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Wenwu ZhuView profile

Professor

• Big data analysis
• Multimedia communication and networking
• Multimedia computing
• +5 more

Wenwu Zhu is a Professor and Vice Chair of the Department of Computer Science and Technology at Tsinghua University. He has held prominent positions at Microsoft Research Asia, Intel Research China, and Bell Labs, establishing himself as a leading figure in multimedia computing and networking with international recognition as a FOREIGN member of the Academy of Europe (elected 2018). His educational background includes: Ph.D. in Electrical and Computer Engineering from New York University (1996) Professor Zhu's research focuses on the intersection of multimedia systems, networking, and big data. His work has pioneered advancements in internet video streaming, multimedia cloud computing, and social-aware content distribution. He has made significant contributions to understanding how multimedia content can be efficiently delivered across diverse network environments, from traditional wired networks to modern mobile and social platforms. His research bridges theoretical computer science with practical applications, with his work on social-aware video content distribution being transferred to Tencent company. His publication record shows a clear evolution from foundational work on internet video streaming in the early 2000s, through multimedia cloud computing in the early 2010s, to more recent work on social-aware multimedia and network embedding using deep learning approaches. This progression reflects the changing landscape of multimedia computing from infrastructure-focused to socially-aware and AI-driven systems. Professor Zhu has received numerous prestigious honors: AAAS Fellow (2016) SPIE Fellow (2013) IEEE Fellow (2010) Minister of Education's Natural Science Award, 1st prize (2017) Chinese Institution of Electronics's Natural Science Award, 1st prize (2015, 2012) National Natural Science Award, 2nd prize (2012) Chief Scientist for NSFC Major Project (2016) Chief Scientist for Ministry of Science and Technology's 973 Project (2014) Multiple Best Paper Awards including ACM Multimedia 2012 As Editor-in-Chief of IEEE Transactions on Multimedia since 2017 and through leadership roles as General Co-Chair for ACM CIKM 2019 and ACM Multimedia 2018, Professor Zhu has significantly shaped the multimedia research community. His research has been supported by major grants including NSFC Major Projects and Ministry of Science and Technology's 973 Projects, demonstrating both academic and national strategic importance. He has published over 300 referred papers with an H-Index of 55, including 6 Best Paper Awards and 7 books or book chapters. Professor Zhu leads a research group at Tsinghua University focused on multimedia big data computing, with strong industry connections. His team has made pioneering contributions to structural network embedding using deep learning and social contextual recommendation systems, bridging theoretical advances with practical applications in social media platforms.

• Database systems
• Large scale analytics
• Distributed systems

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.

Heiko BornholdtView profile

Researcher

• Distributed Communication Middleware
• Overlay Networking
• P2P Networks
• +3 more

Dr. Heiko Bornholdt is a Researcher in the Computer Networks group at the Department of Informatics, University of Hamburg. He is affiliated with the Faculty of Mathematics, Informatics, and Natural Sciences. His research focuses on distributed communication middleware, overlay networking, and edge computing. He holds a doctoral degree and has been with the university since 2016. Position: Research Associate / Postdoc Office: Room F-622, Vogt-Kölln-Str. 30 Contact: heiko.bornholdt@uni-hamburg.de | +49 40 42883-2332 Research Interests Dr. Bornholdt’s work emphasizes distributed systems , particularly in the context of smart cities and IoT. Key areas include: Overlay networks for edge computing Decentralized privacy-preserving systems Efficient data discovery in IoT Latency-aware network protocols Publications Overview His recent work spans 20+ publications, with significant contributions to: Edge computing middleware (e.g., software-defined overlay networks) Secure communication in untrusted environments Smart urban data spaces Awards & Grants No specific awards mentioned, but active in funded projects including the EU-GDPR compliant blockchain research. Labs & Teams Part of the Computer Networks Team led by Prof. Mathias Fischer, collaborating with researchers like Kevin Röbert and Jeetesh Gupta.

• Network Performance
• Cybersecurity
• Congestion Control
• +4 more

Simone Ferlin is an Adjunct Senior Lecturer at Karlstad University and a Senior Performance Engineer. She holds a PhD in Computer Science from Simula Research Lab and Universitetet i Oslo (2017), focusing on robustness in multipath transport protocols like MPTCP. Her research spans network performance, security, and congestion control in mobile/5G networks and the Internet. She collaborates actively with academia and industry, co-supervising students in areas such as edge computing, container orchestration, and distributed systems. Affiliations: Department of Informatics, Karlstad University; Red Hat Research; Ericsson R&D. Education: PhD (2017), Simula/UiO; Master’s and Undergraduate studies emphasized networking and electronics. Her work includes projects like AIDA (AI-driven edge networking) and DRIVE (latency-sensitive mobile services). She has published over 50 papers on topics like QUIC, eBPF, and containerized microservices. Awards include the Best Paper at IEEE ICIN 2021 and ANRP 2025 Prize. Teaching responsibilities include Future Internet Design and Service Quality . Advising spans 15+ students across institutions like TU Berlin, KTH, and Unifesp. She chairs conferences (e.g., ACM SIGCOMM 2025) and serves on editorial boards (IEEE Communications Magazine). Key interests: network observability, low-latency protocols, and sustainability in networking.

Christopher ChenView profile

Associate Professor

• Space Plasma Physics
• Solar Wind
• Plasma Turbulence
• +5 more

Dr. Christopher Chen is a Reader in Space Plasma Physics at Queen Mary University of London, holding a UKRI Future Leaders Fellowship. He is affiliated with the School of Physical and Chemical Sciences within the Department of Physics and Astronomy. Chen earned his PhD in Space Physics from Imperial College London in 2011 and has held research positions at the University of California, Berkeley and Imperial College before joining QMUL in 2017, where he progressed from Lecturer to Senior Lecturer in 2021 and then to Reader in 2022. Chen's research focuses on space plasma physics, particularly solar wind turbulence and its fundamental properties. His work bridges theoretical models, spacecraft data analysis, and laboratory experiments to understand complex plasma behavior. He is actively involved in several major space missions including Parker Solar Probe (as a member of FIELDS and SWEAP teams), Interstellar Probe mission study, and Magnetospheric Multiscale mission (as a member of the Science Working Team). His publication record shows a strong focus on solar wind turbulence, Alfvén wave interactions, and plasma dynamics in the inner heliosphere. The most recent work emphasizes forecasting techniques for solar wind parameters, laboratory experiments of wave interactions, and detailed analysis of turbulence properties using data from Parker Solar Probe. His research demonstrates a clear progression toward understanding the kinetic-scale processes that govern energy transfer in space plasmas. Royal Astronomical Society Fowler Award (2017) American Geophysical Union Macelwane Medal (2021) Conferred Fellow of the American Geophysical Union (2021) American Physical Society Landau-Spitzer Award (2022) Chen actively supervises a large research group including multiple postdoctoral researchers and PhD students, and has secured significant research funding through an STFC Ernest Rutherford Fellowship (2016-21), UKRI Future Leaders Fellowship (2022-26), and multiple STFC Consolidated Grants. His teaching responsibilities include organizing and lecturing the Astrophysical Plasmas module and supervising Masters and undergraduate research projects. He is also engaged in extensive public outreach through media interviews, public talks, and participation in science festivals.

Stephen TaylorView profile

Professor

• Cybersecurity
• Distributed Computing
• Computer and Network Security
• +4 more

Stephen Taylor is a Professor of Computer Engineering at Dartmouth College's Thayer School of Engineering. His research focuses on cybersecurity, distributed computing, and embedded systems security. He has held leadership roles including DARPA Program Manager and Air Force Research Laboratory IPA. Taylor's work includes foundational contributions to the National Cyber Range and Air Force Cyber Experimentation Environment. Education: BSc in Computer Systems from Essex University (1982), MSc in Computer Science from Columbia University (1985), and PhD in Computer Science from the Weizmann Institute (1989). Research emphasizes resilient operating systems for cloud computing, security mechanisms for embedded systems, and large-scale experimentation infrastructure. Awards include the USAF Exemplary Civilian Service Medal and Secretary of Defense Medal for Public Service. Teaches courses on microprocessors, software design, and cyberspace technology. Advises on multi-disciplinary projects and has authored 4 books and over 25 journal articles. His lab explores hardware-software co-design for cyber resilience and soil-based sustainable computing.

Niko MäkitaloView profile

Assistant Professor

• Cyber-Physical Systems
• AI/ML Software Engineering
• IoT Architectures
• +3 more

Niko Mäkitalo is an Assistant Professor at the University of Jyväskylä's Faculty of Information Technology and a member of the University Consortium Chydenius. His research focuses on advancing cyber-physical systems through innovative software architectures for AI, IoT, and the Cloud-Edge Continuum, with significant emphasis on hardware and network infrastructures. He teaches and mentors graduate students in these areas. Research Interests: Mäkitalo's work centers on creating intelligent environments via novel software frameworks, engineering methodologies for distributed AI/ML applications, and addressing ethical/privacy challenges in edge computing. He explores the intersection of agile development practices, third-party code management, and industry standards like IDSA/GAIA-X for AI integration. Key Contributions: His recent work includes studies on software ownership dynamics, regulatory-aware AI deployment, and liquid AI systems. He leads the Empirical Software Engineering Research group and collaborates on initiatives like 6GSoft for edge-cloud software solutions. Advising & Grants: Mäkitalo supervises Master's and Ph.D. candidates in software engineering and systems architecture. His projects often involve industry partnerships to address real-world challenges in smart manufacturing, autonomous systems, and networked environments. Labs/Teams: Active in the Empirical Software Engineering Research group, contributing to cross-disciplinary projects at the University of Jyväskylä's tech innovation ecosystem.

David BellView profile

Researcher

• Atmospheric Chemistry
• Environmental Science
• Secondary Organic Aerosol (SOA)
• +5 more

Dr. David Bell is a Scientist at the Paul Scherrer Institute (PSI) within the Center for Energy and Environmental Sciences and Laboratory of Atmospheric Chemistry . Since 2017, he has conducted research on aerosol formation and aging processes, particularly focusing on secondary organic aerosol (SOA) from biomass burning and complex combustion sources. He transitioned to a Tenure Track position at PSI in 2021. Education : B.Sc. in Chemistry and Mathematics from University of Wisconsin-Stevens Point (2008); Ph.D. in Chemistry from University of Utah (2013); Postdoctoral Researcher at Pacific Northwest National Laboratory (2013-2017). His research systematically investigates aerosol source profiles using atmospheric simulation chambers and real-time chemical composition analysis. Key areas include secondary organic aerosol formation , oxidative potential of combustion aerosols , and humidity effects on aerosol behavior . He employs advanced instrumentation like extractive electrospray ionization mass spectrometry (EESI-TOF) for molecular-level insights. The 15 most recent publications (2023-2025) highlight his work on biomass burning emissions , α-pinene oxidation , NO3 radical impacts , and instrument development for aerosol analysis. His studies emphasize the interplay between inorganic-organic interactions (e.g., ammonia effects) and climate-relevant processes (e.g., cloud formation).

Marta CatilloView profile

Researcher

• Cybersecurity
• Machine Learning
• Intrusion Detection Systems
• +3 more

Marta Catillo is a Researcher at the Department of Engineering (DING) of the University of Sannio (UNISANNIO) . She specializes in Cybersecurity , with focus on Machine Learning applications for intrusion detection , IoT security , and cloud auto-scaling mechanisms . Her research addresses challenges in Denial of Service (DoS) mitigation , anomaly detection , and deep learning architectures for security. Teaching: [803004] PROGRAMMING 1 for Electronic and Biomedical Engineering students (2025 cohort) Contact: Office hours: Thursdays 3-5 PM, Room 23, Bosco Lucarelli Palace Research trends: From 2019-2025 publications, her work spans adversarial attack resistance , collective anomaly detection , outlier-aware architectures , and empirical analysis of defense mechanisms , with recurring collaborations with Antonio Pecchia , Umberto Villano , and Massimiliano Rak . Key methodologies include deep autoencoders , hybrid detection systems , and measurement-based security evaluation . Technical Contributions: Developed the ZED-IDS framework for zero-day threat detection, MultiCIDS for multivariate time series intrusion detection, and DEFEDGE for edge-cloud security testing.

• Internet of Things (IoT)
• Cloud Computing
• Edge Computing
• +6 more

Devki Nandan Jha is a researcher specializing in Internet of Things (IoT) , Cloud/Edge Computing , and Cybersecurity . His work focuses on runtime monitoring, security frameworks, and deployment optimization in heterogeneous environments. Collaborations include institutions across Europe and Asia, with frequent co-authorship with Rajiv Ranjan, David Wallom, and David Blundell.

• Robot Vision
• Robot Navigation
• Computer Vision
• +7 more

Helder Araujo is a Professor at the Department of Electrical and Computer Engineering, University of Coimbra. His research focuses on Robot Vision , Computer Vision , and Medical Imaging , with applications in Capsule Endoscopy , Autonomous Driving , and Sensor Fusion . Recent publications highlight advancements in 3D Object Detection using transformer networks (e.g., RetSeg3D , DDet3D ), Medical Robotics (e.g., Self-supervised monocular pose estimation ), and Federated Learning (e.g., FAIR-FATE ). Key subfields include Transformer Models , Deep Learning , and Autonomous Navigation . His projects span Medical Imaging (e.g., Multi-Cam Capsule Endoscopy ), Autonomous Robotics (e.g., Learning to Navigate Endoscopic Capsule Robots ), and Edge Computing (e.g., Benchmarking CNN Inference on Low-Power Devices ). Grants include funding from Fundação para a Ciência e a Tecnologia (e.g., PTDC/EEI-ROB/1155/2020) and the European Commission (e.g., AdvanCed Hardware/Software Components for Embedded Vision). He has served as an invited researcher at Université Blaise Pascal (2012–2014). Peer review activities cover journals like IEEE Transactions on Pattern Analysis and Machine Intelligence and Autonomous Robots . His work bridges Medical Imaging , Autonomous Systems , and AI Fairness .

Rider W. FoleyView profile

Associate Professor

• Science and Technology Studies
• Sustainability Science
• Ethical STEM Education
• +5 more

Rider W. Foley is an Associate Professor in the Science, Technology & Society program at the University of Virginia's Department of Engineering and Society. He directs the Policy Internship Program and leads the '4C Project' on Cultivating Cultures of Ethical STEM education, collaborating with institutions like Notre Dame and Arizona State University. His research focuses on societal-technology intersections, including ethical STEM education, innovation governance, sustainability challenges, and urban techno-politics. Foley holds a Ph.D. in Sustainability from Arizona State University, a Master's in Environmental Management from Harvard, and a B.S. in Environmental Science from the University of New Hampshire. Prior to academia, he worked in environmental consulting and emergency response for Triumvirate Environmental Inc. His work spans themes like responsible innovation, wicked problems, and policy interventions for equitable technological development. Education: Ph.D. in Sustainability, Arizona State University M.S. in Environmental Management, Harvard University B.S. in Environmental Science, University of New Hampshire His research interests emphasize 'wicked problems' requiring interdisciplinary solutions, such as nanotechnology governance, smart city equity, and energy infrastructure ethics. He co-leads the 'Nano and the City' thematic cluster at Arizona State's Center for Nanotechnology in Society and collaborates with the Sustainability Science Education program at the Biodesign Institute. Recent projects include evaluating innovation ecosystems for wearable medical devices and analyzing the Atlantic Coast Pipeline's societal impacts through public values theory. Foley's academic contributions bridge theory and practice, with a focus on pedagogy (e.g., concept mapping for learning outcomes) and participatory methods (e.g., community-governed network commons). He explores how education and policy can align technological advancements with societal needs, particularly in marginalized communities. His work on anticipatory governance frameworks aims to preempt ethical challenges in emerging technologies like geoengineering and synthetic biology. His advising and grants include collaborations on the '4C Project' and 'Nano and the City,' leveraging partnerships between academia, industry, and policymakers. Current efforts involve refining methodologies for assessing student learning in engineering ethics and advancing frameworks for sustainable innovation in arid regions. Foley is affiliated with the Center for Nanotechnology in Society and contributes to initiatives like the Secure Affordable Sustainable Edge Clouds (SASEC) for smart cities.

• Information Systems
• Big Data
• Cloud Computing
• +12 more

Norman H. White is a Clinical Professor in the Department of Information, Operations, and Management Sciences at the Leonard N. Stern School of Business, New York University. He has been a faculty member since 1973 and currently serves as the Faculty Director of the Stern Center for Research Computing, where he supports advanced computational research across the school. His research spans big data, cloud computing, distributed computing, data science, decision support systems, and mobile applications . He has published in areas including data mining, computer networking, and simulation. His work bridges technology and business applications, particularly in marketing and financial engineering. Professor White holds a Ph.D. in Economics and Statistics from NYU Stern (1974) and a B.A. in Engineering and Applied Physics from Harvard University (1966). He previously served as Deputy Chair of the Information Systems Department and Acting Chief Technology Officer of the Stern School. He has been actively involved in university-wide computing initiatives and has consulted for major organizations including Anheuser-Busch, Kraft, Toyota, Ford, Goldman Sachs, and the U.S. State Department. The Stern Center for Research Computing, under his leadership, provides a high-performance computing grid, private cloud infrastructure, and Hadoop-based big data clusters to support research. He teaches courses such as Dealing with Data , Designing and Developing Web and Mobile Apps , and Computational Approaches to Financial Engineering .

• Computer Architecture
• High-Performance Computing
• Distributed Systems
• +12 more

Yolanda Becerra Fontal is a faculty member at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture within the Barcelona School of Informatics (FIB). She is actively involved in research projects and collaborations, notably with the Barcelona Supercomputing Center, and is a member of prominent research groups such as the High Performance Computing Group (CAP) and CROMAI (Computing Resources Orchestration and Management for AI). Research Interests: Her research spans a broad spectrum of computer systems, with a consistent focus on performance, efficiency, and scalability. Key areas include Computer Architecture , High-Performance Computing (HPC) , Distributed and Cloud Systems , Resource and Energy Management in virtualized environments, and Data-Intensive Computing . More recently, her work has centered on innovative time-series database systems and data management for edge and cloud analytics. Publication Trends: Her recent scholarly output (2020-2022) shows a strong emphasis on time-series data management, proposing novel database architectures like NagareDB and strategies for polyglot persistence. Earlier work (2009-2013) was pivotal in MapReduce workload management, energy accounting for virtualized systems, and optical data center networks, demonstrating a long-standing contribution to foundational distributed computing challenges. Scientific Contributions: Her work has been published in top-tier journals and conferences such as Future Generation Computer Systems , IEEE Transactions , and Nucleic Acids Research . She has also contributed to significant competitive R&D projects and holds patents related to data flow management and distributed indexing. Advising and Grants: Dr. Becerra Fontal has served as a thesis advisor for doctoral students. Her research has been funded through competitive grants from national and regional programs, including Spanish State Research Plans (Plan Estatal de Investigación) and Catalonia's RIS3CAT strategy, supporting projects on high-performance computing and data management. Research Groups and Labs: She is a core member of the CAP - High Performance Computing Group and the CROMAI - Computing Resources Orchestration and Management for AI group at UPC. Her work is closely associated with the Barcelona Supercomputing Center (BSC) , one of Europe's leading supercomputing facilities, indicating access to advanced computational infrastructure.

Martin Wulf GerdesView profile

Associate Professor

• eHealth
• Artificial Intelligence
• Machine Learning
• +9 more

Martin Wulf Gerdes is an Associate Professor at the Department of Information and Communication Technology, University of Agder, Norway. With a Ph.D. in eHealth and over two decades of experience in telecommunications and healthcare technology research, he focuses on developing user-friendly, interoperable eHealth solutions using ICT and IoT. His career spans roles at Ericsson Eurolab and academic leadership in Norway. Education: M.Sc. equivalent in General Electrical Engineering (1998) from RWTH Aachen, emphasizing ICT. Ph.D.: Information and Communication Technologies with eHealth specialization (2019) from University of Agder. Research Interests: Gerdes explores AI-driven decision support systems, distributed eHealth infrastructure, telemedicine, and assistive technologies for chronic disease management. His work bridges IoT, data privacy, and user-centered design in healthcare robotics. Teaching: Since 2014, he has taught at bachelor's and master's levels, currently leading courses in Communication & Cooperation, Technology Understanding, and seminar projects in eHealth. Scientific Publications: His 15 most recent articles (2020-2024) span AI in dental radiology, blood glucose prediction, digital twins, and ethical considerations in healthcare algorithms. Topics include IoT integration, data privacy, and pandemic analytics.