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.
Dr. Yunjie Yang is an Associate Professor at the University of Edinburgh's School of Engineering, with affiliations at the Edinburgh Futures Institute (EFI), the Edinburgh Generative AI Laboratory (GAIL), and the Edinburgh Centre for Robotics. He previously held the Chancellor's Fellow in Data Driven Innovation (2018-2023) and Bayes Innovation Fellow (2023-2024) positions. His research focuses on AI-powered sensing and imaging, machine learning, and soft sensors & electronics for robotics. Yang received his PhD in Engineering Electronics from the University of Edinburgh, MSc in Control Science & Engineering from Tsinghua University, and BEng in Measurement & Control Engineering from Anhui University. After his PhD, he worked as a Postdoctoral Research Associate in Chemical Species Tomography before securing his lectureship. His research interests center on developing intelligent sensing systems that replicate human perception capabilities for robotics and intelligent systems. He pioneers flexible sensing and imaging technologies across various scales through innovative multi-modal sensors, soft electronics, and their modeling using machine learning approaches. His work aims to enable autonomous physical artificial intelligence by bridging the gap between robotic systems and human-like perception. Analysis of his recent publications reveals a strong focus on soft robotics perception, particularly through electrical impedance tomography (EIT) and transformer-based architectures. His research spans medical imaging applications, digital twin modeling for industrial processes, and machine learning approaches for sensor data interpretation. The trend shows increasing integration of physics-informed deep learning with traditional tomographic techniques to achieve higher accuracy and efficiency. European Research Council (ERC) Starting Grant (2024) IEEE J. Barry Oakes Advancement Award (2024) IEEE I&M Society Graduate Fellowship Award (2015) Multiple Best Paper Awards Senior Member of IEEE Fellow of the International Society for Industrial Process Tomography Fellow of the Higher Education Academy ESI highly cited papers Dr. Yang serves as Associate Editor for IEEE Transactions on Instrumentation and Measurement and holds editorial positions with Scientific Reports and IEEE Sensors Journal. His research has been licensed to overseas research institutes and industry partners and received wide media coverage including BBC, EFE, USA Today, and STV. He has secured significant grant funding including the prestigious ERC Starting Grant. He leads the Edinburgh SMART Lab (Sensing/imaging + Machine Learning + Robotics), which aims to replicate human perception capabilities for robotics and advance flexible sensing technologies through innovative multi-modal sensors and machine learning approaches. The lab focuses on enabling autonomous physical artificial intelligence with applications spanning medical diagnostics, industrial monitoring, and advanced robotics systems.
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
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.
Matteo Maffei is a Full Professor at TU Wien, leading the Security and Privacy group. He joined in 2017 after 11 years at Saarland University's CISPA. He holds a Ph.D. in Computer Science from Ca’ Foscari University of Venice (2006). He coordinates the TU Wien Cybersecurity Center, the SecInt Doctoral School, and the FWF Special Research Program SPyCoDe. His research focuses on formal methods for security and privacy, blockchain technologies, and web security. Roles: Full Professor, Coordinator of TU Wien Cybersecurity Center, Module Head of Christian Doppler Lab for Blockchain Technologies (CDL-BOT), Board Member of Vienna Cybersecurity and Privacy Research Cluster (ViSP). His work emphasizes formal verification of cryptographic protocols, smart contracts, and decentralized systems. Key achievements include ERC Advanced (2024) and Consolidator (2018) Grants, and leadership roles in conferences like IEEE Computer Security Foundations Symposium (CSF). Research Interests: Formal methods, smart contracts, blockchain scalability, web security, privacy-preserving protocols, and decentralized systems. His recent projects include optimizing Lightning Network channels, secure multi-hop payments, and AI-driven robustness verification. Publications: Over 200 publications in top venues like CCS, IEEE S&P, and CRYPTO. Recent work includes advancements in blockchain interoperability (e.g., Alba bridges), light client protocols (Blink), and neural network verification techniques. Grants & Awards: ERC Advanced Grant (2024), ERC Consolidator Grant (2018), DFG Emmy Noether Fellowship (2009). Led projects funded by EU Horizon, FWF, and industry partners like ABC Research GmbH. Advising & Labs: Supervised over 20 PhD/Master theses. Active in the Christian Doppler Lab for Blockchain Technologies and the SPyCoDe SFB. Collaborates with institutions like SBA Research and Stanford University.
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.
Dr. Borivoje Dakic is an Associate Professor at the University of Vienna , affiliated with the Faculty of Physics and the Quantum Optics, Quantum Nanophysics and Quantum Information department. His research spans foundational and applied aspects of quantum theory. Operational reconstruction of quantum formalism Quantum interference as a resource for communication Tomography of large-scale quantum systems Macroscopic quantum phenomena His work includes scalable verification techniques for quantum devices and collaborations with experimental teams like Philip Walther’s and Markus Aspelmeyer’s groups. He received the Marko Jarić Prize (2025) for his contributions. Recent projects focus on diagnostics of quantum devices (FWF BeyondC SFB), information-theoretic foundations of quantum interference (FWF P36994), and local operations in quantum field theory (Cluster of Excellence QuantA). His research on quantum coherence in networks and macroscopic entanglement challenges traditional assumptions about quantum-classical boundaries. Publications emphasize resource-efficient tomography, device-independent verification, and foundational frameworks for quantum statistics and field theory. Teaching: Quantum Information (2025W), Theory in Quantum Optics (2025S), VCQ Summerschool Labs: Dakić Group at University of Vienna
Atakan Aral serves as an Associate Professor at the Faculty of Computer Science, University of Vienna, where he leads research in edge computing, distributed systems, and environmental monitoring applications. His work focuses on developing efficient and resilient computing systems for environmental applications, with particular emphasis on neuromorphic edge AI and the cloud-edge continuum. He maintains an active teaching schedule offering courses in Distributed Systems Engineering, Cloud Computing, and Practical Software Courses with Bachelor's Thesis work across multiple semesters through 2025. Dr. Aral's research interests span several critical areas in modern computing including edge computing architectures, federated learning approaches, neuromorphic computing for environmental monitoring, and resilient systems design. His work addresses fundamental challenges in resource-constrained environments, particularly focusing on latency-sensitive applications and energy-efficient computation. The interdisciplinary nature of his research bridges theoretical computer science with practical environmental applications, developing systems that can operate effectively in remote or resource-limited settings. Analysis of his recent publication trajectory reveals a clear evolution from foundational cloud computing research toward increasingly specialized edge intelligence systems. Early work focused on resource allocation and scheduling in cloud environments, while his current research emphasizes neuromorphic approaches for sustainable environmental monitoring. His publications demonstrate growing interdisciplinary collaboration, particularly with environmental scientists, and increasing focus on practical implementations of theoretical concepts in real-world monitoring systems. Dr. Aral leads significant research projects including TROCI (Towards Resilient Operation of Critical Infrastructure), an ongoing initiative, and SWAIN (Sustainable Watershed Management Through IoT-Driven AI), which ran from February 2021 to February 2024. His work spans multiple dimensions of computing systems, from hardware-aware algorithms to application-level implementations, with consistent contributions to major conferences and journals in distributed systems and edge computing. He is an active member of the Scientific Computing research group at the University of Vienna, working from Room 6.49 at Währinger Straße 29. His research environment includes collaboration with the Environment and Climate Research Hub, reflecting the interdisciplinary nature of his work that bridges computer science with environmental applications. His publications indicate strong international collaboration across European institutions and research groups.
Hongbo Jiang is a Distinguished Professor and Vice Dean of the College of Computer Science and Electronic Engineering at Hunan University, China. He holds concurrent roles as Director of the Trusted Systems and Networking Key Laboratory of Hunan Province and Director of the Hunan International Technical Cooperation Base for High-Performance Computing and Distributed Systems. His academic journey includes tenures as a Professor at Huazhong University of Science and Technology and a Hong Kong Scholar Research Fellow at The Chinese University of Hong Kong. Education: PhD in Computer Science (Case Western Reserve University, 2008), B.S./M.S. in Mathematics (Huazhong University of Science and Technology, 2002). Research Interests: Distributed systems, mobile computing, smart sensing, wireless networks, IoT, and edge computing. Ongoing projects include mobile/wireless applications, data science in IoT, and edge computing platforms. His work emphasizes practical implementations such as DriverSonar for driving safety and SmileAuth for biometric authentication. Key Achievements: Elected Member of Academia Europaea (2022), Fellow of AAIA, IET, and BCS. Notable awards include the Wu Wenjun Science and Technology Award (2020) and multiple best paper recognitions. Over 100+ publications in top venues like ACM MobiCom, IEEE/ACM Transactions. Professional Contributions: Editorial roles across 8+ journals including IEEE Transactions on Mobile Computing and ACM Transactions on Sensor Networks. Conference leadership includes co-founding ACM TURC and EAI ICECI. Active in technical committees for INFOCOM, MOBIHOC, and ICDCS. Labs/Teams: Leads research groups focused on networking, IoT, and edge computing. Current openings for PhD/MSc students and PostDoc researchers with strong mathematical and systems backgrounds.
Hannes Hick is a Professor at Graz University of Technology , affiliated with the Institute of Machine Elements and Development Methodology . His research focuses on mechanical development, tribology, and systems engineering for automotive and industrial applications. He actively contributes to engineering education and methodology standardization. Research Interests Hydrogen internal combustion engines System modeling and digital twins Tribology in electric drivetrains Sustainable engineering practices MBSE (Model-Based Systems Engineering) Friction and wear analysis Article Trends His recent work emphasizes hydrogen propulsion systems, model-based approaches for interdisciplinary engineering challenges, tribological optimization for sustainable mobility, and integrating AI with mechanical design workflows. Labs and Teams He leads research at the Institute of Machine Elements, focusing on mechanical validation and development methodologies for advanced powertrain systems.
Dr. Manav R. Bhatnagar serves as a Professor and Brigadier Bhopinder Singh Chair Professor in the Department of Electrical Engineering at Indian Institute of Technology Delhi. He ranks #517 globally in Networking & Telecommunications among the top 2% scientists worldwide according to Stanford University and is a Fellow of INAE, NASI, IET(UK), IETE, and OSI. His academic credentials include a Ph.D. in Signal Processing for Communications from University of Oslo (2008), M.Tech. in Communications Engineering from IIT Delhi (2005), and B.E. in Electronics from North Maharashtra University (1997). He has held visiting appointments at prestigious institutions including Aalto University (Finland), University of Rennes (France), University of Oslo, Indian Institute of Science Bangalore, and University of Minnesota. Dr. Bhatnagar's research spans cutting-edge domains including 5G/6G communication, optical wireless communication, quantum communication, molecular communication, power line communication, and machine learning applications. His work demonstrates significant interdisciplinary connections between communication theory, signal processing, and emerging technologies. His publication record shows a strong focus on wireless and optical communication systems, with recent work addressing challenges in jamming detection, quantum relay systems, IRS-assisted communication, and game-theoretic approaches to resource allocation. His research consistently bridges theoretical foundations with practical applications in next-generation communication systems. NASI-Scopus Young Scientist Award Shri Om Prakash Bhasin Award (2016) Dr. Vikram Sarabhai Research Award (2017) BASIC RESEARCH AWARD of IIT Delhi (2023) Sir Visvesvaraya Young Faculty Research Fellowship (2016) Senior Member of IEEE As an academic advisor, Dr. Bhatnagar has mentored numerous PhD students who have gone on to successful careers at institutions including IIT Jodhpur, IIT Roorkee, Aalto University, and IIT Kanpur. His editorial roles include current Editor of IEEE Transactions on Communications and former Editor of IEEE Transactions on Wireless Communications (2011-2014). His textbook "Telecommunication Switching Systems and Networks" has become a standard reference in the field.
Hans Tompits is an Associate Professor in the Department of Knowledge-Based Systems at Technische Universität Wien (Vienna University of Technology). His research focuses on computational logic, declarative logic programming, and formal methods, with a particular emphasis on Answer-Set Programming (ASP). He coordinates the Master's program in Logic and Computation and leads projects in areas such as formal methods for optimization, fault-tolerant autonomous systems, and algorithmic composition. His work bridges theoretical advancements with practical applications, including tools like SeaLion (an ASP IDE with debugging support) and dlvhex (an ASP-based semantic web reasoner). He has contributed to foundational topics like program equivalence, debugging techniques, and integration of ASP with external systems. His recent projects address challenges in autonomous vehicle architectures, music composition algorithms, and safety-critical system design. Tompits has published extensively on topics ranging from nonmonotonic reasoning and modal logics to the development of declarative programming tools. His interdisciplinary approach spans computer science, mathematics, and AI, with applications in both academic and industrial contexts.
Leandros Tassiulas is the John C. Malone Professor of Electrical Engineering at Yale University, with additional appointments in Computer Science. His career spans faculty positions at the University of Thessaly, University of Maryland, University of Ioannina, and Polytechnic University. A Fellow of both IEEE (2007) and ACM (2020), he is renowned for contributions to network control theory, including the max-weight scheduling algorithm and back-pressure network policy. PhD in Electrical Engineering (1991) from the University of Maryland, College Park His research focuses on computer and communication networks , emphasizing mathematical models for complex networks , wireless system architectures , stochastic systems , and energy-efficient network design . Recent work explores quantum networking (Pant et al., 2019) and federated learning in edge environments (Jiang et al., 2022). Key publication trends include stability analysis (earlier works), mobile edge computing (2019), software-defined networking (2021), and smart grid optimization (2012-2013). The list includes monographs on network theory and patents for distributed bandwidth allocation (2011) and directional antenna protocols (2002). Scientific Awards ACM Fellow (2020) for network control contributions IEEE Koji Kobayashi Award (2016) for scheduling/stability analysis IEEE INFOCOM Achievement Award (2007) for resource allocation Bodossaki Foundation Prize (1999) for distributed systems NSF CAREER, ONR Young Investigator, and multiple best paper awards His work has been funded by the NSF, ONR, and IBM. Current projects bridge AI , quantum communication , and next-generation network architectures .
Mohamed-Slim Alouini is a Professor of Electrical Engineering and Associate Dean of the Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia. He also serves as the Associate Vice President for Research and holds the UNESCO Chair in Education to Connect the Unconnected. With over 500 journal publications and more than 46,000 citations, he is a world-renowned expert in wireless communications who was elected IEEE Fellow in 2009 at the age of 39. Education: PhD in Electrical Engineering, California Institute of Technology (Caltech), 1998 MS in Electrical Engineering, Georgia Institute of Technology (Georgia Tech), 1995 Diplôme d'Etudes Approfondies (DEA) in Electronics, Université Pierre & Marie Curie (Sorbonne University), 1993 Diplôme d'Ingénieur, École Nationale Supérieure des Télécommunications (Télécom Paris Tech), 1993 Habilitation, Université Pierre & Marie Curie (Sorbonne University), 2003 Dr. Alouini is a world-renowned expert in wireless communication and networking with research interests spanning diversity combining techniques, MIMO systems, multi-hop/cooperative communications, optical wireless systems, cognitive radio, UAV communications, and advanced modulation schemes. His current focus addresses the technical challenges of uneven information and communication technology distribution, particularly targeting rural, low-income, disaster-prone, and hard-to-reach areas through integrated ground-airborne-space networks. His work bridges theoretical foundations with practical implementations to solve real-world connectivity problems. His recent publications (2020-2024) demonstrate a clear research trajectory toward integrated communication networks combining terrestrial, aerial, and space components. There's growing emphasis on UAV communications, satellite systems, optical wireless technologies, and rural connectivity solutions, with increasing integration of machine learning techniques for network optimization. His work shows consistent focus on addressing the digital divide, with several publications specifically targeting 6G challenges for connecting underserved populations and recycling existing infrastructure for enhanced rural connectivity. Scientific Awards: Member of the European Academy of Sciences and Arts (2019) Fellow of the African Academy of Sciences (2018) IEEE Fellow (2009) Abdul Hameed Shoman Award for Arab Researchers (2016) OIC Science & Technology Achievement Award (2017) Multiple recognitions as Highly Cited Researcher NSF CAREER Award (1999) Dr. Alouini has mentored numerous successful students and post-doctoral fellows who have secured positions at top institutions worldwide including Harvard, Caltech, Imperial College, and faculty positions at Korea University, Hanyang University, and universities across the Middle East. His December 2018 PhD graduate Qurrat-Ul-Ain Nadeem received the prestigious Marconi Society Paul Baran Young Scholars award, while post-doctoral fellows have won IEEE ComSoc Young Professionals Best Innovation Award and attended the Lindau Nobel Meeting. His Communication Theory Lab at KAUST drives significant research in wireless communications with funding supporting extensive publication output and innovative projects. Dr. Alouini leads the Communication Theory Lab at KAUST and holds the UNESCO Chair in Education to Connect the Unconnected, focusing specifically on technical solutions for connecting underserved communities. His lab works on integrated ground-airborne-space networks to bridge the digital divide, with particular emphasis on rural, low-income, and hard-to-reach areas. The team develops practical solutions using UAVs, satellite communications, and recycled infrastructure to provide cost-effective connectivity where traditional approaches fail.
Sabine Seidel is a full Professor at the Institute of Crop Production, Department of Agrarwissenschaften, University of Natural Resources and Life Sciences, Vienna (BOKU). Her research integrates plant modeling, sustainable agriculture, and digital farming to enhance climate-resilient and resource-efficient crop systems. Her research interests focus on the development and testing of innovative, diverse (organic) cultivation systems, particularly mixed cropping and intercropping. She investigates ecosystem services such as yield and greenhouse gas emissions through measurements and modeling. Her work emphasizes the interactions between genotype, environment, and management (G×E×M), especially concerning water, nitrogen, and root dynamics. She also explores root growth responses to nutrient deficiency and drought stress, and leads initiatives in digital farming, including AI tools for pollinator detection and digital twin development in agriculture. Analysis of her recent publications (2024–2025) reveals a strong trend in interdisciplinary research combining field experiments with advanced modeling. Her work spans agroecosystem modeling, intercropping systems (especially wheat and faba bean), soil-crop interactions, and the application of AI and machine learning in agriculture. She frequently contributes to multi-model studies and calibration protocols, emphasizing model accuracy and validation. Her research is highly collaborative, involving teams across Germany and Austria. Root:shoot ratio under conservation tillage Phenotypic plasticity in winter wheat Resource acquisition in intercropping Digital crop growth simulation using GANs Soil carbon sequestration and organic matter dynamics She has been actively involved in the PhenoRob Cluster of Excellence as a junior research group leader (2020–2025), focusing on optimizing plant mixtures through field experiments and modeling. Prior to this, she conducted postdoctoral research on subsoil management at the University of Bonn. Her work bridges ecology, plant science, soil science, and digital technologies. She earned her doctorate on plant modeling and irrigation from the Technical University of Dresden and studied agricultural sciences at the Technical University of Munich. She is based in Vienna and maintains an active presence in knowledge transfer, with media contributions in print and online outlets discussing sustainable farming practices.
