Data Science Email: torsten.moeller@univie.ac.at Research interests include: Visual data analysis for complex systems Interdisciplinary applications in climate science and medicine Human-computer interaction in data exploration Image processing and computer graphics Recent publication trends show expertise in: Visualizing climate change and pandemic data Multi-volumetric and network analysis Algorithmic transparency and user-centered design Interdisciplinary collaborations (e.g., astrophysics, medical imaging) Statistical and uncertainty visualization Design frameworks for visualization recommendation Teaching includes courses in: Computer graphics and visualization Image processing and analysis Human-computer interaction Data analysis projects Doctoral research seminars
Professor Marta Zofia Kwiatkowska is Professor of Computing Systems and Fellow of Trinity College at the University of Oxford, where she has held a faculty position since 2007. She previously served as Professor of Computer Science at the University of Birmingham (2001–2007), Reader and Lecturer at the University of Birmingham (1994–2001), and Lecturer at the University of Leicester (1986–1994). Her academic career began as Assistant Professor at the Jagiellonian University in Kraków, Poland (1980–1988). Education: BSc/MSc in Computer Science, Jagiellonian University, Kraków MA, University of Oxford PhD, University of Leicester Research Interests: Professor Kwiatkowska spearheaded the development of probabilistic and quantitative verification methods on the international stage. Her work bridges theory and practice through the PRISM model checker—the leading software tool in probabilistic model checking—used worldwide for research and teaching. Application domains include communication and security protocols , nanotechnology designs , power management , ubiquitous computing and systems biology . She investigates automated verification , temporal logics , semantic models for concurrency , real-time systems , and biological process modelling . Current grant funding exceeds £3.7 million from EPSRC, EU and ERC, including the prestigious ERC Advanced Grant VERIWARE. Scientific Awards & Honours: Fellow of the Royal Society Fellow of the ACM Fellow of the European Association for Theoretical Computer Science (EATCS) Fellow of the British Computer Society (BCS) Fellow of the Polish Society of Arts & Sciences Abroad ERC Advanced Grant VERIWARE (€2.046 M, 2010–2015) Top Cited Article Award, Theoretical Computer Science (2005–2010) Best Paper Award, QEST 2006 Doctoral Supervision & Grants: Professor Kwiatkowska actively supervises doctoral students (D.Phil. at Oxford) and post-doctoral researchers. She welcomes applications in areas aligned with her research interests, detailed here . Current students include Charlie Griffin, Daqian Shao, Matthew Yuan and Minghao Liu; past students and researchers number over twenty, many now in faculty or industry leadership roles. Laboratory & Teams: She leads the Oxford Quantitative Verification group within the Department of Computer Science. Ongoing projects include FUN2MODEL, ELSA, FAIR and the flagship PRISM probabilistic model checker. The group maintains strong collaborations with biological, robotics and engineering teams worldwide.
Dominik Schörkhuber is a PreDoc Researcher at the Vienna University of Technology (TU Wien) in the Computer Vision department. With a background in Informatics (BSc, Dipl.-Ing.), he focuses on computer vision applications for autonomous driving, robotics, and human-machine interaction. His work spans driver action recognition, pedestrian prediction, and adaptive lighting systems. Current projects: Empathic Vehicle (2024–2026), SyntheticCabin (2021–2025), SmartProtect (2020–2025) Research themes: Video transformers, synthetic data transfer learning, multi-task learning, and sensor-lighting integration Specializes in 3D sensing, nighttime driving analysis, and mobile video creation tools
Dr. Rajkumar Buyya is a Redmond Barry Distinguished Professor at the University of Melbourne and Founder & CEO of Manjrasoft , a spin-off commercializing cloud innovations. He has held visiting roles at Imperial College London , University of Birmingham , and Tsinghua University . Research Interests : His work spans Cloud Computing , Edge Computing , Grid Systems , and Energy-Efficient Computing , focusing on utility-driven resource allocation, simulation tools, and scalable IoT application frameworks. He pioneered the CloudSim toolkit and Aneka Cloud technologies. Scientific Awards : IEEE Fellow (2015), Web of Science Highly Cited Researcher (2016-2021) Khwarizmi International Award (2020), Scopus Researcher of the Year (2017) Frost & Sullivan New Product Innovation Award (2010), IEEE TCSC Medal (2009) Impact : Authored over 850 publications, including the widely adopted textbook Mastering Cloud Computing . Graduated 54 PhD students now in leadership roles at institutions like Newcastle University and companies such as IBM , Google , and Amazon . His research has driven global adoption of cloud/edge technologies in 50+ countries.
Jiao Licheng is a Distinguished Professor and Doctoral Supervisor at Xidian University, leading the School of Artificial Intelligence and the Department of Computer Science and Technology. He holds prominent roles such as Director of the Key Laboratory of Intelligent Perception and Image Understanding (Ministry of Education) and the International Joint Research Center for Intelligent Perception and Computing. His research focuses on Artificial Intelligence, Deep Learning, Evolutionary Computation, and Remote Sensing, with significant contributions to image understanding and brain-inspired computing. Education: B.E. (1982) from Shanghai Jiao Tong University, M.E. (1984) and Ph.D. (1990) from Xi'an Jiaotong University. Postdoctoral research at Xidian University (1990–1992). Research Interests include AI, Machine Learning, Image Processing, and Big Data Analysis. His work bridges theoretical advancements and practical applications, such as medical imaging, SAR image analysis, and autonomous systems. Recent articles emphasize innovations in remote sensing, deep learning architectures, and evolutionary algorithms. Awards include IEEE Fellow, IET Fellow, and the Wu Wenjun Artificial Intelligence Outstanding Contribution Award. Labs/Teams: Key Lab of Intelligent Perception, International Joint Research Center, and leadership in national innovation bases. Active in academic societies, including editorial roles in IEEE Transactions on Cybernetics and Geoscience and Remote Sensing.
Prof. Yu Jihong is a full Professor at the Department of Chemistry, Jilin University, and serves as Director of the International Center of Future Science and Vice President of the Chinese Chemical Society. She leads the State Key Laboratory of Inorganic Synthesis and Preparative Chemistry. Her research focuses on designing nanoporous materials for energy and environmental applications, with over 320 publications in top journals like Science and Nature Communications. Education: BS (1989), MS (1992), PhD (1995) from Jilin University Postdoctoral: Hong Kong University of Science and Technology (1996–1997), Tohoku University (1997–1998) Research interests include inorganic synthesis, porous materials, catalytic materials, and environmental applications. Her work bridges computational methods with experimental synthesis, yielding innovations in zeolite structures and catalytic systems. Awards: IUPAC Distinguished Women in Chemistry Award (2017), TWAS Fellow (2016), Chinese Academy of Sciences Academician (2015), and multiple national science prizes. She is an Associate Editor of Chemical Science and leads editorial boards for Materials Horizons and others. Her articles emphasize novel synthetic methods, catalytic systems, and sustainable materials. Key themes include accelerating zeolite crystallization, designing nanocatalysts, and developing porous membranes for environmental applications.
Dr. Li Baowen is Chair Professor at Southern University of Science and Technology (SUSTech) with joint appointments in the Department of Physics and Department of Materials Science and Engineering. A pioneer in phononics and thermal metamaterials, he previously held endowed professorships at University of Colorado Boulder and UC Berkeley. His research focuses on controlling heat transfer at nano scales, developing thermal metamaterials like thermal cloaks, and applying complex networks to physical systems. Dr. Li has published over 400 papers including 3 in Reviews of Modern Physics and 30 in Physical Review Letters, with more than 34,800 citations (H-index 98). He is recognized with the Brillouin Medal from the International Phononics Society and is a Fellow of the American Physical Society. He founded research centers including the China-EU Joint Lab for Nanophononics at Tongji University. His current research explores quantum phononics, machine learning applications in thermal materials, phonon lasers, and quantum sensing technologies.
Ares J. Rosakis is the Theodore von Kármán Professor of Aeronautics and Mechanical Engineering at the California Institute of Technology (Caltech), where he served as Chair of the Division of Engineering and Applied Science from 2009-2015 and previously as Director of the Graduate Aerospace Laboratories (GALCIT). He has held numerous prestigious visiting professorships including at Nanyang Technological University, Northwestern University, Columbia University, Oxford University, and École Normale Supérieure in Paris. Rosakis earned his B.A. and M.A. in Engineering Science from Oxford University in 1978, followed by his Sc.M. (1980) and Ph.D. (1982) in Engineering (Solid Mechanics) from Brown University. He joined Caltech as an Assistant Professor in 1982, was promoted to Associate Professor in 1988, and to full Professor in 1993. In 2004, he was named the Theodore von Kármán Professor, one of Caltech's most distinguished named chairs. Rosakis is globally recognized as the foremost expert in dynamic failure mechanics of solid materials. His pioneering contributions span the dynamic failure of metals, composites, and interfaces. He invented Coherent Gradient Sensing (CGS) interferometry, a novel optical method sensitive to gradients of optical path differences that has been widely adopted in fracture mechanics and thin film stress measurements. His research encompasses dynamic shear-dominated rupture of heterogeneous materials, rupture mechanics of crustal earthquakes (where he experimentally discovered 'intersonic' or 'supershear' ruptures), and reliability of thin films and in-situ wafer level metrology. His work bridges engineering science, materials mechanics, and geophysics with remarkable interdisciplinary impact. His recent publications demonstrate a strong focus on earthquake mechanics and laboratory simulations of seismic events, particularly supershear earthquake ruptures. The research connects fundamental fracture mechanics with real-world geophysical phenomena, revealing how laboratory-scale experiments can illuminate the physics of large-scale earthquakes. His work has established critical links between theoretical models, experimental observations, and geological field evidence. Rosakis has received numerous prestigious awards including: 2024 Foreign Member of the Royal Society, UK 2023 Honorary PhD from National Technical University of Athens 2023 Honorary Degree of Doctor of Engineering from University of Illinois 2021 Zdeněk P. Bažant Medal for Failure and Damage Prevention 2018 Timoshenko Medal from ASME 2016 Elected to the National Academy of Sciences 2011 Elected to the National Academy of Engineering Throughout his distinguished career at Caltech, Rosakis has mentored numerous graduate students and postdoctoral researchers, many of whom have become leaders in their fields. His research has been continuously supported by major grants from the National Science Foundation, Department of Energy, and other federal agencies, focusing on dynamic fracture, earthquake mechanics, and advanced optical measurement techniques. He has served on numerous editorial boards and advisory committees for major scientific organizations. At Caltech, Rosakis leads research in the Graduate Aerospace Laboratories (GALCIT), where he has established world-class experimental facilities for studying dynamic fracture and earthquake mechanics. His laboratory features high-speed imaging systems capable of millions of frames per second, infrared diagnostics for temperature field measurements, and specialized equipment for simulating earthquake ruptures at laboratory scale. His research group combines experimental, theoretical, and computational approaches to address fundamental questions in solid mechanics and their applications to geophysics and materials engineering.
Massimiliano Di Ventra is a Professor of Physics at the University of California, San Diego, holding this position since 2006 after serving as Associate Professor (2004-2006) and moving from Virginia Tech where he was Assistant Professor (2000-2002) and Associate Professor (2003). His academic journey includes research roles at IBM T.J. Watson Research Center and Vanderbilt University. Education: Undergraduate degree in Physics, summa cum laude, University of Trieste, Italy (1991) PhD in Physics, Swiss Federal Institute of Technology, Lausanne (1993-1997) Di Ventra's research bridges theoretical physics with practical applications, focusing on quantum transport in nanoscale systems, non-equilibrium statistical mechanics, and DNA sequencing/polymer dynamics in nanopores. His pioneering work on memory effects in nanostructures has driven innovations in unconventional computing and biophysics, resulting in over 300 refereed publications and significant commercial impact through memcomputing technologies. His scientific awards include: Senior member, National Academy of Inventors (2025) Humboldt Research Award (2024) Fellow, American Association for the Advancement of Science (2022) IEEE Nanotechnology Council Distinguished Lecturer (2022) Fellow, IEEE (2022) George W. and Carol A. Lattimer Research Fellow (2021) Member of Academia Europaea (2020) Feynman Prize for Theory in Nanotechnology (2020) APS Outstanding Referee (2019) Highly Cited Researcher (2018) Di Ventra has secured major research funding including an NSF CAREER Award and Ralph E. Powe Award, holds 11 granted patents, and co-founded MemComputing, Inc. His mentorship extends to numerous graduate students and postdoctoral researchers within his active research group at UCSD. He maintains a globally recognized research presence through visiting professorships at institutions including École Normale Supérieure of Paris (2024), Technion (2017), and Technical University of Dresden (2015), and has delivered over 350 invited talks including 20 plenary/keynote presentations worldwide.
