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).
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.
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.
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.
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.
Olaf Steinbach is a University Professor (Univ.-Prof.) at the Institute of Applied Mathematics at Graz University of Technology. His academic career spans over three decades with continuous research activity from 1992 to the present, including publications scheduled for 2026. He serves as a project manager for several research initiatives including the Special Research Area (SFB) F90 Computational Electric Machine Laboratory, which runs from 2022 to 2026. Professor Steinbach's research interests primarily focus on Numerical Analysis and Computational Mathematics . His work centers around developing and analyzing advanced numerical methods, particularly Finite Element Methods (FEM) and Boundary Element Methods (BEM), for solving partial differential equations (PDEs) and optimal control problems. His research spans both theoretical aspects (such as error analysis, stability, and convergence) and practical applications (including electric machines, electromagnetics, and biomechanics). He has made significant contributions to space-time finite element methods, which treat time as an additional dimension in the discretization process, leading to more robust and efficient solvers for time-dependent problems. Analysis of his recent publications (2021-2026) reveals a strong focus on optimal control problems governed by partial differential equations, with particular emphasis on elliptic, parabolic, and hyperbolic PDEs. His work demonstrates a consistent pattern of developing robust numerical methods with rigorous error analysis, often incorporating regularization techniques to handle challenging constraints. The applications span computational electromagnetics (particularly electric machines), fluid dynamics, and wave propagation problems. His research increasingly incorporates advanced computational techniques including parallel computing and isogeometric analysis. Professor Steinbach has supervised numerous doctoral students and has been actively involved in organizing academic events, including summer schools on Boundary Element Methods. His collaborative network extends across multiple disciplines and institutions, reflecting the interdisciplinary nature of his work in computational mathematics. His research has been supported through multiple significant projects including DK-W1244 Doctoral Program on Partial Differential Equations, the EU CASOPT project on optimization of industrial devices, and the ongoing Special Research Area on Computational Electric Machine Laboratory. These projects demonstrate his leadership in establishing research frameworks that bridge theoretical mathematics with practical engineering applications. Professor Steinbach maintains an active research group within the Institute of Applied Mathematics, collaborating closely with researchers in computational engineering, electrical engineering, and biomechanics. His work on the Computational Electric Machine Laboratory represents a particularly strong interdisciplinary effort combining mathematical theory with electrical engineering applications.
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.
Gheorghe Paun is a Senior Researcher at the Institute of Mathematics of the Romanian Academy (1994–present) and a Visiting Researcher at the University of Sevilla (2009–present). He earned his Ph.D. in Mathematics from the University of Bucharest (1977), supervised by Solomon Marcus. His research spans Automata and Language Theory (descriptional complexity, regulated rewriting), Natural Computing (DNA computing, membrane computing), and he is the initiator of membrane computing . Education : M.Sc. in Mathematics (1974), University of Bucharest (specialization: computer science) Ph.D. in Mathematics (1977), University of Bucharest His work includes foundational contributions to DNA computing (book DNA Computing. New Computing Paradigms , 1998) and membrane computing (book Membrane Computing. An Introduction , 2002). He has collaborated with over 100 researchers globally and advised multiple Ph.D. students, including Victor Mitrana and Gianina Georgescu. His scientific awards include the Gheorghe Lazar award (1981), Corresponding Member of the Romanian Academy (1997), Doctor Honoris Causa from Silesian University of Opava (2007), and recognition as an ISI Highly Cited Scientist (2007). He also holds honorary citizenships in Curtea de Arges (1998), Arges County (2007), and Cicanesti village (2009). Paun has served on editorial boards for journals like Theoretical Computer Science. Natural Computing Series and Natural Computing , and organized major workshops in membrane computing. His academic contributions include over 150 publications and editorial roles in 20+ journals.
Prof. Maosong Sun is a Professor at the Department of Computer Science and Technology, Tsinghua University, China. He holds additional leadership roles including Executive Vice Dean of the Institute for Artificial Intelligence and Deputy Director of the National Engineering Laboratory for Cyberlearning and Intelligent Technology. His research focuses on natural language processing (NLP), artificial intelligence, machine learning, and computational education. He leads interdisciplinary projects in computational humanities, knowledge graphs, and MOOC platforms like XuetangX, which has over 58.8 million registered learners. Key contributions include pioneering work in Chinese NLP tools, poetry generation systems like Jiuge, and large-scale research initiatives funded by Chinese and Singaporean programs. Awards include the Tsinghua University Education Award (2019) and the National Outstanding Practitioner Award (2007). Established NLP and Computational Humanities & Social Sciences Lab (2008) Co-director of the Joint Research Center for Extreme Search (2011-present) Over 200 publications with 11,000+ citations (h-index 47)
Emanuel Sallinger is a Full Professor at TU Wien's Databases and Artificial Intelligence Group and Vice Dean of Academic Affairs for Business Informatics and Data Science. He leads the Knowledge Graph Lab, focusing on scalable knowledge-based systems, reasoning in knowledge graphs, and AI integration. His research spans computational logic, database theory, and blockchain applications. Education: PhD in Computer Science (awarded 'sub auspiciis praesidentis rei publicae'), Master's degrees in Computational Intelligence and Informatics Management, and a Bachelor's in Software and Information Engineering. Research Interests: Knowledge graphs (construction, reasoning, scalability), logic-based systems, AI/ML integration with databases, enterprise architecture modeling, and financial knowledge systems. His work emphasizes practical applications like enterprise modeling, sustainable waste management, and regulatory compliance. Grants & Projects: Lead Vienna Science and Technology Fund (WWTF)-funded Knowledge Graph Lab. Involved in projects like 'Knowledge Graph-driven Tour Management' (sustainability), 'SustainGraph' (waste processing), and 'Enterprise Architecture Knowledge Graphs'. Teaching: Offers courses on Knowledge Graphs, Generative AI, Database Systems, and research methodology. Supervises doctoral and master's students in AI, databases, and knowledge representation. Labs/Teams: Knowledge Graph Lab at TU Wien, collaborating with industry on blockchain-based systems, financial AI, and enterprise architecture frameworks.
Viktor Prasanna is the Charles Lee Powell Chair in Engineering and Professor of Electrical and Computer Engineering and Computer Science at the University of Southern California. He holds courtesy appointments in Computer Science and leads the Center for Energy Informatics, focusing on interdisciplinary research linking energy technologies, computer science, and engineering. Education: BE in Electronics (Bangalore University), ME (Indian Institute of Science), PhD in Computer Science (Pennsylvania State University) His research spans reconfigurable computing, FPGA accelerators, parallel and distributed systems, and big data applications. He has pioneered high-performance architectures and algorithms using FPGAs, impacting domains like networking, security, HPC, and machine learning. Prasanna has published over 600 papers, received 22 best paper awards, and secured >$50M in grants. His work emphasizes energy-efficient computing, with recent grants totaling $12.9M (2016–2021). His h-index is 73, with 23,454 total citations. Scientific Awards: IEEE Fellow, ACM Fellow, AAAS Fellow, W. Wallace McDowell Award, multiple Distinguished Alumnus Awards He has advised over 70 doctoral students and led major centers including CiSoft (Big Data in oilfield tech) and CAST. His editorial roles include Editor-in-Chief of IEEE Transactions on Computers and Journal of Parallel and Distributed Computing.
Prof. Dr. Christopher Markiewicz is a leading scholar in Ottoman and Islamic Studies at Ghent University's Department of Languages and Cultures (affiliated with the Department of History). He previously held positions as Associate Professor at University of Birmingham and Junior Research Fellow at Exeter College, University of Oxford. His research centers on the political, social, and intellectual history of the Ottoman Empire (15th-17th centuries), with special emphasis on state formation, diplomatic cultures, and the interplay between Islamic law and governance. Education PhD in Near Eastern Languages & Civilizations, University of Chicago (2015) Magna cum laude dissertation award from Middle East Studies Association (2016) His scholarship explores the transition from medieval Islamic political fragmentation to early modern imperial consolidation , focusing on how Persian émigrés shaped Ottoman sovereignty and diplomatic practices. Current research investigates pious endowments (waqf) through an ERC Starting Grant (2023-2028) , analyzing their role in Ottoman state-building. Scientific contributions include: Winner of Malcolm H. Kerr Dissertation Award (2016) Principal Investigator for Islamic Endowments project Series Editor for The Ottoman Empire and the World (I.B. Tauris) Trustee of EJW Gibb Memorial Trust Member of British Institute at Ankara committees His 2023-2024 teaching includes courses on Middle East politics and global historical developments. Publications reveal evolving research from waqf taxation controversies to diplomatic gift-giving protocols, with consistent focus on cross-cultural exchange and historiographical evolution.
Marc Pollefeys is a Full Professor of Computer Science at ETH Zurich and Director of the Microsoft Mixed Reality and AI Zurich Lab. He has held roles such as Visiting Professor at Stanford University (2007) and Assistant/Associate Professor at UNC-Chapel Hill (2002–2009). His research focuses on 3D computer vision, robotics, machine learning, and augmented reality. Education: PhD in Computer Science from KU Leuven (1999), followed by postdoctoral research there until 2002. He transitioned to academic roles at UNC-Chapel Hill before joining ETH Zurich in 2007. Research interests include 3D reconstruction, visual localization, SLAM, and applications in archaeology, urban modeling, and robotics. Notable projects include real-time 3D scanning, city-scale reconstruction, and autonomous vision-based drones. Key awards include ACM Fellow (2022), IEEE Fellow (2012), and ERC Starting Grant (2008). He advises numerous PhD students and collaborates with institutions like Google and Microsoft. Labs and teams: Leads the Computer Vision and Geometry (CVG) lab at ETH Zurich and directs the Microsoft Mixed Reality and AI Lab. His work bridges academia and industry, focusing on perception for mixed reality and autonomous systems.
Sylvain Lefebvre is a permanent researcher at INRIA (Institut National de Recherche en Informatique et en Automatique) in France, where he leads the MFX research team since 2018. Previously, he was part of the ALICE group at INRIA Nancy (2009-2018) and the REVES team in Sophia Antipolis (2006-2009). His career includes a postdoctoral position at Microsoft Research Seattle (2005) following his PhD at INRIA Rhones-Alpes under Fabrice Neyret. His educational background includes a PhD in Computer Graphics from Université Joseph Fourier (Grenoble) in 2005, preceded by a Master in Computer Graphics from INP Grenoble in 2001. His habilitation thesis focused on Runtime Texture Synthesis. Lefebvre's research centers on simplifying content creation for highly detailed patterns, structures, and shapes with applications spanning Computer Graphics to additive manufacturing. He develops fast, controllable by-example synthesis approaches that generate content while enforcing user-specified constraints. His work addresses computational challenges through novel data structures and algorithms optimized for GPUs and FPGAs, including his Silice programming language. The ERC-funded ShapeForge project (2012-2017) advanced shape generation for 3D printing, leading to the IceSL software for digital modeling and fabrication. Analysis of his 15 most recent publications reveals a strong focus on additive manufacturing optimization, with recurring themes in structural integrity, material efficiency, and geometric algorithms. His work bridges computer graphics theory with practical fabrication constraints, particularly in microstructure design, slicing techniques, and mechanical metamaterials. The interdisciplinary nature spans computer science, materials engineering, and robotics. EUROGRAPHICS Young Researcher Award (2010) ERC Starting Grant for ShapeForge project (2012) Lefebvre has advised over 25 PhD students and interns including Marco Freire, Thibault Tricard, and Jimmy Etienne. His ShapeForge project received significant ERC funding, supporting research in computational fabrication. He serves on numerous program committees including SIGGRAPH, Eurographics, and SIGGRAPH Asia, reflecting his leadership in the computer graphics community. As leader of the MFX team since 2018, Lefebvre directs research in computational fabrication, focusing on IceSL software development for 3D printing workflows. The team integrates computer graphics techniques with manufacturing constraints, developing tools that simplify complex object design and fabrication while addressing real-world challenges in material usage and structural integrity.
