Dimitrios Dechouniotis is an Assistant Professor at the Department of Electrical and Computer Engineering within the School of Electrical and Computer Engineering at the University of Patras . His career spans roles in academia, research institutions, and public administration. 2004: Diploma in Electrical Engineering (University of Patras) 2006: MSc in Automation Systems (NTUA) 2014: PhD in Electrical and Computer Engineering (University of Patras) His research focuses on Systems & Control Theory , Cyber-Physical Systems , Robotics , Cloud Computing , and 5G Communications . Recent publications highlight work in edge computing , network slicing , and resource orchestration for IoT and robotics applications. He has participated in over 10 national and European research projects related to telecommunications and Industry 4.0. His technical contributions include frameworks for edge-cloud continuum orchestration , blockchain-based slice orchestration , and energy-aware resource allocation , with a strong emphasis on system modeling and control-theoretic approaches. Contact: dechouniotis@uop.gr | Office: Building Z, 2nd Floor
Assoc. Prof. Dejan Lavbič is an Associate Professor at the University of Ljubljana, Faculty of Computer and Information Science with 15+ years of academic experience. His research focuses on intelligent agents, multi-agent systems, ontologies, and blockchain-based smart contracts , particularly in semantic web technologies, AI services ecosystems, and information quality assessment . Doctor of Philosophy in Computer Science, University of Ljubljana (2010) Bachelor of Science in Computer Systems and Informatics, University of Ljubljana (2004) His scientific contributions span semantic web frameworks, blockchain applications, and machine learning systems, with 20+ peer-reviewed publications. Recent works include: Smart contract classification with AI Cardano blockchain identity systems Information quality metrics with gamification Awards include Cambridge CAE certification and multiple industry certifications. He mentors students in decentralized applications, AI development, and smart city ecosystems , having guided 6+ diploma/master theses on topics like automated essay grading and air quality data collection.
Arthur G Richards serves as Professor of Robotics and Control within the Dynamics and Control department at the University of Bristol's School of Engineering Mathematics and Technology. His research specializes in trajectory optimization for aerospace applications, focusing on UAV autonomy, spacecraft rendezvous, and air traffic management through advanced optimization techniques. His educational foundation includes an M.Eng. from the University of Cambridge and S.M./Ph.D. degrees from MIT. Research interests center on solving complex aerospace challenges through: Non-convex optimization for obstacle avoidance in cluttered environments Robust model predictive control for real-time disturbance compensation Distributed optimization enabling large-scale vehicle cooperation Scalable algorithms for high-traffic scenarios with minimal fuel consumption Analysis of his 132 research outputs reveals evolving emphasis on reliability-aware UAV path planning, interpretable reinforcement learning for aircraft control, and swarm robotics with real-world validation. Recent work increasingly integrates machine learning with traditional control theory while addressing practical constraints like sensor noise and system failures. Professor Richards has supervised 22 research students and secured funding for 11 projects, including the active Aerial Robotics for Search and Rescue (2022-2026) and PORTAL (2022-2024) initiatives. His industry collaborations with Thales and focus on technology transfer demonstrate strong academic-industrial integration. He actively contributes to the Smart Networks for Sustainable Futures and Robotics research groups, developing frameworks for multi-robot systems that balance theoretical rigor with practical deployment requirements in conservation, inspection, and exploration scenarios.
Umakishore Ramachandran is a Professor in the School of Computer Science at Georgia Institute of Technology's College of Computing, where he directs the Embedded Pervasive Lab. He received his Ph.D. from the University of Wisconsin-Madison in 1986 and has led transformative initiatives including the Online MS in Computer Science (OMSCS) program. His research spans distributed systems, edge computing, and real-time sensor networks, with applications in smart surveillance and connected vehicles. His research interests include architectural design of parallel/distributed systems, large-scale situation awareness using camera networks, cloud-edge continuum optimization, and latency-sensitive applications for geo-distributed infrastructures. Recent work focuses on elevating edge computing to parity with cloud resources. His publications show strong emphasis on edge computing innovations (MicroEdge, FogStore), real-time video analytics (EVA, ClairvoyantEdge), and adaptive mobile systems (Foresight). Trends include multi-tier architectures, quality-of-experience optimization, and scalable processing for IoT workloads. Major Awards: IEEE Fellow (2014) NSF Presidential Young Investigator (1990) ACM/IFIP Middleware Best Paper (2022) 3x College of Computing Dean's Awards He has advised 40+ PhD students, with recent graduates at Google, Microsoft, and academia. Current NSF/CPS grants support his work on geo-distributed latency-sensitive applications. He co-leads the STAR Center and Samsung-funded embedded software programs. His Embedded Pervasive Lab develops systems like Stampede (stream processing) and DFuse (sensor fusion), with testbeds in the Aware Home and transportation networks. Teams collaborate with Intel, Microsoft, and Bosch on edge-AI deployments.
Prof. Dr. André Hinkenjann is the Founding Director of the Institute for Visual Computing and holds a Research Professorship in Computer Graphics and Interactive Systems at Bonn-Rhein-Sieg University of Applied Sciences. His research spans computer graphics, interactive environments, and visualization, with applications in VR/AR, digital twins, and scientific data analysis. He leads multidisciplinary projects funded by institutions like BMBF and Zukunftsfonds NRW. His research integrates: Computer Graphics : Real-time global illumination, foveated rendering, and GPU optimization Interactive Systems : Haptic interfaces, large-display collaboration, and spatial interaction techniques Applied VR/AR : From trauma therapy to industrial training and cultural heritage preservation Recent publications emphasize mixed-reality interaction, neural rendering, and perceptual optimization, reflecting a consistent focus on bridging theoretical graphics with human-centered applications. His lab frequently contributes to high-impact venues like ACM SIGGRAPH, IEEE VR, and Eurographics. Notable projects under his direction include: PInBiM: Gamified citizen science for museum-based insect research DT4MP: Digital twins for urban/industrial multiphysics simulations GTN: State-wide network advancing game technology in NRW Witality: VR for sensory wine analysis
Leopoldo Teixeira is an Assistant Professor at the Informatics Center (CIn) of the Federal University of Pernambuco (UFPE) in Brazil. Since May 2023, he has served as Head of Graduate Studies at his department. He leads the Software Testing and Analysis Research group and is affiliated with the Software Productivity Group and CIn-Trust. Dr. Teixeira was a CAPES-Alexander von Humboldt Experienced Research Fellow at the Chair of Software Engineering of Universität des Saarlandes in 2022, where he collaborated with Sven Apel on variability analysis over time and space. His educational background includes: PhD in Computer Science from Federal University of Pernambuco (CIn-UFPE, 2014), supervised by Paulo Borba and Rohit Gheyi MSc in Computer Science from CIn-UFPE (2010) Bachelor's degree in Computer Engineering from the Polytechnic School of Pernambuco (2007) Dr. Teixeira's research focuses on providing strong foundations for improving software quality and productivity. His work spans software product lines, configurable systems, refactoring, formal methods, software testing, and mobile development. He has made significant contributions to understanding challenges in highly configurable systems and software evolution, with particular emphasis on theoretical rigor combined with practical applicability. His publication record demonstrates expertise across software testing methodologies, analysis of configurable systems, and formal verification techniques. Recent work addresses pressing challenges in containerization practices (Dockerfile repair), test reliability (flaky test detection), and formal specification of API properties, showing his ability to tackle both theoretical and practical aspects of software engineering. Dr. Teixeira has received recognition through the CAPES-Alexander von Humboldt Experienced Research Fellowship. CAPES-Alexander von Humboldt Experienced Research Fellow (2022) Dr. Teixeira actively contributes to the software engineering community through extensive service on program committees of major conferences including ICSE, FSE, ASE, and SPLASH across multiple years. In 2024, he served as Conference and Local Organization Chair for FSE. He mentors students through his leadership of the Software Testing and Analysis Research group at CIn-UFPE. His laboratory work focuses on software testing and analysis, particularly in the context of configurable systems and software product lines. The research group investigates practical approaches to improve software quality through better testing methodologies, analysis techniques, and formal verification approaches for complex software systems.
Dr. Michael Dietz is a Researcher at the Chair of Human-Centered Artificial Intelligence ( University of Augsburg , Faculty of Applied Informatics, Institute of Informatics). His work focuses on Human-Computer Interaction , Mobile Assistive Systems , and Signal Processing with Machine Learning applications. Key research trends include: Development of mobile frameworks for real-time affective feedback (SSJ Framework, SenseEmotion) Augmented reality applications for public spaces and ambient media Privacy-preserving machine learning on mobile devices Physiological signal analysis for stress detection in older adults Eye-tracking innovations for visual search detection Explainable AI techniques in facial expression recognition Projects: EmmA (Emotional mobile Avatar) Glassistant (Smart Glasses for MCI patients) SenseEmotion (Multisensorial emotion recognition) SSJ Framework (Social Signal Processing)
Dr. Karol Chlasta serves as an Assistant Professor in the Faculty of Management in Networked and Digital Societies at Kozminski University in Warsaw. He earned his doctoral degree in engineering and technical sciences from the Polish-Japanese Academy of Information Technology in 2023, defending his dissertation "Neural Simulation Pipeline for Liquid State Machines" with distinction (summa cum laude). His academic journey includes a Master's degree in Economic Computer Science from the University of Economics in Krakow (2008) and postgraduate studies in Business Analytics at Warsaw University of Technology (2015). Dr. Chlasta's research spans artificial intelligence, particularly neural networks and machine learning, human-computer interaction, and information management. His recent publications demonstrate expertise in AI applications for mental health screening through eye-tracking and speech analysis, sentiment analysis of social media data for migration studies, and innovative virtual reality interaction techniques. He has published consistently from 2020-2024 across multiple high-impact venues, with his work appearing in journals like Frontiers in Psychology, European Psychiatry, and Telematics and Informatics Reports, as well as conferences including ACM DIS and IEEE VR. His scientific contributions form several interconnected research threads: AI-based diagnostic systems for depression, anxiety, and dementia through biometric analysis Computational neuroscience tools including the Neural Simulation Pipeline deployable in cloud environments Sentiment analysis of social media data to understand migrant experiences during the pandemic Novel interaction techniques like VXSlate for virtual reality environments Dr. Chlasta has received notable recognition including the Scholarship of the Minister of National Education and Sport (2006) and the "Outstanding Leader" award from Aviva's global CIO (2017). His interdisciplinary approach bridges technical AI expertise with practical applications in healthcare, migration studies, and human-computer interaction. With over fifteen years of industry experience at major organizations including HP, IBM, and Aviva, Dr. Chlasta brings substantial real-world perspective to his academic work. Since 2022, he has served as Head of Technicus Poland, where he established and manages the Polish branch while developing the company's global IT and cybersecurity functions. He is also a certified specialist across multiple enterprise technologies and a member of several professional organizations including ACM and IEEE. His research approach integrates academic rigor with practical problem-solving, focusing on developing tools that address real-world challenges in mental health screening, migration support, and virtual interaction environments.
Robert Kałaska is an Assistant Lecturer at the Department of Computer Systems Architecture within the Faculty of Electronics, Telecommunications and Informatics at Gdańsk University of Technology. His work focuses on computer systems architecture with particular emphasis on IoT systems and energy-efficient computing. Dr. Kałaska's research interests center around: Internet of Things (IoT) systems and applications Containerization technologies and their optimization Energy efficiency in computing systems Middleware deployment strategies Performance analysis of computer architectures His work bridges theoretical computer science with practical implementation challenges in modern distributed systems. His recent publications demonstrate a consistent focus on optimizing IoT systems through careful analysis of containerization, CPU affinity, and energy consumption. Kałaska's research shows a progression from fundamental performance analysis to practical implementation recommendations for real-world IoT deployments, with a growing emphasis on energy efficiency as evidenced by his 2025 publication. Dr. Kałaska actively contributes to academic discourse through publications in journals such as Applied Sciences-Basel and TASK Quarterly, addressing critical challenges in modern computing infrastructure. While specific information about research grants is not provided in the available text, his collaborative work with P. Czarnul suggests involvement in research projects focused on energy-efficient computing and web technologies.
Dr. Huseyin Dagdeviren serves as Senior Lecturer and Director of Employability in the School of Computer Science and Engineering at the University of Westminster, where he actively contributes to the Centre for Parallel Computing (CPC). With over two decades of academic experience, he bridges theoretical research with industrial applications through major EU-funded initiatives. His educational foundation includes a BA (Honours) in Business Administration and MSc in Information Systems. This interdisciplinary background informs his research approach, combining technical cloud computing expertise with strategic business perspectives. Dr. Dagdeviren's research centers on complex information systems, with specialized focus on Cloud Computing, Requirements Engineering, and Strategic Management of IT. His work drives innovation in cloud-to-edge orchestration and digital manufacturing through Horizon 2020 projects like CloudiFacturing and DIGITbrain, addressing critical industry challenges in SME digital transformation. Analysis of his 2004-2023 publications reveals an evolving trajectory from foundational database and UML education research toward cutting-edge distributed systems. Recent work (2021-2023) dominates in cloud/edge computing, demonstrating strategic alignment with funded projects and industrial relevance in manufacturing simulation and digital twin deployment. As Director of Employability, he oversees career development programs while securing substantial EU grants including CO-VERSATILE (2020) and DIGITbrain (2020). These multi-institutional projects provide robust funding for the CPC lab and create direct industry pathways for students. The Centre for Parallel Computing operates as his primary research hub, facilitating international collaboration across 10+ European countries. Students benefit from exposure to large-scale EU consortia, industry partnerships with Siemens/Bosch, and hands-on development of production-grade cloud orchestration platforms.
Jay Deslauriers serves as a Research Fellow at the University of Westminster's Centre for Parallel Computing and holds a Teaching Fellow position at Imperial College London spanning both the Graduate School and Business School. With five years at Westminster following prior service as a full-time Lecturer in the School of Computer Science & Engineering, his career bridges advanced cloud research and technical education. His research focuses on cloud and container orchestration with emphasis on vendor-agnostic solutions across the cloud-edge continuum. Key projects include leading MiCADO framework development for the EU Horizon 2020 DIGITbrain (Digital Twins in Manufacturing) and ASCLEPIOS (secure healthcare cloud platform) initiatives. His technical expertise spans Kubernetes, Docker, TOSCA standards, and infrastructure-as-code implementation. Research outputs show consistent publication trends in Decentralized orchestration frameworks (2023-2025) Digital twin deployment systems (2021-2022) Cloud-agnostic application management (2018-2020) with recent work emphasizing microservices in edge computing environments. His professional engagement includes Society of Research Software Engineering membership (since 2019) AdvanceHE fellowship (since 2020) supporting his dual focus on technical infrastructure and research education. Current supervision interests center on cloud/container orchestration, Docker/Kubernetes implementation, and statistical methods for resource optimization. His MiCADO framework remains central to multiple EU-funded projects with ongoing development for cloud-edge continuum applications.
Hamed Hamzeh serves as Lecturer in Data Science at the School of Computer Science and Engineering, University of Westminster, and is affiliated with the Centre for Parallel Computing. His academic credentials include a Ph.D. in Cloud Computing from Bournemouth University and an MSc in Data Science from Istanbul Sehir University, Turkey. Dr. Hamzeh's research centers on cloud-native resource management, computer networks, and multi-agent systems, with groundbreaking work on fairness in cloud resource allocation. He developed novel algorithms including H-FFMRA and MRFS that address multi-resource scheduling in heterogeneous environments. His expertise spans AWS, Kubernetes, Python, and optimization techniques, bridging theoretical cloud computing with industrial applications in orchestration and resource management. Analysis of his 11 publications (2017-2023) reveals an evolving research trajectory: beginning with network bandwidth allocation (2017), advancing to cloud resource fairness (2018-2021), and culminating in cloud-to-things continuum orchestration (2023). This progression demonstrates increasing system complexity while maintaining core focus on fairness metrics across distributed environments. Dr. Hamzeh actively contributes to the academic community as technical committee member for IEEE ICCCS and Distributed AI conferences, and as reviewer for Springer's Journal of Grid Computing and Journal of Supercomputing. His service reflects recognition within cloud computing research circles. Prospective students receive supervision in Cloud Computing, Artificial Intelligence, Machine Learning, Software Engineering, and Computer Networks. Current research opportunities emphasize practical implementation of resource allocation algorithms in cloud-native environments through the Centre for Parallel Computing.
Muhammad Mustafa Rafique is an Associate Professor in the Department of Computer Science at Rochester Institute of Technology's Golisano College of Computing and Information Sciences. His research specializes in optimizing large-scale computing systems, with focus areas including: High-performance computing (HPC) resource management Distributed deep learning acceleration Fault-tolerant cloud architectures GPU-accelerated checkpointing systems Serverless computing frameworks Dr. Rafique's work demonstrates consistent innovation in improving computational efficiency for containerized HPC workflows, multi-GPU scheduling, memory optimization, and distributed training pipelines. His publications frequently appear in premier IEEE/ACM conferences, reflecting contributions to systems performance engineering. While no awards or student advisees are mentioned in available materials, his research collaborations include co-authors from institutions worldwide, indicating active engagement in the high-performance computing research community. Current work explores emerging memory technologies like CXL and advanced containerization techniques for next-generation datacenters.
Dr. Matthias Becker serves as a Group Leader within the Career Development Fellow Programme at the German Center for Neurodegenerative Diseases (DZNE) in Bonn, Germany. His research integrates advanced machine learning techniques with biomedical applications, focusing on drug discovery and privacy-preserving health data analysis. His primary research interests include: Development of generative AI models for drug molecule design (DrugDiff) Privacy-preserving synthetic data generation for medical research (PriSyn project) Swarm learning applications for high-dimensional biomedical data Energy-efficient computing for molecular modeling His work bridges computational methods with neurodegenerative disease research, emphasizing practical implementations that balance innovation with ethical data handling. Becker's recent publication analyzes autoencoder architectures for molecular data, demonstrating significant reductions in data requirements (97%) and energy consumption (36%) while maintaining performance. His research shows particular strength in optimizing latent space utility for chemical applications. Becker actively collaborates with major institutions including CISPA Helmholtz Center for Information Security, QuantPi startup, and Hewlett Packard Enterprise. His technical expertise spans HPC/GPU cluster utilization, containerization for reproducibility, and emerging technologies like FPGAs for energy-efficient computing. He contributes to DZNE's computational infrastructure while advancing research in synthetic data generation for genetic and clinical applications.
Ali Mesbah is a Professor in the Department of Electrical and Computer Engineering at the University of British Columbia (UBC), where he leads the SALT lab. His research focuses on software engineering with emphasis on AI-driven software analysis, software testing, and software evolution. Previously, he was a Visiting Research Scientist at Google during 2017-2018. Dr. Mesbah received his BSc/MSc (2003) and PhD (2009) degree cum laude in Computer Science from the Delft University of Technology (TUDelft). After completing a postdoctoral fellowship with the Software Engineering Research Group at TUDelft and a Visiting Researcher position at Fujitsu Laboratories of America, he joined UBC in 2011. His research interests span software engineering with particular focus on AI-driven software analysis, software testing, software evolution, program comprehension, fault localization and repair. His work has significant applications in web application testing, JavaScript analysis, and automated program repair. He has pioneered techniques for testing modern web applications, analyzing JavaScript code, and leveraging AI for software maintenance tasks. His recent publications demonstrate a clear evolution toward integrating large language models with traditional program analysis techniques, focusing on test generation, bug repair, and understanding multi-hunk patches. His work bridges theoretical software engineering concepts with practical applications, particularly in web technologies and AI-assisted development. Amazon Research Award (2023) Killam Accelerator Research Fellowship (KARF) (2020) Killam Faculty Research Prize (2019) NSERC Discovery Accelerator (DAS) award (2016) ACM Distinguished Paper Awards at ICSE (2009, 2014) IEEE Distinguished Paper Award at ICST (2018) Best Paper Award at ESEM (2015) Best Paper Award at ICWE (2013) Dr. Mesbah has advised numerous PhD and MASc students, many of whom have gone on to positions at leading technology companies including Google, Amazon, Apple, Microsoft, and SAP. His research has been supported by various grants including the Amazon Research Award and NSERC funding. He leads the SALT lab at UBC, which focuses on software analysis, testing, and learning, with current research directions including AI-driven software engineering, web application testing, and program repair. The lab maintains active collaborations with industry partners and academic institutions worldwide.
