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Stanislav Smirnov is a Professor at the University of Geneva's Department of Mathematics since 2003 and Head of the Chebyshev Laboratory at St. Petersburg State University since 2010. He holds a Ph.D. from the California Institute of Technology (1996) and a B.Sc./M.Sc. from St. Petersburg State University (1992). His research focuses on mathematical physics, probability, complex analysis, and dynamical systems, with groundbreaking contributions to the understanding of critical phenomena in statistical physics. Key achievements include receiving the Fields Medal (2010), the highest honor in mathematics, for his work on percolation and the Ising model. He has organized major international conferences, such as the 'St. Petersburg School in Probability & Statistical Physics' (2012) and the '2D Statistical Physics Workshop' (2013). His academic career includes positions at Yale University, the Max-Planck Institute, and KTH Royal Institute of Technology. Education: Ph.D., Mathematics, California Institute of Technology (1996) B.Sc./M.Sc., Mathematics (with honors), St. Petersburg State University (1992) Awards: Fields Medal (2010) European Research Council Advanced Grants (2008, 2013) Rollo Davidson Prize (2002) Salem Prize (2001) Smirnov’s research bridges probability theory and complex analysis, with notable results on conformal invariance in two-dimensional models. His work has advanced understanding of critical exponents, percolation thresholds, and the universality of phase transitions. He advises doctoral students and collaborates internationally on projects funded by Swiss and European grants. He co-organized over 20 conferences worldwide, including plenary talks at the International Congress of Mathematicians (2006, 2010) and the World Congress in Probability and Statistics (2012). His lab fosters interdisciplinary research, linking mathematics to physics and computer science.

• Mathematical Physics
• Probability
• Complex Analysis
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Beng Chin Ooi is a Lee Kong Chian Centennial Professor at the National University of Singapore (NUS), School of Computing (SoC). He holds a B.Sc. (1st Class Honors) and Ph.D. in Computer Science from Monash University. His research focuses on database systems, large-scale analytics, and distributed computing. He has held leadership roles including Dean of School of Computing (2007–2013) and Director of Smart Systems Institute (2011–2021). Key achievements include the Singapore President’s Science Award (2011), ACM Fellow (2011), IEEE Fellow (2009), and multiple best paper awards. His work emphasizes scalable data management, blockchain systems, and healthcare data analytics. Education: Monash University (B.Sc., Ph.D.) Leadership: Dean (SoC), Director (Smart Systems Institute) Awards: Over 15 major honors including ACM SIGMOD E.F. Codd Innovations Award (2020) His research spans distributed databases, big data systems, and innovative applications of blockchain technology. Recent work includes NASI (neural architecture search) and Rafiki (ML-as-a-service).

• Database systems
• Large scale analytics
• Distributed systems
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Christoph Koch is a Full Professor in the School of Computer and Communication Sciences at EPFL (Ecole Polytechnique Federale de Lausanne) , Switzerland. He has held academic positions at Cornell University (2007-2010, 2006), Saarland University (2005-2007), and TU Vienna (2001-2005). His research focuses on database systems, logic, programming languages, and data management.

• Database systems
• Database theory
• Programming languages
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Jan Dreier is a Research Fellow at the Institute of Logic and Computation at Vienna University of Technology. His research centers on structural graph theory and algorithmic meta-theorems, particularly exploring the boundaries of tractability for model checking problems. Dreier's work bridges theoretical computer science and discrete mathematics, focusing on graph decompositions, parameterized complexity, and logical expressiveness. Key research themes include monadic stability in graph classes, applications of model theory to computer science, and efficient algorithms for logical queries on structured graphs. His publication record shows consistent focus on graph sparsity concepts and algorithmic applications of logic, with recent work expanding into approximation methods for counting queries. Research demonstrates sophisticated applications of combinatorial methods to fundamental problems in computational complexity.

• Structural Graph Theory
• Algorithmic Meta-theorems
• Computational Complexity
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Richard Franz Löscher is a researcher at the Institute of Applied Mathematics specializing in numerical methods for optimal control problems. He holds a BSc, Diplom-Ingenieur (Dipl.-Ing.), and Doctorate in Technical Sciences (Dr.techn.), demonstrating extensive technical education and engineering expertise. His educational qualifications include: BSc Diploma in Engineering (Dipl.-Ing.) Doctorate in Technical Sciences (Dr.techn.) Löscher's research centers on numerical mathematics with deep specialization in finite element methodologies for distributed optimal control problems governed by partial differential equations. His work addresses elliptic, parabolic, and hyperbolic control systems through regularization techniques, adaptive mesh refinement, and robust solver development. Key innovations include variable energy regularization frameworks, mass-lumping discretizations, and complexity-optimal space-time finite element systems that significantly advance computational efficiency and error estimation in constrained control environments. Analysis of his 2024-2026 publications reveals a cohesive research trajectory focused on overcoming computational bottlenecks in optimal control. His work consistently bridges theoretical rigor with practical implementation, emphasizing discretization schemes that balance accuracy and computational cost while addressing state/control constraints across diverse PDE systems. No scientific awards or honors were documented in available sources. Löscher maintains active research collaborations with prominent figures including Ulrich Langer and Olaf Steinbach, evidenced by co-authored publications and peer-review activities for journals like Journal of Computational and Applied Mathematics. His external research engagement includes a July 2024 visit to Delft University of Technology, highlighting international academic partnerships.

• Numerical Mathematics
• Finite Element Analysis
• Optimal Control
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Deval Desai serves as Reader in International Economic Law at the University of Edinburgh's Edinburgh Law School, a position he has held since 2020 after serving as Lecturer from 2020-2023. His academic career includes research positions at Harvard Law School and the Geneva Graduate Institute. Dr. Desai also brings extensive practical experience from a decade working with the World Bank on rule of law and governance in sub-Saharan Africa, as well as advising the United Nations on rule of law issues. Dr. Desai's educational background includes an MA in History and French Literature from Oxford University, followed by legal training at City University/BPP Law School (PGDipL and PGDipLP), and advanced law degrees (LLM and SJD) from Harvard Law School. At Harvard, he held prestigious fellowships including the Byse Fellowship, Program on Negotiation Next Generation Fellowship, and Institute for Global Law and Policy Fellowship. MA (Oxon), History and French Literature PGDipL, PGDipLP, City University/BPP Law School LLM, Harvard Law School SJD, Harvard Law School Dr. Desai's research centers on law and development, administrative law and regulation, theories of the state, and patterns of knowledge and authority across the Global North and South. His work examines institutional reform processes, particularly how expertise and knowledge operate within rule of law initiatives. His interdisciplinary approach draws from legal and social theory, development studies, international relations, and performance studies, as evidenced in his monograph Expert Ignorance (Cambridge University Press). His recent work focuses on fiscal sociology, administrative law in the Global South, and the politics of social welfare provision. Dr. Desai's publications span leading journals in law, political science, and development studies, revealing a consistent focus on the intersections between legal institutions, governance, and development. His work demonstrates increasing engagement with comparative methodologies and critical perspectives on knowledge production in global governance. Recent articles show particular attention to fiscal policy, welfare systems, and responses to global crises like the Covid-19 pandemic, with comparative studies between India and European contexts. Dame Muriel Spark Medal (2024, Royal Society of Edinburgh) Chancellor's 'Rising Star' Award (2023, University of Edinburgh) Member of the Young Academy of Scotland Fellow of the Royal Society of Arts Fellow of the Young Academy of Europe Dr. Desai has secured significant research funding from diverse international sources, including a £2.1 million Swiss National Science Foundation Sinergia grant titled 'Reversing the Gaze: Towards Post-Comparative Area Studies' where he serves as PI. He also leads projects funded by the British Academy, University of Edinburgh's Big Ideas Accelerator, Scottish Funding Council, and Foreign, Commonwealth, and Development Office. His commitment to mentoring is evident through his recognition with the Susan Manning Award for Inspiring Mentor and his leadership in establishing programs like the Global Scholars' Academy at the Geneva Graduate Institute and the Global Justice summer school at CEU. As editor-in-chief of the Cambridge University Press book series 'Elements in Legal Theory and the Global South' and serving on multiple editorial boards, Dr. Desai plays a significant role in shaping scholarly discourse. His current research projects examine 'loss' in legal institutions guiding transitional processes, constitutional implications of fiscal arrangements in fragile contexts, and social welfare provision in India and Italy.

• Law and Development
• Administrative Law
• Regulation
• +7 more

Huamin Qu is a Chair Professor in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST). He serves as the Founding Dean of the Academy of Interdisciplinary Studies (AIS), Founding Head of the Division of Emerging Interdisciplinary Areas (EMIA), and was the Founding Acting Head of Computational Media and Arts (CMA) at HKUST(GZ). Qu directs the VisLab and coordinates the Human-Computer Interaction (HCI) group. He obtained his BS in Mathematics from Xi'an Jiaotong University and MS/PhD in Computer Science from Stony Brook University. Qu's research integrates Data Visualization , Human-Computer Interaction , and Human-Centered AI , with applications in urban informatics, social networks, and explainable AI. His work focuses on developing interactive systems for big data analytics, visual storytelling, and AI-driven decision support. Research extends to multimodal communication, fintech, and augmented reality applications. His publications emphasize visual analytics for complex datasets (mobility, social media, financial), interaction techniques for immersive environments, and AI-enhanced visualization tools. Recent works explore explainable AI interfaces and large-scale data communication frameworks. IEEE Visualization Academy (2020) IEEE VGTC Technical Achievement Award AI 2000 Most Influential Scholar (2019, 2023, 2024) 21 Best Paper/Honorable Mention awards IBM Faculty Award (2009) APICTA Merit Award (2015) Yelp Dataset Grand Prize (2018) Qu has advised 48 PhD graduates (21 now faculty at institutions like UC Davis, University of Minnesota, Texas A&M) and 30 MPhil students. He secured major grants including RGC theme-based projects (digital citizenship, air pollution), UGC AoE (slope safety), and China's 973 Program. As VisLab director, he leads 20+ researchers in visualization/HCI projects adopted by Microsoft, IBM, Huawei, and Tencent.

• Data Visualization
• Human-Computer Interaction
• Big Data Analytics
• +13 more

Claus Lamm is a Full Professor of Biological Psychology at the University of Vienna , where he leads the Social, Cognitive and Affective Neuroscience Unit (SCAN-Unit) . He serves as Vice Dean for Research and Advancement of Early Career Researchers at the Faculty of Psychology and holds affiliations with the Vienna Cognitive Science Hub , Environment & Climate Change Hub , and Austrian Academy of Sciences . His academic career spans international collaborations and formative research experience abroad. Scientific Focus: Lamm investigates the neural underpinnings of empathy and prosocial behavior , employing multi-modal approaches combining neuroimaging, psychopharmacology, and psychoneuroendocrinology . His work extends to comparative studies with ravens and dogs, and explores environmental social neuroscience through climate change decision-making research. Recent publications show trends in cross-cultural psychology , machine learning applications , and neurobiological pathways related to social behavior. Awards & Grants: Recipient of the APS Mentor Award for his support of early career researchers. Funded by European Research Council , Austrian Science Fund , Vienna Science and Technology Fund , and intramural grants exceeding €10 million. Key projects include "Unravelling the opioid system in empathy" and "Comparative dog-human fMRI" . Media Engagement: A prominent public science communicator, Lamm has appeared in Nature , Science Magazine , and Austrian media outlets like Ö1 Mittagsjournal and ORF2 , discussing topics from pandemic psychology to social media effects . He maintains active outreach through Science TV and educational programs .

• Empathy
• Prosocial Behavior
• Social Neuroscience
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Univ.-Prof. Dr. Hans J. Briegel is a Professor at the Institute of Theoretical Physics within the Faculty of Mathematics, Computer Science and Physics at the University of Innsbruck. His research group focuses on Quantum Information and Computation . He can be contacted via Hans.Briegel@uibk.ac.at and is located in Room 4S15.

• Quantum Information
• Quantum Computation
• Theoretical Physics
• +1 more

Katja Hose is a Full Professor of Data Management at TU Wien's DBAI research unit, heading the Data Management and Knowledge-Driven AI Lab. She previously held a Poul Due Jensen Foundation Professorship at Aalborg University. Her research focuses on data and knowledge engineering, including graph databases, knowledge graphs, querying, analytics, and machine learning, with interdisciplinary applications in bioscience, healthcare, and environmental assessment. Education: PhD in Computer Science (Ilmenau University of Technology, 2009), Postdoc at Max Planck Institute for Informatics (2009–2012). Academic roles include Program Co-Chair for ISWC 2024 and EDBT 2023, and editorial board membership at VLDBJ and TGDK. She leads projects like TARGET (health virtual twins) and ARMADA (data management). Research Interests: Knowledge Graphs, Semantic Web, Big Data, Machine Learning, Data Integration, and Provenance Systems. Key contributions include SHACL shape extraction, conversational data analytics, and environmental knowledge graphs. Awards include the 2025 Distinguished Meta-Reviewer Award and 2024 Manfred Paul Award. Advising and Grants: Supervised students including E. Pürmayr (Diploma Thesis 2025). Active in EU projects (TARGET, ARMADA) and grant coordination. Labs/Teams: DMKI Lab at TU Wien, collaborating with interdisciplinary teams in healthcare and environmental science.

• Knowledge Graphs
• Semantic Web
• Data Management
• +7 more

Christoph H. Lampert is a Professor at the Institute of Science and Technology Austria (ISTA), leading the Machine Learning and Computer Vision (MLCV) Group. His research spans machine learning, computer vision, and trustworthy AI with emphasis on robustness and fairness. He serves as ELLIS Fellow and Unit Director for ISTA's ELLIS unit. His research program focuses on foundational challenges in machine learning including robustness against distribution shifts, fairness in algorithmic decision-making, and verification of neural networks. Key contributions include work on 1-Lipschitz networks for robust classification, multi-source learning frameworks, and federated learning architectures. The group maintains strong output in top-tier venues through theoretical and empirical approaches. Recent publications (2023-2025) demonstrate consistent focus on verification, robustness, and multi-source learning, with notable recognition including the DARPA Disruptive Ideas award for logic gate neural network verification. Work frequently bridges computer vision and machine learning theory, with applications in safety-critical systems. Scientific Awards: ELLIS Fellow DARPA Disruptive Ideas award at NeuS (2025) for "Logic Gate Neural Networks are Good for Verification" Professor Lampert has supervised 12+ PhD students including recent graduates Alex Peste (2023), Nikola Konstantinov (2022), and Mary Phuong (2021), with current advisees including Max Cairney-Leeming and Egor Zverev. His group secures consistent publication placements at NeurIPS, ICML, and ICLR while editing major volumes like "Advanced Structured Prediction" (MIT Press 2015). The MLCV group comprises 10+ members including postdocs and PhD students, operating within ISTA's ELLIS unit (approved 2019). The team maintains active collaborations across Europe through the ELLIS network and regularly hosts visiting researchers.

• Machine Learning
• Computer Vision
• Robust Machine Learning
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Maria Chudnovsky is a Professor of Mathematics at Princeton University and a former Professor of IEOR and Mathematics at Columbia University (2006-2014). Her research focuses on graph theory and combinatorics, with significant contributions to structural graph theory, perfect graphs, and algorithmic applications. Education: B.A. Summa Cum Laude (1996) and M.Sc. (1999) from Technion, Ph.D. (2003) from Princeton University Her work addresses fundamental problems in graph coloring, forbidden induced subgraphs, and combinatorial optimization, including the proof of the Strong Perfect Graph Theorem and development of algorithms for detecting graph structures. Notable awards include the MacArthur Foundation Fellowship (2013-2017), D.R. Fulkerson Prize (2009), and Henry Burchard Fine Professor of Mathematics (2022). She has held prestigious fellowships such as the Clay Mathematics Institute Research Fellowship (2003-2008). Grants: NSF DMS-EPSRC Grant DMS-2120644 (2021-2024), US Army Research Office Grant W911NF-16-1-0404 (2016-2020), and multiple NSF grants She has advised numerous PhD/MSc students and postdocs, including Sophie Spirkl, Mingxian Zhong, and Tara Abrishami. Her outreach includes popular science communication on YouTube's Numberphile and participation in initiatives promoting women in STEM.

• Graph Theory
• Combinatorics
• Discrete Mathematics
• +3 more

Wojciech Rytter is a full professor at the Institute of Informatics, Department of Mathematics and Informatics at the University of Warsaw, Poland, holding this position continuously since October 1971. His academic career includes significant international appointments as full professor at New Jersey Institute of Technology (2002-2004), Liverpool University (1997-2002), and Bonn University (1994-1995), and as visiting professor at University of California, Riverside (1992-1993) and University of Warwick (1985-1986). He earned his MSc in 1971, PhD in 1975, habilitation in 1985, and was awarded the scientific degree of professor in 1997, all from Warsaw University. Professor Rytter's research focuses on the design and analysis of computer algorithms, with particular expertise in automata and formal languages, parallel algorithms, and text algorithms. His work spans efficient sequential and parallel algorithms, automata theory, complexity of recognition and parsing of context-free languages, pattern matching, algorithmics of WWW, parallel combinatorial computing, graph-theoretic algorithms, and algorithmics of highly compressible objects. His theoretical contributions have practical applications in computational biology, bioinformatics, and text processing systems. His recent publications (2022-2025) demonstrate continued activity in string algorithms, particularly in pattern matching, string covers, and combinatorics on words, with a strong focus on theoretical computer science with applications in bioinformatics. 200 problems on automata, languages, computations (Cambridge University Press 2023) 125 Problems in Text Algorithms (Cambridge University Press, 2021) Jewels of Stringology (World Scientific, 2002) Fast parallel algorithms for matching problems in graphs (Oxford University Press 1998) Text algorithms (Oxford University Press 1994) Professor Rytter has collaborated extensively with researchers including Jakub Radoszewski, Tomasz Walen, Tomasz Kociumaka, and Maxime Crochemore. He is a member of the Academy of Europe (elected 2011, Informatics section) and has authored or co-authored more than 130 publications. He maintains an active research laboratory focused on string algorithms and combinatorics on words at the University of Warsaw.

• Design and analysis of computer algorithms
• Automata and formal languages
• Parallel algorithms
• +5 more

Cao Jiannong is currently a Chair Professor and Director of the University Research Facility in Big Data Analytics at Hong Kong Polytechnic University . He has held academic roles including Assistant Professor at City University of Hong Kong and University Lecturer at the University of Adelaide and James Cook University. His research spans Cloud and Edge Computing , Parallel and Distributed Systems , Big Data Analytics , and Wireless Sensing . Ph.D. in Computer Science, Washington State University (1990) MSc in Computer Science, Washington State University (1986) BSc in Computer Science, Nanjing University, China (1982) His work focuses on solving theoretical and practical challenges in distributed computing , mobile cloud systems , and wireless sensor networks . Recent projects include coupled network embedding models for heterogeneous networks and SDN architectures for vehicular communication. His research also pioneers WiFi-based non-invasive health monitoring and fault-tolerant sensor deployment for structural health applications. Dr. Cao's publications highlight advancements in network embedding , edge computing , and WSN optimization . Key papers address multi-user computation partitioning , energy-efficient SHM systems , and consensus protocols for mobile networks. These works have been cited over 15,000 times, with an h-index of 60. Ministry of Education (China) Natural Science Award (2018) Distinguished Member, ACM (2017) Fellow, IEEE (2014) Best Paper Awards at IEEE DSAA, SMARTCOMP, and WCNC Dr. Cao has advised multiple PhD students, including Linchuan Xu and Weigang Wu , whose research on WSN-based SHM and coupled network embedding has practical impact. His leadership includes directing Hong Kong Polytechnic University's Big Data Research Facility and serving on technical committees for IEEE INFOCOM and ACM/IEEE conferences.

• Cloud and edge computing
• Parallel and distributed computing
• Big data analytics
• +2 more

Gene Tsudik is a Distinguished Professor of Computer Science at the University of California, Irvine (UCI), with a career spanning over two decades. He obtained his Ph.D. in Computer Science from the University of Southern California (USC) in 1991, focusing on access control in the Internet. His research spans multiple areas including computer and network security, applied cryptography, and digital privacy, with a recent emphasis on database privacy, genomic privacy, and usable security. His notable contributions include the Inter-Domain Policy Routing (IDPR) protocol, KryptoKnight for network security, and Tree-Based Group Key Agreement protocols. He has over 210 publications and 8 patents. From 2002 to 2007, he served as Associate Dean of Research and Graduate Studies at UCI's School of Information and Computer Sciences and currently directs the UCI Secure Computing and Networking Center (SCONCE). Research Keywords : Cybersecurity, Cryptography, Privacy, Network Security, Digital Signatures, Genomic Data Protection. Scientific Awards : IEEE Fellow (2012), ACM Fellow (2014), AAAS Fellow (2016), Fulbright Senior Scholar (2007), and IFIP Fellow (2020). Professor Tsudik has supervised 18 PhD students and held visiting positions at universities across Europe and Asia. His recent publications focus on secure hardware attestation, biometric authentication, and social media data privacy.

• Computer and network security
• Cryptopoetry
• Internet security and privacy
• +2 more