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Kim WernerView profile

Professor

• Climate Change Adaptation
• Sustainability and Climate Protection
• Diversity
• +5 more

Prof. Dr. Kim Werner is a Professor of Business Administration, specializing in Event Management, at the Faculty of Economics and Social Sciences (WiSo) of Osnabrück University of Applied Sciences. Her academic career spans roles in industry and academia, including positions at Lufthansa, Tourism Australia, and the Auckland University of Technology. She holds a PhD in the impact of mega-events on regional collaboration and knowledge transfer. Education: PhD in Event Management (Auckland University of Technology, 2013) Bachelor's in International Tourism Management (Bremen University of Applied Sciences, 2004) Research Interests: Climate Adaptation in Events Sustainability and Climate Protection Event Co-Creation and Value Creation Knowledge Transfer in Destinations Funding and Projects: "KlimaEvent": Climate-Resilient Event Supply Chains (BMUV-funded, 2023–2026) "Kreislaufwirtschaft in der Messewirtschaft" (DBU-funded, 2024–2026) VR-Based Climate Adaptation Training (STIL-funded, 2025–2027) Awards and Roles: Editorial Board Member: Event Management and Journal of Policy Research in Tourism, Leisure and Events Scientific Advisor: degefest e.V. (Congress and Seminar Industry Association) Labs and Teams: Leading research groups on climate adaptation and sustainable event design, collaborating with the University of Osnabrück and local municipalities.

Bertram LudäscherView profile

Professor

• Data and Knowledge Management
• Scientific Workflows
• Data Provenance
• +4 more

Bertram Ludäscher is a Professor at the School of Information Sciences at the University of Illinois, with affiliate appointments at the National Center for Supercomputing Applications (NCSA) and the Department of Computer Science. He leads the Center for Informatics Research in Science and Scholarship and directs the NSF-funded Euler project focused on logic-based taxonomic alignment. His research emphasizes scientific workflow systems, data provenance, and knowledge representation. Ludäscher co-founded the Kepler workflow system and contributed to DataONE’s provenance initiatives. He previously held roles at UC Davis and the San Diego Supercomputer Center. Education: PhD in Computer Science, University of Freiburg (1998) MS in Computer Science, Technical University of Karlsruhe (1992) Research Interests: Data and knowledge management, scientific workflows, provenance tracking, biodiversity data curation, and taxonomic reconciliation using logic-based methods. Ludäscher’s work bridges computational methods with biological and environmental sciences, focusing on reproducibility and interoperability in data-driven research. Recent Work Trends: His articles address provenance unification in databases, workflow automation recovery, and resolving taxonomic conflicts. Key themes include reproducibility frameworks (e.g., the Whole Tale project), ontology alignment, and scalable workflow systems for diverse scientific domains. Awards: 2018 ProvenanceWeek Best Paper, Google Scholar Classic Papers recognition. Advising & Grants: Leads NSF-funded projects like Euler and Kurator. Active in collaborative initiatives such as DataONE and the Whole Tale. Courses taught include data curation, workflow design, and data cleaning methodologies. Labs/Teams: Directs the Center for Informatics Research in Science and Scholarship and collaborates with NCSA on cyberinfrastructure projects. Key partnerships include the San Diego Supercomputer Center and UC Davis Genome Center.

Ella HaigView profile

Associate Professor

• Intelligent Systems
• User Modelling and Personalisation
• Data Mining
• +7 more

Ella Haig is an Associate Professor of Artificial Intelligence at the University of Portsmouth, UK, affiliated with the School of Computing within the Faculty of Technology. She is also a member of the Portsmouth AI and Data Science Centre, Future of Law, Innovation and Technology Research Centre, and Centre for Cybercrime and Economic Crime. Her academic journey includes a PhD in Computer Science from Birkbeck College (University of London), an MSc in Learning Technologies from the National College of Ireland, and a Postgraduate Certificate in Learning and Teaching from the University of Portsmouth. Her research focuses on Intelligent Systems, User Modelling, Data Mining, and Decision Support, with notable contributions to emotion recognition, machine learning, and educational data mining. Ella has published over 140 works, including articles on multimodal emotion detection and comparative analyses of AI models like GPT-3 and BERT. She actively contributes to conferences, such as the IEEE World Congress on Computational Intelligence and the International Conference on Educational Data Mining. Ella has secured grants totaling over £235,000 for projects like the KTP Citizens Advice initiative, exploring technology solutions for public services. Her work aligns with UN Sustainable Development Goals, particularly in advancing education and innovation. Notable achievements include a 2023 Best Paper Award for her research on multimodal emotion recognition systems.

Stephen QuackenbushView profile

Professor

• International Conflict
• Deterrence Theory
• Strategic Studies
• +4 more

Stephen L. Quackenbush is a Professor and Director of Defense and Strategic Studies at the Truman School of Government and Public Affairs, University of Missouri. His expertise spans international conflict, deterrence theory, strategic studies, and bridging academic-policy divides. He created the MA in Defense and Strategic Studies program and previously served as President of the International Studies Association-Midwest. Education: Bachelor of Science (BS) in Aerospace Engineering, Illinois Institute of Technology Master of Science (MS) in Aerospace Engineering, Georgia Institute of Technology Master of Arts (MA) and Doctor of Philosophy (PhD) in Political Science, University at Buffalo, SUNY Research Interests: General and extended deterrence mechanisms Gray zone conflicts and geopolitical strategy Counterinsurgency dynamics and military effectiveness Policy applications of strategic studies His recent work emphasizes updating conflict datasets (e.g., Politically Active Dyads) and addressing accidental warfare risks. He has authored influential books like Understanding General Deterrence and International Conflict: Logic and Evidence . Awards: Recipient of the Bronze Star Medal for service during Operation Iraqi Freedom while in the U.S. Army. Led initiatives in curriculum development (MA program creation) and contributed to defense policy debates through game-theoretic models of extended deterrence in Northeast Asia and Middle Eastern conflicts.

• Computer Vision
• Machine Learning
• Deep Learning
• +5 more

Dr. Nathanael L. Baisa is a Lecturer in Artificial Intelligence at De Montfort University (DMU), part of the Computing, Engineering and Media faculty within the School of Computer Science and Informatics. His academic career includes roles as a senior research associate at Lancaster University, researcher at AnyVision, and research fellow at the University of Lincoln, focusing on computer vision and machine learning projects funded by ERC, EPSRC, and Innovate UK. Education: PhD in Electrical Engineering (Computer Vision/ML - Heriot-Watt University, 2018) MSc in Computer Vision and Robotics (Erasmus Mundus program, 2013) Research focuses on computer vision applications including object detection, scene understanding, autonomous systems, and biometrics. He leads work on deep learning for visual tracking, hand-based person identification, and robotic perception. He teaches courses like Introduction to Computer Vision and Deep Learning frameworks. His recent publications emphasize vision-language models, multi-object tracking algorithms, and geoscience machine learning applications. He collaborates with the Institute of Artificial Intelligence (IAI) and contributes to interdisciplinary projects in robotics and energy exploration.

Prasad TadepalliView profile

Professor

• Artificial Intelligence
• Machine Learning
• Reinforcement Learning
• +5 more

Prasad Tadepalli is a Professor in the School of Electrical Engineering and Computer Science at Oregon State University, serving as the AI Graduate Program Director. He is affiliated with the Collaborative Robotics and Intelligent Systems Institute. His expertise spans artificial intelligence, machine learning, reinforcement learning, and automated planning, with impactful contributions to explainable AI and natural language processing. Tadepalli holds a Ph.D. from Rutgers University and M.Tech/B.Tech degrees from Indian institutions. He has authored over 100 papers, organized international conferences, and received awards such as the AAAI Outstanding Paper Award (2013) and ICAPS Best Student Paper (2009). Education: Ph.D. (Rutgers University, 1990), M.Tech (IIT Madras, 1981), B.Tech (Regional Engineering College, 1979) His research focuses on advancing AI through techniques like relational planning, reinforcement learning, and interpretable models. Recent work includes integrating planning and RL for multiagent systems and developing explainable models via tree ensemble compression. His articles highlight contributions to time-series imputation, adversarial attacks on bandits, and chess rating estimation using CNN-LSTM networks. Awards: AAAI Outstanding Paper Award (2013), ICAPS Best Student Paper (2009) Tadepalli emphasizes independent thinking in students and has advised numerous researchers. His work bridges theoretical AI with practical applications, such as robotics and data-driven decision-making.

Gao HuijunView profile

Professor

• Networked Control Systems
• Signal Processing
• Image Processing
• +7 more

Prof. Gao Huijun is a Full Professor at the School of Aeronautics and Astronautics, Harbin Institute of Technology (HIT), where he also serves as Director of the Research Institute of Intelligent Control and Systems. He holds honorary positions at The University of Hong Kong and the University of Alberta. His research focuses on networked control systems, robotics, and signal processing, with over 380 SCI publications and an H-index of 120. Positions: Director of Interdisciplinary Science Research Center (2019–present), Dean of School of Science (2015–2019), and Honorary Professor at The University of Hong Kong (2009–present). Education: Ph.D. in Control Science and Engineering from HIT (2005), postdoc at University of Alberta (2005–2007). Research interests span networked control systems, multi-agent systems, and opto-mechanical integration. His work has led to 100+ patents and prestigious awards like the IEEE Fellow (2013) and National Natural Science Award (2014). Editorial roles include Co-Editor-in-Chief of IEEE Transactions on Industrial Electronics and Senior Editor roles in multiple journals. He has advised over 30 doctoral students, many of whom hold academic or industry leadership roles. Key Awards: National Natural Science Award (2014), China Youth May Fourth Medal (2011), Highly Cited Researcher (2014–2020). Grants: Chief Scientist of National Key R&D Programs, Director of China Postdoctoral Science Foundation. Labs/Teams: Leads the Research Institute of Intelligent Control and Systems, focusing on interdisciplinary projects like AOI systems and industrial robotics.

Rayna DimitrovaView profile

Assistant Professor

• Verification
• Reactive Systems Synthesis
• Control and Robotics
• +3 more

Rayna Dimitrova is a Tenure-track faculty member at the CISPA Helmholtz Center for Information Security in Saarbrücken, Germany. Previously, she held positions as Lecturer (Assistant Professor) at the University of Sheffield and University of Leicester, and postdoctoral roles at the University of Texas at Austin and the Max Planck Institute for Software Systems. She earned her PhD from Saarland University. Her research focuses on formal methods, including verification and synthesis of reactive systems, applications to control and robotics, quantitative analysis of probabilistic systems, and information-flow security. Key interests include strategic synthesis under partial observability, probabilistic uncertainty, and continuous dynamics, with applications to autonomous systems. She has served in numerous prestigious roles, including PC co-chair for VMCAI 2024, HYPER 2023, and SMT 2018. Her awards include the RS3 Best Paper Award (VMCAI 2012) and nominations for ETAPS (TACAS 2015) and EMSOFT (2014) Best Paper Awards. Her research group includes PhD students Rafael Dewes, Philippe Heim, and Saleh Soudijani. She has taught courses on reactive synthesis, program analysis, and decision procedures at multiple institutions, including the University of Sheffield and TU Kaiserslautern.

• High-performance Computing
• Energy-efficient Computing
• Machine Learning
• +3 more

Dr. Ngoc Nha Vi Tran is an Associate Professor of Computer Science at UiT The Arctic University of Norway. She holds a PhD from UiT and was a visiting scholar at Rutgers University, USA. Her research focuses on high-performance and energy-efficient computing, machine learning, and bioinformatics. She is a member of the NORA.startup Steering Group and leads the Arctic Green Computing Group. Education: PhD in Computer Science (UiT), M.Sc. in Software Engineering via Erasmus Mundus (Blekinge Institute of Technology, Sweden & Technical University of Kaiserslautern, Germany). Research interests include energy-efficient algorithms, bioinformatics tools (e.g., vCOMBAT), and applications of machine learning in healthcare and robotics. She teaches courses such as INF-2200 Computer Architecture, INF-2900 Software Engineering, and INF-2202 Concurrent Programming. Her work spans computational models for antibiotic target-binding, runtime energy optimization (REOH framework), and power models for embedded systems (RTHpower/ICE). She contributed to the EXCESS project on energy-efficient computing systems. Labs/Teams: Arctic Green Computing Group, EXCESS consortium.

Michael Reichhardt HansenView profile

Associate Professor

• Formal Methods
• Embedded Systems
• Real-Time Systems
• +3 more

Michael Reichhardt Hansen is an Associate Professor at the Department of Applied Mathematics and Computer Science (DTU Compute) at the Technical University of Denmark. He holds a MSc in Engineering (1982) and a PhD in Computer Science (1987) from DTU. He has held postdoctoral and visiting roles, including a fellowship at IBM Research Center (1984–1985) and a guest professorship at Oldenburg University (1992–1993). His research focuses on formal methods, embedded systems, and real-time systems, emphasizing mathematically grounded software development. He has authored/co-authored three books and over 70 scientific articles. Research interests include model-based program construction, temporal logic, functional programming, and ontology alignment. He has led projects on ontology matching frameworks (e.g., MDMapper) and formal methods for real-time systems. Hansen has supervised PhD students in areas like data integration and genetic circuit synthesis. He has contributed to international conferences and serves as a reviewer/examiner for academic programs. His work bridges theoretical foundations with industrial applications, particularly in embedded systems and data management. He has collaborated internationally, with projects addressing ESG reporting standards and regulatory compliance through automated data traceability.

• Electric Vehicles
• Fuzzy Logic
• Blockchain
• +5 more

Shahid Hussain is an Associate Professor at King Abdullah University of Science and Technology (KAUST) in the Computer, Electrical and Mathematical Sciences and Engineering Division. His research spans multiple domains including electric vehicle infrastructure, blockchain technology, and intelligent systems for IoT applications, with a focus on practical implementations of computational intelligence techniques. Dr. Hussain's research interests include: Electric Vehicles and Smart Grid Integration Fuzzy Logic and Intelligent Decision Systems Blockchain Applications for Security and Privacy Machine Learning for IoT and Healthcare Applications Energy Management Systems Smart City Infrastructure Development His recent publications demonstrate a strong focus on applying hybrid computational approaches to solve complex engineering problems, particularly in transportation systems and healthcare applications. Dr. Hussain has published extensively in IEEE journals, with particular emphasis on innovative approaches to electric vehicle charging infrastructure, secure IoT systems, and blockchain-enabled solutions for real-world challenges. Dr. Hussain maintains active collaborations with researchers globally, particularly with Reyazur Rashid Irshad, Young-Chon Kim, and Subhasis Thakur. His work bridges theoretical advancements with practical implementations, as evidenced by his research on fuzzy integer linear programming for EV charging stations and blockchain-enabled security frameworks for medical IoT systems.

• Strategic Leadership
• Corporate Governance
• Organizational Search
• +3 more

Wei Shen is the Dean’s Council Distinguished Professor and Chair of the Department of Management and Entrepreneurship at Arizona State University’s W. P. Carey School of Business. He previously served as Associate Dean for W. P. Carey China Programs and Faculty Director of the China Executive MBA Program. His research focuses on CEOs, boards of directors, and organizational impacts, with publications in top-tier journals like Administrative Science Quarterly and Strategic Management Journal. Educated at Peking University (B.S. in Psychology) and Texas A&M University (Ph.D. in Business Administration), Shen has received awards including the Robert J. Litschert Best Doctoral Student Paper Award and the Mays Outstanding Ph.D. Alumni Award. He currently serves as President-Elect of the International Association for Chinese Management Research (IACMR). His research interests include strategic leadership, corporate governance, organizational search mechanisms, and research methodology. Key themes in his work address CEO accountability, board dynamics, and the interplay between organizational performance and governance structures. Shen’s publications span over two decades, consistently exploring governance mechanisms, strategic decision-making, and leadership succession. Recent work examines tiered status hierarchies in competitive actions, gender bias in CEO roles, and compliance with governmental mandates. His books include Empirical Methods in Organization and Management Research (4th ed.) and Organizational Management: A Perspective of Chinese Enterprises in the Age of Digital Intelligence . He has advised numerous academic programs and holds leadership roles in advancing Chinese management research. His courses include doctoral seminars, strategic management, and global corporate strategy, reflecting his commitment to educating future business leaders.

Glen ChouView profile

Assistant Professor

• Robotics
• Trustworthy Autonomy
• Machine Learning
• +4 more

Glen Chou is an Assistant Professor in the Department of Electrical and Computer Engineering at Georgia Tech. He holds dual B.S. degrees from UC Berkeley (Electrical Engineering & Computer Science and Mechanical Engineering) and M.S./Ph.D. degrees from the University of Michigan (Electrical & Computer Engineering). Prior to Georgia Tech, he was a postdoctoral researcher at MIT CSAIL. Chou directs the Trustworthy Robotics Lab, focusing on algorithms for general-purpose robots and autonomous systems to ensure capability, safety, and resilience in real-world conditions. His research integrates control theory, machine learning, optimization, and formal methods. He emphasizes both theoretical foundations (e.g., proving algorithmic properties) and practical deployment on real robots. Key research areas include trustworthy autonomy, human-robot interaction, and constraint learning from demonstrations. His lab addresses challenges in perception, motion planning, and system reliability through interdisciplinary approaches. Chou has received notable awards including the Robotics: Science & Systems Pioneer (2022), NDSEG Fellowship (2019), and NSF Graduate Fellowship (2019). His work bridges foundational theory with real-world applications, with a focus on safety-critical systems.

William IdsardiView profile

Professor

• Neurolinguistics
• Phonology
• Psycholinguistics
• +3 more

William Idsardi is a Professor of Linguistics at the University of Maryland, affiliated with the Program in Neuroscience and Cognitive Science and the Maryland Language Science Center. His research focuses on neurolinguistics, phonology, and psycholinguistics, combining experimental, computational, and theoretical approaches. Key areas include phonological abstraction mechanisms, the neural basis of speech perception, and the computational foundations of phonological patterning. His work bridges disciplines, investigating how phonological categories are represented in the brain using neuroimaging techniques like MEG. Notable contributions address the role of categorical perception in fricative sounds, the phoneme hypothesis, and computational complexity differences between phonology and syntax. Collaborative projects explore dialect perception, infant lexical learning, and cross-linguistic vowel systems. Publications span phonological theory, neuroimaging studies, and computational linguistics, emphasizing interdisciplinary methods. His research has implications for understanding language acquisition, speech disorders, and the evolution of linguistic structure. Labs associated with his work include the EEG/ERP Lab and Maryland Neuroimaging Center.

Sam LindleyView profile

Associate Professor

• Programming Languages
• Formal Methods
• Type Systems
• +3 more

Sam Lindley is a Reader in Programming Language Design and Implementation at the School of Informatics, University of Edinburgh. He holds a UKRI Future Leaders Fellowship in Effect Handler Oriented Programming. His research focuses on foundational aspects of programming languages, including effect systems, session types, type theory, and functional programming. Key research interests span algebraic effects, concurrency models, type systems for resource management, and language implementation techniques. Lindley's work bridges theory and practice, addressing challenges in systems programming, web technologies (e.g., WebAssembly), and compiler design. Recent publications (2023–2025) emphasize effect handlers for low-level languages (e.g., C, WebAssembly), modal type systems for memory management, and formal semantics for concurrent systems. His work often explores how advanced type systems can improve expressivity and efficiency in programming models. Scientific Awards: UKRI Future Leaders Fellowship Labs/Teams: Laboratory for Foundations of Computer Science (LFCS) Grants: Active funding via UKRI Fellowship