Dr. Yang Liu is a Senior Lecturer in the Department of Computer Science at Swansea University's Faculty of Science and Engineering. He holds a D.Phil. in Computer Science from the University of Oxford and specializes in data security, privacy-preserving computing, and blockchain technologies. Research Focus: Dr. Liu's work centers on secure computation frameworks with specific expertise in: Federated learning systems optimization Privacy-preserving smart contract design Blockchain security and regulation Cryptographic techniques for data protection Secure machine learning applications Recent publications demonstrate methodological innovations in adaptive federated learning algorithms, regulatable blockchain architectures, privacy-enhanced recommendation systems, and security vulnerability analysis in Ethereum networks. His research bridges theoretical cryptography with practical applications in cloud/edge computing environments.
Antonio Brogi is a Full Professor at the Department of Computer Science, University of Pisa. He leads the Service-Oriented, Cloud and Fog Computing (SOCC) research group and is actively involved in multiple editorial roles, including for Electronics , Heliyon Computer Science , and Journal of Computer Languages . His research focuses on cloud-edge computing, quantum software engineering, and formal methods for distributed systems. He chairs program committees for major conferences like ESOCC, ADAPTIVE, and IEEE ICWS. Research Interests: Service computing, fog computing, quantum software engineering, system coordination, resilience, and sustainability. He has pioneered declarative approaches for managing distributed systems and has contributed to frameworks like ECLYPSE and FREEDA. Teaching: Teaches Cloud Computing (BSc) and Advanced Software Engineering (MSc) at the University of Pisa. Supervises master's and bachelor's theses in related areas. Grants & Projects: Participated in EU-funded initiatives like SeaClouds and national projects DECLware and Through the Fog. Active in industry collaborations for cloud-edge infrastructure optimization.
Rebecca Schreib serves as an Assistant Teaching Professor and Director of Undergraduate Studies in Rice University's Department of Computer Science. She holds a Ph.D., M.S., and B.S. in Computer Science from Rice University (2019, 2015, 2014 respectively). Her research focuses on computer science education, virtualization, and embedded runtime systems. Her educational background includes a doctoral emphasis on designing personalized interactive learning tools for large introductory courses. Key research contributions include MemStep (2024), collaborative computational thinking courses (2020), and automated assessment systems (2016–2017). Her work spans both educational technology and embedded systems, with a focus on bridging theory-practice gaps in programming education while advancing runtime system reliability for constrained environments. She has developed tools that enhance student engagement and automated systems for testing and memory management. While no scientific awards are listed, her publications reflect sustained innovation in educational technology and embedded computing since 2012. Her advising and grant activities are not explicitly documented here. She contributes to Rice's undergraduate program infrastructure through her directorship role.
Miguel Matos is an Assistant Professor at Instituto Superior Técnico (IST) of Universidade de Lisboa and a Researcher at INESC-ID's Distributed Systems Group. His research focuses on Persistent Memory systems, blockchain scalability, distributed systems evaluation, and database performance. He has led major projects such as Angainor (reproducible evaluation tools) and ACT-PM (crash-consistency testing). Research interests include exploring persistent memory's challenges, blockchain Layer-2 limitations, automated bug detection (HawkSet, Mumak), and decentralized network emulation (Kollaps). He has received awards like the Gilles Muller Best Artefact Award at EuroSys 2025 and Best Paper Awards at DAIS 2017 and IPDPS 2012. He coordinates multi-million Euro grants including EU's Qualichain and national FCT projects. Teaching includes courses like 'Highly Dependable Systems' and 'Large-Scale Systems Engineering' at IST. His work bridges academia and industry, collaborating with startups like MIMA Housing and LeanXcale.
Pavlos Fafalios is an Assistant Professor of Information Systems at the School of Production Engineering and Management, Technical University of Crete, and an Affiliated Researcher at the Centre for Cultural Informatics (CCI) and Information Systems Laboratory (ISL), Institute of Computer Science, Foundation for Research and Technology - Hellas (FORTH). He holds a PhD and MSc in Information Systems from the University of Crete and an Engineer's Diploma from the University of the Aegean. His academic journey includes postdoctoral research at L3S Research Center, Leibniz University of Hanover, and FORTH-ICS, as well as teaching roles at Hellenic Mediterranean University and the University of Crete. His research interests span Information Systems , Data and Knowledge Management , and Linked Data , with a strong interdisciplinary focus on applications in Cultural Heritage and the Humanities . He develops semantic technologies, knowledge graphs, and information management systems for complex, real-world domains. The recent publications highlight a strong trend in applying semantic technologies to cultural and historical data, including earthquake data modeling, feminism history documentation, and museum data integration. His work consistently focuses on knowledge representation, ontology development, and data interoperability, particularly using CIDOC CRM and Linked Data principles. Individual postdoctoral research fellowship 'Marie Skłodowska-Curie' (H2020-MSCA-IF-2019) Finalist for the '2019 ERCIM Cor Baayen Young Researcher Award' Fellowship from legacy 'Maria Michael Manasaki' (2014-2015) 1st prize in Hack4Med 2014 1st prize in Blue Hackathon 2013 PhD and MSc scholarships by FORTH Pavlos Fafalios has been involved in significant research projects such as PortADa (MSCA Staff Exchange), RICONTRANS (ERC Consolidator Grant), FE.P.I.B., ReKnow (Marie Curie project), SeaLiT (ERC Starting Grant), and ALEXANDRIA (ERC Advanced Grant), where he served as principal investigator, scientific responsible, or lead researcher. He has supervised student projects that led to award-winning software tools. He is active in scientific committees and regularly publishes in international venues. He leads and contributes to research in the Centre for Cultural Informatics (CCI) and Information Systems Laboratory (ISL) at FORTH-ICS, collaborating on interdisciplinary projects that bridge computer science with humanities and cultural heritage. His lab work emphasizes practical tools for semantic data integration, exploration, and analysis.
Harry Xu is a Professor in the Computer Science Department at the Samueli School of Engineering , University of California, Los Angeles . His research spans computer systems, programming languages, compilers, and AI infrastructure. He co-founded BreezeML for GenAI risk management and has held visiting roles at Microsoft Research and IBM Watson Research Center. Current research focuses on user-defined clouds and AI application infrastructures Founded BreezeML and contributed to Niijima (SOSP'19) and Yak GC (OSDI'16) Developed VQPy, integrated into Cisco's DeepVision Scientific Awards 2018 Dahl-Nygaard Junior Prize ACM Distinguished Scientist Advising and Collaborations Current students: Shan Yu, Zhenting Zhu, Shu Anzai, Yicheng Liu Alumni: Shi Liu (Databricks), Jiyuan Wang (AWS), Haoran Ma (ByteDance AI Infra), Yifan Qiao (UC Berkeley), Christian Navasca (BreezeML), Pengzhan Zhao (BreezeML co-founder)
Bo Bernhardsson is a Professor in Automatic Control at the Department of Automatic Control, Faculty of Engineering (LTH), Lund University. He has been a full-time professor at Lund since 2010, following a decade (2001–2010) as an Expert in Mobile System Design and Optimization at Ericsson. He is affiliated with major research initiatives including ELLIIT (Excellence Center in Information Technology), LCCC (Lund Center for Control of Complex Engineering Systems), and WASP-AS (Wallenberg AI, Autonomous Systems and Software research school), where he has played a leadership role since 2016. His research focuses on modeling and control of uncertain and large-scale systems, with applications spanning industrial automation, mobile communications, particle accelerators, biomedical systems, and navigation technologies. He integrates theoretical control methods with practical implementations, particularly under constraints such as communication limitations, noise, and delays. His recent publications reveal a strong trend in networked control, communication-constrained estimation, and optimization-based control design. The works span theoretical advances in signal estimation under SNR constraints, event-based and stochastic control, and practical applications like IMU-radio fusion for navigation and RF field control in particle accelerators. Keywords include Control Theory, Communication Systems, Optimization, Signal Processing, and Networked Control , with subfields such as encoder-decoder co-design, virtual antenna arrays, and dynamic programming for time-delay systems. PhD in Control, Lund University, 1992 Professor in Automatic Control, Lund University, since 1999 Expert, Mobile Systems, Ericsson, 2001–2010 Bo Bernhardsson has supervised over 20 PhD and licentiate students, including Jacob Bergstedt (immune system modeling), Anders Mannesson (navigation and radio), and Erik Johannesson (control under communication constraints). His research has been funded by major entities such as the European Spallation Source and the Wallenberg Foundation. He teaches advanced courses in Linear Systems, Convex Optimization, and Robust Control, and has contributed significantly to both academic and industrial advancements in control engineering. He leads and collaborates on interdisciplinary projects involving real-time control, autonomous systems, and machine learning, often in partnership with industry and international research centers. His work in the RobotLab at LTH and on cloud-based control systems highlights his engagement with emerging technologies.
Alfredo Perez, Ph.D., is an Associate Professor and Graduate Program Chair for MS CS Education in the College of Information Science & Technology at the University of Nebraska at Omaha. He holds a doctorate and M.Sc. in Computer Science from the University of South Florida (2011, 2009) and a B.Sc. in Systems Engineering from Universidad del Norte, Barranquilla (2006). Education: Ph.D., Computer Science & Engineering, University of South Florida (2011) M.Sc., Computer Science & Engineering, University of South Florida (2009) B.Sc., Systems Engineering, Universidad del Norte, Barranquilla (2006) Dr. Perez's research focuses on privacy, mobile/ubiquitous computing, and computer science education. His recent work explores blockchain security, IoT privacy frameworks, and machine learning for malware detection. He also investigates formal modeling techniques for secure systems and wearables' facial privacy solutions. His publications reveal trends in privacy-preserving IoT architectures , blockchain applications , machine learning security , and formal verification methods . Research spans from technical implementations to societal impacts of privacy technologies. Scientific Recognition: IEEE Senior Member Member, U.S. National Academy of Inventors Dr. Perez has served on technical committees for journals/conferences like Elsevier Computer Communications and reviewed grants for the National Science Foundation. His teaching expertise covers computer programming, machine learning, and CS teacher education.
Matthew Robinson is a Research Fellow at the University of Hertfordshire within the Department of Engineering and Technology, School of Physics, Engineering & Computer Science. His work focuses on next-generation communication systems and security applications, primarily through European and commercially funded projects including those with the European Space Agency (ESA), Horizon 2020, and industry partners like Global Invacom and Meazon. Education: MEng in Digital Communications and Electronics, University of Hertfordshire (2010-2014) Research Interests: Robinson specializes in 6G communications infrastructure with emphases on Software Defined Networking (SDN) , Machine Learning for sensor systems, Software Defined Radio (SDR) , and Satellite Communication for video broadcasting. His fingerprint analysis reveals strong activity in Connected Vehicles (80%), Software Defined Networking (80%), Machine Learning (50%), and Heterogeneous Transport Networks (40%). Projects demonstrate practical applications in energy disaggregation, vehicle sensor reliability, and secure smart metering. Research Trends: Recent publications (2021-2025) show a strategic pivot from video broadcasting systems toward cybersecurity applications for connected infrastructure. His work increasingly integrates unsupervised machine learning with hardware-software co-design, particularly for real-time threat detection in smart grids and autonomous vehicles, while maintaining satellite communication expertise. Awards: GB Patent GB2612705A: "Improvements to video data distribution networks" Projects & Grants: Robinson has contributed to four major initiatives: (1) SAT>IP WiFi Live Mobile TV (ESA-funded, with BBC R&D/Global Invacom), (2) EDIoT (H2020-funded, with Meazon), (3) AutoTrust (ESA-funded, with RL Automotive/Surrey), and (4) CPU/GPU Satellite Modem (ESA-funded). These projects secured substantial European funding and yielded patents, conference papers, and deployable systems for video broadcasting, energy monitoring, and vehicle sensor networks. Laboratory Affiliation: Works within the Networks and Security Research Centre, leveraging facilities for Software Defined Radio experimentation, satellite communication testing, and machine learning validation for IoT systems.
Michael E. Cotterell is a Senior Lecturer of Computer Science and Undergraduate Coordinator at the University of Georgia's School of Computing. He holds a B.S. (2011) and Ph.D. (2017) in Computer Science from UGA. His roles include directing the Computer Science Undergraduate Assistant (CSUA) and UGAHacks experiential learning programs. He chairs the Undergraduate Program & Curriculum Committee and serves on UGA’s University Council. Dr. Cotterell’s teaching career began in 2012 with Software Development courses, transitioning to full-time instructor in 2015. He has won multiple teaching awards, including the Teaching Excellence in Computer Science Award (2018, 2020) and was promoted to Senior Lecturer in 2021. He has also served as a UGA Online Learning Fellow, Writing Fellow, and Teaching Academy Fellow. His research interests span computational education, active learning methodologies, and technical fields like big data analytics, ontology-based semantics, and energy informatics. His work bridges pedagogical innovation with applied computational science. Dr. Cotterell’s publications focus on improving educational practices, predictive analytics, and interdisciplinary applications of computer science. His most recent work emphasizes student sentiment analysis in active learning environments and scalable energy systems modeling. Awards include the 2016 Outstanding Faculty Teaching Award and multiple fellowships recognizing his contributions to pedagogy and online education. He oversees undergraduate program development and coordinates experiential learning initiatives, emphasizing hands-on learning through hackathons and assistantship programs.
Prof. Andrea Benigni is a Professor and Director at the Research Center Jülich GmbH, leading the Energy System Technology (ICE-1) department within the Institute of Climate and Energy Systems (ICE). His work focuses on advanced simulation tools for multi-energy systems, power grid optimization, and real-time control solutions. Key research areas include: Multi-energy system integration (power, gas, thermal) High-performance simulation frameworks (e.g., GasNetSim, HeatNetSim) Quantum computing applications for grid partitioning Hydrogen blending in gas networks Hardware-in-the-loop testing for control architectures PMU-based fault detection and grid resilience Benigni has pioneered open-source tools like HeatNetSim and contributed to FIWARE-based ICT platforms for building/district-level energy systems. His recent work emphasizes digital twin applications for pseudo-measurement generation and parallel simulation techniques leveraging GPUs and FPGAs. Notable achievements include: Development of MGRIT-based parallel-in-time electromagnetic simulations Optimization methods for battery sizing in multi-vector systems Quantitative analysis of high PV penetration impacts in African grids Current projects involve: Hydrogen integration strategies for Southern Italy gas networks DC microgrid communication protocols via low-frequency injection Cloud-based multi-agent systems for grid flexibility management
Prof. Dr. Uwe Breitenbücher is a Professor of System Architecture at Reutlingen University's Faculty of Informatics. He holds a Diplom in Computer Science (2011) and a PhD (2016) from the University of Stuttgart. His research focuses on cloud computing, IT systems management, IoT, blockchain, and pattern languages for software architecture. He also leads educational initiatives in software engineering pedagogy, including gamified e-learning platforms like IT-REX and Gamify-IT. Education: Diplom-Informatiker (2011), University of Stuttgart Dr. rer. nat. (2016), University of Stuttgart His research interests emphasize practical deployment solutions for distributed systems, including cross-component issue management, blockchain interoperability, and cloud orchestration using TOSCA standards. He actively develops tools like Variability4TOSCA and Dromi to address challenges in deployment variability and microservice architecture. His recent articles highlight trends in cross-chain smart contract invocations, gamified education systems, and orchestration of heterogeneous deployment technologies. He has contributed to over 50 peer-reviewed publications since 2018, focusing on cloud automation, blockchain integration, and software engineering education. He chairs the Bachelor's Examination Board for Digital Business and collaborates with industry on projects like the 5G-PreCiSe initiative. His work bridges academic research with practical deployment challenges in modern distributed systems.
Michael Maire is a researcher at the University of Chicago focusing on the intersection of software engineering and machine learning, specifically addressing challenges in integrating and testing machine learning APIs within software systems. His research spans Software Engineering and Machine Learning with concentrated expertise in API Testing, Software Integration, Automated Testing, Cloud Computing, and Software Reliability. He investigates practical methodologies for ensuring correct implementation and robust performance of machine learning services in real-world software environments, emphasizing error prevention and system correctness. Analysis of his publication trajectory reveals consistent emphasis on machine learning API reliability, evolving from empirical studies of API usage patterns (2021) to automated testing frameworks (2022) and ultimately run-time failure prevention systems (2023). This progression demonstrates growing technical sophistication in addressing integration vulnerabilities, with increasing focus on proactive error mitigation in cloud-based ML deployments. Scientific Awards: No awards or honors were documented in the source materials. Advising and Grants: Available information does not specify doctoral advisees, research grants, or funded projects.
Zilong Ye is an Associate Professor in the Department of Computer Science at California State University, Los Angeles, within the College of Engineering, Computer Science, and Technology. He holds a Ph.D. in Computer Science from University at Buffalo, SUNY (2015), an M.S. from Shanghai Jiao Tong University (2010), and a B.S. from Shandong University (2007). Ph.D., Computer Science, University at Buffalo, SUNY M.S., Computer Science, Shanghai Jiao Tong University B.S., Computer Science, Shandong University His research focuses on computer networking, with emphasis on Network Function Virtualization, Software-Defined Networking, Fog Computing, and Optical Networking. He has pioneered work in distributed fiber optic sensing and infrastructure-as-a-sensor systems, addressing challenges in sensor placement, network survivability, and concurrent sensing capabilities. Publications from 2013-2024 span optical networking, IoT security, and cloud optimization, with recent work on UAV-based mobile edge computing and fiber optic sensing. Awards include Best Paper (ICC 2021) and Best Demo (ACM ICN 2016). TPC co-chair for ACM Mobihoc workshop on MobileHealth (2018) Organized international symposia on 5G technologies and SDN/NFV Journal reviewer for IEEE Transactions on Network and Service Management, Mobile Computing, and others Patents include distributed fiber optic sensor placement systems and methods for information-centric networks. Teaching includes advanced courses in computer networks and operating systems.
Ákos Lédeczi is a prolific researcher with significant contributions to computer science, sensor networks, robotics, and K-12 education. His work spans hardware-software co-design, wireless localization, and accessible programming environments. Co-developed NetsBlox and DeepForge for novice-friendly distributed computing. Created PinPtr high-precision GPS cloud service and inTrack mobile node tracking systems. Pioneered Browser-based robotics simulation and smartphone IoT education for K-12 students. Explored RF interferometry , Doppler shift tracking , and acoustic shooter localization in urban environments. Contributed to medical capsule robot design and security co-design for embedded systems. His recent focus includes project-based AI curricula for female high school students and collaborative visual programming environments . While specific university affiliations aren't detailed here, his collaborations with Péter Völgyesi, Miklós Maróti, and others highlight his role in advancing distributed and sensor network research.
