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).
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.
Lam James is a Chair Professor of Control Engineering at the University of Hong Kong (HKU), affiliated with the Faculty of Engineering. He holds a BSc (1st Hons.) in Mechanical Engineering from the University of Manchester, and MPhil/PhD degrees from the University of Cambridge. His academic journey includes roles as a Croucher Fellow, Lecturer at the University of Melbourne, and faculty member at City University of Hong Kong before joining HKU in 1993. Professor Lam serves as Editor-in-Chief for four international journals including IET Control Theory and Applications and Journal of The Franklin Institute . His research focuses on networked control systems, vibration control, control theory, and multi-agent systems. With 600+ peer-reviewed publications, he maintains an H-index of 102 (Web of Science) and 108 (Scopus), recognized as a Highly Cited Researcher in multiple fields. Education: BSc Manchester (Mechanical Engineering), MPhil/PhD Cambridge Editorial Roles: 20+ journals, including leadership roles since 2012 His awards include Foreign Membership of Academia Europaea (2024), National Academy of Artificial Intelligence membership (2025), and two State Natural Science Awards (2015, 2019). He is a Fellow of multiple institutions including IEEE, IMechE, and HKIE.
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.
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.
Jiannong Cao is a Chair Professor and Director of the University Research Facility in Big Data Analytics at the Department of Computing, Hong Kong Polytechnic University. He has held various academic roles since 1990, including Assistant Professor at City University of Hong Kong and Lecturer at Australian universities. PhD in Computer Science, Washington State University (1990) MSc in Computer Science, Washington State University (1986) BSc in Computer Science, Nanjing University (1982) His research focuses on cloud and edge computing , parallel and distributed computing , and mobile computing , with significant contributions to wireless sensor networks (WSN) for structural health monitoring (SHM) and software-defined networking (SDN) for vehicular communications. Recent work includes WiFi-based non-invasive health monitoring systems and multi-user computation partitioning in mobile cloud environments. Dr. Cao’s publications demonstrate trends in WSN optimization , SDN architectures , and cognitive modeling for network embedding , with applications in smart healthcare , transportation systems , and industrial IoT . Ministry of Education Natural Science Award (2018) ACM Distinguished Member (2017) IEEE Fellow (2014) Best Paper Awards at IEEE DSAA, SMARTCOMP, WCNC He has mentored numerous researchers, including Linchuan Xu , Xuefeng Liu , and Weigang Wu , who have authored key publications in top venues like ACM WSDM and IEEE INFOCOM . His professional roles include chairing IEEE committees and serving on grant panels for the Hong Kong Research Grant Council.
Prof. Tina Wakolbinger is a Professor at Vienna University of Economics and Business (WU) , where she serves as Deputy Head of the Institute for Transport Economics and Logistics and Head of the Supply Chain Management Research Institute. She also chairs the Senate and has led numerous research projects in supply chain management, humanitarian logistics, and the circular economy. PhD in Business Administration, Isenberg School of Management, UMASS Amherst (2007) Mag. in International Economics, University of Innsbruck (2002) Her research focuses on Supply Chain Management , with an emphasis on Humanitarian Logistics and the Circular Economy . She investigates how operational settings and disaster characteristics affect supply chain resilience, explores sustainable urban mobility solutions like electric scooters, and develops frameworks for resource allocation in disaster relief. She has published extensively on topics including disaster preparedness, outsourcing in humanitarian logistics, and the impact of digitalization on sustainable supply chains. Recent publications highlight trends in 2025 with strategic dependencies in supply chains, 2023 contributions to circular economy models and humanitarian logistics assessments, and 2022 analyses of pandemic-era supply chain disruptions. Earlier work includes studies on sustainable freight transport, e-waste management, and risk-sharing contracts. Scientific Awards Literati Award 2020 (Journal of Humanitarian Logistics) WU Cooperation Officer of the Year 2018 Talent promotion bonus of Upper Austria 2011 Best Paper Award 2008 (Fogelman College of Business) Graduate School Fellowship 2006 (UMASS Amherst) She has been involved in external positions such as Member of the Post Control Commission (2022–2027) and advisory roles for Caritas Österreich and Finland’s Strategic Research Council. Current projects include developing circular business models for timber supply chains and optimizing e-scooter fleet management in Vienna.
Edgar Weippl is a Professor at the Faculty of Computer Science, University of Vienna, where he serves as Vice Dean and Head of the Research Group Security and Privacy. His work spans cybersecurity, blockchain, and machine learning, with teaching roles in information security and software security courses. Current Positions: Vice Dean (Faculty of Computer Science), Head (Security and Privacy Research Group), Deputy Head (Neuroinformatics & Knowledge Engineering Groups) Research Interests: Cybersecurity, blockchain, IoT security, code obfuscation, privacy technologies, reinforcement learning, and socio-technical systems security Selected Publications: Focus on blockchain privacy, VoWiFi security, code obfuscation, and reinforcement learning applications
Ulrich Schmid is a Full Professor and Head of the Research Unit for Embedded Computing Systems at TU Wien. He holds a position in the Faculty of Informatics and leads the department of Embedded Computing Systems (E191-02). His roles include Curriculum Coordinator for the Bachelor and Master programs in Computer Engineering, as well as the Excellence Program Bachelor with Honors. He is also the Chair of the Curriculum Commission for Computer Engineering and a Substitute Member of the Informatics Commission. His research focuses on fault-tolerant distributed algorithms, digital integrated circuits, and topology-based approaches to distributed systems. He coordinates major projects such as the FWF-funded DMAC (2019–2024) and ByzDEL (2020–2025), which integrate topological semantics and hybrid delay models for robust hardware design and distributed system analysis. Schmid has contributed to groundbreaking work in Byzantine fault tolerance, epistemic logic for system recovery, and real-time scheduling through collaborations with researchers like Chatterjee, Függer, and Rajsbaum. Notable awards include the 2018 Edsger W. Dijkstra Prize and the 2021 Principles of Distributed Computing Doctoral Dissertation Award. His research also bridges formal verification techniques with physical hardware implementations, exemplified by projects like HEX (a Byzantine-tolerant clock distribution system) and the Involution tool for timing analysis. Schmid actively contributes to academic governance, advancing rigorous education and research standards in computer engineering. His advising and grant work involve mentoring on fault-tolerant architectures and securing funding from agencies like FWF and the European Commission. Labs and teams under his leadership include the Embedded Computing Systems group, specializing in hardware-software co-design for dependable systems-on-chip, and collaborations with institutions like GSI Helmholtzzentrum and the University of Amsterdam.
Prof. Ulrich Schmid is a full professor at TU Wien, affiliated with the Forschungsbereich Embedded Computing Systems. His research focuses on distributed systems, fault-tolerant computing, and asynchronous algorithms. He leads projects like 'Asynchronous Distributed Algorithms in the Theta-Model' and 'Gracefully Degrading Agreement in Directed Dynamic Networks.' Prof. Schmid has received honors at TU Wien and actively supervises numerous students in PhD and Master's programs. His academic work spans theoretical foundations (e.g., epistemic logic in Byzantine systems) and practical applications (e.g., digital circuit delay modeling). Key contributions include hybrid delay models for integrated circuits and formal verification frameworks for timed circuits. Collaborations involve institutions like the Institut für Technische Informatik and the E191-02 research group. Notable research areas: Byzantine fault tolerance, consensus protocols, and embedded systems Leadership in 4 major projects addressing distributed computing challenges Recipient of TU Wien honors (2021) Prof. Schmid's lab emphasizes bridging theoretical computer science with hardware-software co-design, producing over 220 publications and 10+ supervised theses since 2000.
Beng Chin Ooi is a Lee Kong Chian Centennial Professor at the National University of Singapore (NUS), School of Computing. He has been with NUS since 1991, progressing through the ranks from Lecturer to his current distinguished position. He previously served as Dean of the School of Computing from 2007 to 2013 and as Director of the Smart Systems Institute from 2011 to 2021. His educational background includes: 1985: B.Sc. (1st Class Honors) from Monash University, Melbourne, Australia 1989: Ph.D. in Computer Science from Monash University, Melbourne, Australia Beng Chin Ooi's research focuses on database systems, large scale analytics, and distributed systems. His work has been instrumental in advancing the field of data management technology, particularly in the context of "big data" in large-scale parallel and distributed systems. He has made significant contributions to spatio-temporal and distributed data management, as well as pioneering research in distributed database management and peer-to-peer based enterprise quality management. His recent publications demonstrate a strong focus on blockchain technology, machine learning systems, and healthcare informatics. There's a clear progression from foundational database research to applications in emerging technologies like blockchain and AI. His work bridges theoretical advances with practical system implementations, as evidenced by multiple open-source projects associated with his publications. His notable awards include: 2021: NUS Research Recognition Award 2020: ACM SIGMOD E.F. Codd Innovations Award 2020: ACM SIGMOD Research Highlight Award 2019: VLDB Best Paper Award 2016: Fellow of Singapore National Academy of Science 2016: China Computer Federation Overseas Outstanding Contributions Award 2014: VLDB Best Paper Award 2014: IEEE TCDE CSEE Impact Award 2013: Singapore National Day's Public Administration Medal (Silver) 2013: NUS Outstanding Researcher Award 2012: IEEE Computer Society Kanai Award 2011: ACM Fellow 2011: Singapore President's Science Award 2009: IEEE Fellow 2009: ACM SIGMOD Contributions Award Throughout his career, Professor Ooi has demonstrated exceptional leadership in the database community, promoting high standards of database research at both international and regional levels. His BLOCKBENCH framework became the world's first benchmarking tool for private blockchains, and his work on data provenance on blockchain systems earned both the VLDB Best Paper Award and the ACM Research Highlight Award. He has led several major research initiatives, including the Smart Systems Institute at NUS. Professor Ooi has established multiple open-source projects including FabricSharp for blockchain data provenance and Cool for cohort online analytical processing. His research group has consistently produced high-impact work that bridges theoretical advances with practical system implementations.
Professor Jana Lasser holds a professorship in Data Analysis at the University of Graz, where she leads the Complex Social & Computational Systems research group at the interdisciplinary IDea_Lab. She serves as Associate Faculty at the Complexity Science Hub Vienna and previously held positions at Graz University of Technology as a Marie Curie Fellow and interim professor at RWTH Aachen. Her educational background includes a PhD in Physics from Georg-August-University Göttingen (2019), conducted at the Max Planck Institute for Dynamics and Self-Organization, with research on salt desert pattern formation. Her academic journey reflects a transition from geophysics to computational social science. Lasser's research centers on emergent phenomena in complex social systems, employing machine learning, natural language processing, and computational modeling. Key interests include misinformation spread on social media, counterspeech effectiveness, social media recommendation algorithms' societal impact, and the fracturing of societal understanding of honesty. Her work combines theoretical frameworks with real-world applications through agent-based simulations and large-scale text analysis. Her recent publications reveal strong thematic coherence across computational social science, with significant focus on political communication dynamics, platform governance, and methodological innovation. The 15 most recent works demonstrate increasing integration of computational methods with social theory, particularly in analyzing truth-concept evolution in political discourse and developing alternative social media architectures. ERC Starting Grant 101160928 DeSiRe for designing social media recommendation algorithms FWF standalone project P 37280-N on conspiracy theory spread netidee SCIENCE prize for digital civic innovation Marie Curie Fellowship for postdoctoral research Lasser actively supervises graduate students in computational social science, with current focus on topics related to her ERC-funded project. She leads the Survey Special Interest Group within the COST Action on Researcher Mental Health, conducting Europe's largest benchmark study on academic mental health. Her lab maintains strong collaborations with the Complexity Science Hub Vienna and international institutions.
Giulia Scaffino is a PreDoc Researcher in the Security and Privacy group at the Technical University of Vienna (TU Wien). Her research focuses on cryptocurrencies, blockchain interoperability, scalability, off-chain protocols, and decentralized finance (DeFi). She holds an MSc in Nuclear and Particle Physics from the University of Pavia, Italy, and is pursuing a PhD at TU Wien. Before her PhD, she worked as a Salesforce developer at Deloitte Digital in Milan. Giulia is involved in projects such as CDL-BOT (2020–2025), Browsec (2018–2024), CoRaF (2022–2025), and SFB SPyCoDe (2023–2026). Her work includes developing frameworks for cross-blockchain smart contracts, optimizing light clients for DeFi, and creating scalable blockchain bridges. She has contributed to publications on topics like IoT data marketplaces and distributed key generation using zk-SNARKs. Her research trends emphasize solving blockchain scalability challenges through innovative protocols and enhancing interoperability between different blockchain systems. Projects like Glimpse and Alba highlight her focus on efficient, secure, and decentralized solutions for modern blockchain ecosystems.
Peter Winkler serves as a University Professor in the Department of Communication Science at Paris Lodron University Salzburg. His academic profile demonstrates extensive engagement with contemporary communication challenges, particularly focusing on digital transformation's impact on strategic and organizational communication systems. With continuous scholarly output from 2008 through projected 2025 publications, he maintains active research leadership in the field. Professor Winkler's research interests center on strategic communication in digital environments, with particular expertise in organizational communication, public relations evolution, and digital media strategies. His work critically examines the political dimensions of integrated communication systems, exploring how micro-political dynamics and ideological frameworks shape corporate communication practices. He investigates the paradoxical nature of digital transformation in public relations, analyzing tensions between control demands and flexibility requirements in contemporary communication strategies. His recent publication trajectory reveals a pronounced focus on digitalization challenges in strategic communication, with increasing attention to political dimensions of corporate communication and organizational emergence through communication processes. The VUCA framework appears as a significant conceptual tool in his latest work, reflecting adaptation to volatile, uncertain, complex, and ambiguous communication environments. Dissertationspreis der DGPuK Fachgruppe Public Relations und Organisationskommunikation (2015) EUPPRERA Best Paper Award (2016, 2020, 2022, 2023) Professor Winkler actively contributes to academic discourse through substantial peer review activities for journals including Journal of Communication Management, Business & Society, and Journal of Business Ethics. He serves as project manager for multiple significant research initiatives, notably DigInfluAd Austria and the DIGISKILLS series examining digital competencies in Austria. His advisory activities include participation in habilitation committees and expert assessments, demonstrating institutional leadership beyond direct research contributions.
Jasmin Wachter is a Researcher at the Institute for Artificial Intelligence and Cybersecurity at Alpen-Adria-Universität Klagenfurt. Her work focuses on interdisciplinary research at the intersection of cybersecurity, machine learning, and game theory. She holds a Diplom-Ingenieur (Dr.) and dual undergraduate degrees (BSc, BA), reflecting her multidisciplinary background. Her research interests span critical areas such as IT security, data science, cryptology, and risk management. She contributes to advancing methodologies for secure systems, adversarial modeling in cybersecurity, and ethical AI frameworks. Her recent publications highlight innovations in attack graph modeling, security game theory applications, and human-robot collaboration safety protocols. While currently affiliated with the Faculty of Technical Sciences, her work emphasizes both foundational research and practical solutions for modern cybersecurity challenges. She is actively involved in the institute's research initiatives, though no specific awards or student advisement roles are documented in the provided materials.
