Jing (Roy) Yang is a Postdoctoral Research Fellow at the School of Information Systems, Faculty of Science, Queensland University of Technology (QUT). He holds a PhD from QUT (2023), and MEng and BEng degrees from Sun Yat-sen University. His research focuses on process mining, data quality, and their applications in explainable AI systems. Roy contributes to the Food Agility Cooperative Research Centre and serves as a reviewer for leading conferences like BPM and ECIS. His work bridges process mining with practical AI, emphasizing organizational models and workforce analytics. Publications span journals like Decision Support Systems and conferences such as BPM and CAiSE. He develops frameworks like OrdinoR for organizational model analysis and explores applications in robotic process automation and agronomy-informed process modeling. Roy’s academic affiliations include QUT’s Centre for Data Science and the School of Information Systems. His research interests are organized around advancing process mining techniques for real-world challenges in resource allocation, predictive analytics, and organizational knowledge extraction.
Prof. Gerald Ackner is a Professor at the University of Applied Sciences Furtwangen, based at the Tuttlingen campus. His research focuses on human factors in automated driving systems, driver behavior analysis, and human-machine interaction (HMI) design. He specializes in optimizing driver assistance systems, collision warning strategies, and visual attention management in automotive interfaces. His work bridges cognitive science and engineering, with a strong emphasis on improving road safety through better understanding of driver-system interactions. Key research interests include: Design and evaluation of proactive voice assistance systems in automated vehicles Reduction of unnecessary collision alarms through adaptive assistance strategies Analysis of non-driving task engagement in highly automated environments Development of LED-based visual attention guidance systems His publications from 2016-2025 consistently address challenges in automated driving safety, with a thematic focus on: Driver-vehicle interface design Collision avoidance system efficacy Driver behavior under automation Human perception vs. system perception discrepancies He participated in the interdisciplinary UR:BAN-MV research project, contributing to urban mobility HMI design and driver behavior prediction. His work reflects a commitment to both theoretical and applied research in automotive human factors.
Dr. Eda Mizrak is a Lecturer in Psychology at Queen Mary University of London's School of Biological and Behavioural Sciences, affiliated with the Centre for Brain and Behaviour. She holds a BSc, MSc, and PhD in relevant fields. Her research focuses on human memory mechanisms, particularly working memory (WM) and long-term memory (LTM), employing behavioral experiments, computational modeling, and neuroscientific methods. Research Interests: Factors enhancing WM capacity (e.g., encoding pauses, familiar information chunks) Neuroscientific underpinnings of memory storage and retrieval Individual differences in memory performance Cognitive modeling of memory systems Her publications highlight contributions to understanding temporal effects in WM, semantic encoding benefits, and cortico-hippocampal network interactions. Current work examines neuroscientific mechanisms behind WM limits using advanced imaging and modeling techniques. Future research will explore individual variability in memory benefits observed in prior studies. Grants & Collaborations: Active collaborations in cognitive neuroscience and experimental psychology. Research highlighted in journals like Psychological Science , Cell Reports , and Cognition . Lab Affiliation: Centre for Brain and Behaviour, Queen Mary University of London.
Sergio Moreschini is a Postdoctoral Researcher in Computing Sciences, focusing on Artificial Intelligence, Edge Computing, and MLOps. His research explores the integration of AI techniques in microservices, cloud-edge continuum systems, and distributed home automation frameworks. He has contributed to foundational studies such as a Systematic Mapping Study on AI in Microservices Life-Cycle and developed frameworks like Flexconnect for mobile computational offloading. Education: He holds a Bachelor of Science in Technology (2012) and a Higher-Degree in Computing from Università Degli Studi Roma Tre (2016). His work aligns with UN Sustainable Development Goal 4 (Quality Education) through contributions to educational tools and methodologies. Research Interests : Moreschini investigates AI lifecycle management, edge-cloud system orchestration, vulnerability analysis in open-source components, and generative AI applications in software architecture. Key areas include fault-tolerant distributed systems, cognitive cloud continuum frameworks, and MLOps tool ecosystems. Recent Trends in Publications : Recent work emphasizes MLOps adoption challenges, self-organizing edge computing for visual SLAM, and best practices in resource provisioning for cognitive systems. He has explored trade-offs between continuous training and transfer learning in edge environments, and evaluated vulnerability severity metrics in open-source software. Awards : Won the Best Paper Award in 2022 for contributions to industrial edge service scheduling. Data Contributions : Co-created datasets like RARE (cloud-native memory anomalies) and CIVIT (integral microscopy recordings). His collaborative projects include the 6GSoft initiative for edge-cloud continuum systems and the OSSARA tool for open-source component risk assessment. Active in international conferences like IoT and SEAA, he bridges academic research with industrial applications in edge computing and AI infrastructure.
Joseba Martinez is an Assistant Professor of Economics at London Business School, where he contributes to the Department of Economics within the Faculty of Economics. He holds a BSc from University College London, an MSc from the London School of Economics and Political Science, and a PhD from New York University, all in economics. BSc, University College London, Economics MSc, London School of Economics and Political Science, Economics PhD, New York University, Economics His research spans macroeconomics, financial economics, and economic growth, with a strong emphasis on automation, productivity, technology adoption, tax policy, and financial stability. His work investigates how technological change affects labor markets and income distribution, how fiscal and monetary policies influence inflation and innovation, and how financial systems can be designed to mitigate crises. He has published in leading journals such as the Review of Economic Studies , American Economic Journal: Macroeconomics , and Journal of International Economics . The themes in his recent publications reveal a consistent focus on structural economic transformations—particularly those driven by technology and policy. His research uses both theoretical modeling and empirical analysis to understand business cycle dynamics, the impact of tax changes, and the efficiency of financial markets. A recurring thread is the role of heterogeneity across firms in shaping aggregate outcomes, especially in the context of AI and automation adoption. CEPR Research Affiliate (Macroeconomics) Visiting Scholar, International Monetary Fund Consultant, New York-based investment fund He has received no explicitly mentioned scientific awards in the provided text. His advisory role includes PhD and Master’s students, though specific names are not listed. His research is supported through institutional affiliations and collaborations with central banks and international organizations. He is actively engaged in public discourse through articles in Think at London Business School , where he discusses the economic implications of AI, tax policy, and global political events. Joseba Martinez is affiliated with the Think at London Business School platform and contributes to public-facing economic commentary. His work bridges academic rigor with policy relevance, particularly in the areas of innovation, taxation, and financial regulation.
Wojciech Thomas is a Lecturer at the Department of Applied Informatics, Faculty of Information and Communication Technology, Wrocław University of Science and Technology. He teaches courses including Technologies Supporting Software Development (DevOps) , Cloud Computing , and Script Languages . Since 2016, he has directed the postgraduate program Computer Network Administration , designed for professionals seeking advanced knowledge in network/server management. His research focuses on DevOps, cloud technologies (AWS/Azure), automation of complex IT environments, web applications, and software engineering. He has published on topics ranging from task scheduling algorithms to trends in software engineering education. His publications (2000–2021) reflect interdisciplinary work in computer science, operations research, and educational methodology. Common themes include optimization algorithms, cloud infrastructure, and academic curriculum development.
Florian Steurer is a PhD student at the Max Planck Institute for Informatics, affiliated with the Internet Architecture department. He has served as a Tutor in the Hot Topics in Data Networks Seminar during multiple terms (2022–2025). Education: Master of Computer Science (Julius-Maximilians-Universität Würzburg, 2016–2018), Bachelor of Computer Science (DHBW Stuttgart, 2013–2016). Professional background includes software development roles at codeunity GmbH (2017–2018, 2018–2022) and prior industry experience at HOMAG GmbH (2013–2016) and Student at HOMAG GmbH (2013–2016). His research focuses on network architecture, fault-tolerant and scalable systems, DNS, and internet traffic analysis. Recent publications examine DNS tree exploration biases, CrowdStrike outage impacts, and dynamic DNS root server measurement. Key scientific achievements include a Best Paper Award at PAM 2025 and selection for the Internet Society Pulse Research Fellowship. His work bridges theoretical network analysis with practical infrastructure resilience.
Xinyu Qin is a Professor at the Department of Electrical and Computer Engineering within the School of Information Engineering at Guangdong University of Technology. His research focuses on advanced robotics, signal processing, and integrated circuit design, contributing to fields like multi-manipulator systems and Delta-Sigma modulators. Education: Affiliated with prestigious institutions through collaborative research Research Interests: Robotics, Machine Learning, Electrical Engineering His recent publications (2023-2025) demonstrate expertise in robotic task allocation, high-speed circuit design, and explainable AI for healthcare. Award-winning work includes Interactive Explainable Deep Survival Analysis (2024) and SVP: Safe and Efficient Speculative Execution Mechanism through Value Prediction (2023). Key collaborations involve Guoxing Wang and Liang Qi across 16 records. Current projects involve optimizing convolutional neural network accelerators, analyzing atmospheric river impacts on Greenland's crustal deformation, and advancing MASH Delta-Sigma modulator architectures. His work bridges theoretical innovation with practical applications in smart energy systems and autonomous robotics.
Birthe Kåfjord Lange is an Associate Professor at the Department of Leadership and Organization, School of Communication, Leadership and Marketing, Kristiania University of Applied Sciences. Her primary teaching focus is on management disciplines, with extensive experience in executive education programs. She specializes in Change Management , Managerial Discretion , and Work-Integrated Learning , emphasizing the development of managers and organizational ambidexterity. Her research explores themes such as strategic adaptation during crises, digital transformation challenges, and the psychological dimensions of workplace change. Recent work includes studies on organizational ambidexterity in sports organizations and the role of mentorship in leadership development. Key publications span topics like uncertainty management in the 'New Normal', HR strategies for evolving work environments, and time management in Norwegian managerial roles. Her 2020-2025 works highlight a trend toward analyzing modern workplace dynamics and leadership challenges in hybrid/digital settings. Lange has no listed scientific awards but maintains active research output with 15+ publications since 2002. No grants or advising activities are explicitly mentioned in the provided data.
George Kousiouris is an Associate Professor at the Department of Informatics and Telematics , Harokopio University of Athens . He holds a Ph.D. in Cloud Computing from the National Technical University of Athens (2012) and a Dipl. Eng. in Electrical and Computer Engineering from the University of Patras (2005). His research focuses on Cloud Platforms , Serverless Computing (FaaS) , IoT Infrastructure , and Performance Engineering . He has led major EU-funded projects such as H2020 PHYSICS (lead architect), BigDataStack , and CloudPerfect , contributing to cloud service benchmarking, FaaS frameworks, and edge-cloud collaboration. His work emphasizes practical applications in healthcare, smart agriculture, and urban network analysis. Over 70 publications highlight his expertise in cloud resource optimization , service-level agreements , and data-driven infrastructure management . His recent work explores sustainable computing , human-AI collaboration , and conversational AI for MLOps . Key Projects: PHYSICS, BigDataStack, CloudPerfect, SLALOM, COSMOS Research Highlights: FaaS performance benchmarking, IoT event processing, hybrid-cloud workflows Awards/Grants: Multiple EU H2020 and FP7 project leadership roles He advises on cloud migration methodologies (e.g., ARTIST framework) and contributes to regulatory compliance frameworks like GDPR via semantic ontologies.
Vassilis Papakostopoulos is an Assistant Professor at the Department of Product and Systems Design Engineering, University of the Aegean, specializing in Ergonomics. His academic background includes a PhD in Cognitive Psychology (Panteion University, 2008), MSc in Ergonomics (Loughborough University, 1998), and BSc in Psychology (University of Crete, 1996). He has extensive research experience in driver behavior analysis, human-robot interaction, and workplace design. His research focuses on visual perception, motor coordination, and ergonomics applications in transportation systems. Key areas include advanced driver assistance systems (ADAS), human factors in autonomous vehicles, and safety in urban environments. He has contributed to major EU-funded projects such as interACT, ASK-IT, and PReVENT, addressing challenges in traffic safety and human-machine interaction. Teaching responsibilities include undergraduate and graduate courses on ergonomics, user-centered design, and product development. He has published over 20 peer-reviewed articles, emphasizing holistic approaches to driver behavior analysis and interdisciplinary ergonomics applications. As Greece’s representative in the Centre for Registration of European Ergonomists (CREE), he promotes professional standards in ergonomics practice. Recent research trends include autonomous vehicle interactions, motorcycle safety, and organizational policies affecting risky driving behaviors. His work bridges historical ergonomic principles (e.g., ancient Athenian court design) with modern challenges in smart city infrastructure and human-robot collaboration.
Gautam Srivastava is a Professor in the Department of Mathematics & Computer Science at Brandon University (BU), holding concurrent roles as Visiting Professor at Lebanese American University and Adjunct Associate Professor at Lakehead University. His research focuses on Blockchain Technology, Cryptography, Big Data, and Privacy-Preserving Systems. He actively supervises graduate students requiring strong academic credentials. Education: Ph.D. (Computer Science, University of Victoria, 2012), M.Sc. (Computer Science, University of Victoria, 2007), B.Sc. (Mathematics & Computer Science, Briar Cliff University, 2004) Roles: Holds visiting appointments at institutions in Lebanon, Taiwan, and China, and leads research in Cyber-Physical Systems and IoT Security. His research interests emphasize secure communication protocols, federated learning frameworks, and applications of AI in healthcare and industrial systems. Notable work includes blockchain-enhanced IoT security and privacy-preserving machine learning models. Awards: Best Oral Presentation at Fuzzy Systems and Data Mining (FSDM 2017) Grants: Over $200K in funding from NSERC, MITACS, and CIRA for projects on IoT security, federated learning, and edge computing. Dr. Srivastava’s current projects explore quantum-resistant MQTT protocols, federated learning for healthcare diagnostics, and smart city sensor systems.
Bruce Oddson serves as Associate Professor in Laurentian University's School of Kinesiology and Health Sciences, where his interdisciplinary research bridges health psychology, rehabilitation science, and educational kinesiology. His work demonstrates consistent collaboration across medical, psychological, and outdoor education domains with primary focus on practical health outcome measurement. His academic foundation includes: B.A. (Hons) from University of Waterloo M.A. from University of Guelph Ph.D. in Psychology from University of Toronto Dr. Oddson's research spans exceptionally diverse territories including child communication development (notably through the FOCUS assessment system), wilderness immersion pedagogy, cognitive load management, and cerebral palsy rehabilitation. His approach integrates psychological principles with physical activity contexts, emphasizing real-world applications for wellness improvement. The FOCUS tool development represents a significant thread through his work, evolving from initial conception to validated outcome measurement. Analysis of his publication history reveals growing specialization in communication assessment tools while maintaining parallel investigations into adventure education and cognitive performance. Recent work shows increased methodological sophistication in longitudinal tracking and outcome validation, particularly in pediatric rehabilitation contexts. His 2022 wilderness immersion study exemplifies the Northern Ontario-focused, experiential learning orientation characteristic of Laurentian-based research. No scientific awards were documented in the source materials. While collaborative patterns indicate extensive research partnerships, specific information regarding graduate student supervision or grant funding mechanisms was not provided in available documentation. Operational details about dedicated laboratories or research teams were not specified, though his physical location at the B.F. Avery Physical Education Centre suggests integration with campus recreation and kinesiology facilities.
Dominik Baumann is an Assistant Professor at the Department of Electrical Engineering and Automation at Aalto University in Espoo, Finland. His research focuses on the interplay of systems and control theory with machine learning and communication networks, with a current emphasis on causal inference in control systems. Education: Diploma in Electrical Engineering from TU Dresden, Germany (2016) PhD from KTH Stockholm, Sweden (2020), supervised by Sebastian Trimpe (Max Planck Institute) and Karl H. Johansson Postdoctoral positions at RWTH Aachen University (1 year) and Uppsala University with Thomas Schön (1 year) Dr. Baumann's research bridges theoretical foundations with practical applications in robotics, wireless networks, and decision-making systems. His work spans safe reinforcement learning, event-triggered control systems, causal inference in dynamical systems, and ergodicity economics perspectives on long-term decision-making. He applies mathematical rigor to address challenges in resource-constrained environments, particularly focusing on safety guarantees and computational efficiency for real-world implementation. His recent publication record demonstrates a strong trajectory in safe learning-based control, with increasing focus on ergodicity economics in reinforcement learning, multi-agent coordination, and human-robot interaction. The research consistently balances theoretical guarantees with practical implementation constraints, particularly in bandwidth-limited wireless control systems and robotics applications. Scientific Awards: Best Paper Award for 'Feedback control goes wireless: Guaranteed stability over low-power multi-hop networks' at ACM/IEEE International Conference on Cyber-Physical Systems (2019) Dr. Baumann maintains extensive international collaborations, evidenced by numerous seminar invitations worldwide including Oxford University, ETH Zürich, University College London, and institutions across Asia. His research program addresses fundamental challenges in cyber-physical systems with applications in industrial automation, robotics, and the Internet of Things, securing research funding for projects focused on safe learning in control systems and wireless cyber-physical systems. His research group at Aalto University develops both theoretical foundations of learning-based control and practical algorithms for real-world deployment, with active software repositories on GitHub related to predictive triggering, causal structure identification, and ergodic reinforcement learning.
Joe K. Kearney is a Professor in the Department of Computer Science at the University of Iowa and the University of Minnesota. His career spans over three decades, focusing on virtual reality, computer vision, and human-computer interaction research. Key affiliations: University of Iowa (Iowa City, IA, USA), University of Minnesota (Minneapolis, MN, USA) Research domains: Virtual environments, perception-action coupling, motion capture systems, pedestrian behavior simulation Research trends show sustained contributions to immersive visualization , autonomous navigation , and human factors in virtual reality . His 2014-2025 work explores AR-based pedestrian safety systems, while earlier studies (1986-2006) established foundational frameworks for virtual environment simulation and optical flow analysis. Long-term collaborations with Jodie M. Plumert (1986-2021), James F. Cremer (1986-2009), and Pooya Rahimian (2015-2017) demonstrate consistent team research in VR cognition and autonomous systems.
