جست‌وجوی استاد و پژوهشگر

John McNamaraمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• Cybersecurity
• Transportation Systems
• +۳ مورد دیگر

John McNamara is an IBM Master Inventor and Advanced Visiting Research Fellow at the University of Sheffield, holding Honorary Professorships at University College London (UCL) and Sheffield Hallam University. He specializes in interdisciplinary innovation across cybersecurity, transportation systems, and artificial intelligence, leveraging technologies like Cloud and Watson for Tech for Good initiatives. His roles include IBM Technical Specialist, IBM Thought Leader, and Open Group Distinguished Technical Specialist, with industry expertise spanning defense, finance, and healthcare sectors. Education: BSc (Hons) in Information Systems from the University of Hull. Research focuses on patentable inventions addressing complex event processing, automated systems optimization, and regulatory compliance. Key innovations include intelligent fuel management systems, automated style-checking frameworks, and goal-directed simulation tools for business processes. His work bridges academic research with real-world industry applications. Awards: IBM Master Inventor IBM Thought Leader Technical Specialist Open Group Distinguished Technical Specialist Collaborates with IBM UK University Programs to develop socially impactful technologies. Active in creating solutions for disease control, banking systems, and defense applications through cross-disciplinary partnerships.

Kristopher Micinskiمشاهده پروفایل

استادیار

• Programming Languages
• Static Analysis
• Formal Methods
• +۴ مورد دیگر

Kristopher Micinski is an Assistant Professor in the Electrical Engineering and Computer Science Department at Syracuse University. His research focuses on scalable program analysis, static analysis, and formal methods applied to computer security and privacy. He holds a PhD in Computer Science from the University of Maryland and a BS in Computer Engineering from Michigan State University. Education: PhD, Computer Science, University of Maryland at College Park BS, Computer Engineering, Michigan State University Research Interests: His work bridges theory and application of program analyses, emphasizing scalable static analysis frameworks, Datalog optimization for distributed systems, and security applications. Recent efforts include GPU-accelerated Datalog engines and large-scale malware analysis pipelines like Assemblage. Grants & Projects: NSF PPoSS Large: $1M grant for declarative analytics DARPA V-SPELLS: $400K for legacy software optimization Assemblage: $350K DoD grant for malware classification Teaching: He teaches undergraduate and graduate courses on programming languages (CIS352) and formal methods (CIS700), with materials publicly available on YouTube.

Ruben Martinsمشاهده پروفایل

استاد پژوهشی

• Constraint Programming
• Program Synthesis
• Software Analysis
• +۳ مورد دیگر

Ruben Martins is an Assistant Research Professor and Master’s Program Director at the School of Computer Science, Carnegie Mellon University. He holds a Ph.D. from the Technical University of Lisbon, followed by postdoctoral research at the University of Oxford and UT Austin. His work focuses on constraint programming, program synthesis, and formal verification, with applications in improving programmer productivity and automating data science tasks. Education: Ph.D. in Computer Science, Technical University of Lisbon (2013) Postdoctoral Researcher, University of Oxford (2014-2015) Postdoctoral Researcher, UT Austin (2015-2017) Ruben's research bridges constraint programming with program synthesis, aiming to automate tasks such as vulnerability detection, code repair, and SQL synthesis. He developed Open-WBO , a MaxSAT solver that won multiple gold medals and is used in real-world optimization scenarios like seating arrangements for events. His work integrates large language models (LLMs) with traditional methods to enhance software analysis and debugging. Awards: Distinguished Paper Award at PLDI 2018 Gold Medal in MaxSAT Competitions for Open-WBO Advising & Grants: Ruben advises Master’s students and directs courses such as 15639, 15604, and others. His research has been supported by grants focusing on program synthesis and cybersecurity. Labs/Teams: Leads development of Open-WBO and contributes to projects like Crabtree (Rust API testing) and Pryde (evasion attack analysis).

Peter Dybjerمشاهده پروفایل

استاد

• Intuitionistic Type Theory
• Categorical Type Theory
• Proof Assistants
• +۹ مورد دیگر

Peter Dybjer is a Professor of Computing Science at the Department of Computer Science and Engineering, Chalmers University of Technology in Sweden. He is a leading researcher in the field of type theory, with a focus on intuitionistic type theory, categorical semantics, and proof assistants. His work bridges foundational aspects of mathematics and computer science, emphasizing constructive methods and formal verification. Research Interests: Intuitionistic Type Theory and its categorical semantics Proof assistants and formal verification Inductive and inductive-recursive definitions Game semantics and normalization techniques Dependent type systems and their applications Homotopy Type Theory and univalent foundations Activities & Contributions: Editor of the Bulletin of Symbolic Logic Member of program committees for conferences like TYPES, FSCD, and MFPS Keynote speaker at events including the European Congress of Mathematics and the Hausdorff Research Institute's Summer School on Types, Sets, and Constructions Initiated and directed the Master's Program in Computer Science – Algorithms, Languages, and Logic at Chalmers Teaching & Outreach: Professor Dybjer has taught advanced courses at international summer schools, including: Inductive Definitions in Constructive Type Theory (TYPES Summer School, 2005) Dependent Types at Work (LerNet Summer School, Uruguay, 2008) Normalization by Evaluation (Midlands Graduate School, 2009 and 2015)

• Programming Languages
• Formal Semantics
• Theoretical Computer Science
• +۳ مورد دیگر

Benedict Bunting is a Doctoral Student in the Department of Computer Science at the University of Oxford, concurrently serving as a College Lecturer. He is affiliated with St John's College and Keble College. His research focuses on programming languages, formal semantics, and theoretical computer science, particularly in areas such as algorithmic game semantics and concurrency theory. Bunting's work explores foundational aspects of programming languages through operational and denotational approaches. Supervisor: Andrzej Murawski His research themes include state and control mechanisms in programming languages, nested data structures, and the application of game semantics to program equivalence. He has published at leading conferences such as the ACM/IEEE Symposium on Logic in Computer Science (LICS).

Kim Wernerمشاهده پروفایل

استاد

• Climate Change Adaptation
• Sustainability and Climate Protection
• Diversity
• +۵ مورد دیگر

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 Ludäscherمشاهده پروفایل

استاد

• Data and Knowledge Management
• Scientific Workflows
• Data Provenance
• +۴ مورد دیگر

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 Haigمشاهده پروفایل

دانشیار

• Intelligent Systems
• User Modelling and Personalisation
• Data Mining
• +۷ مورد دیگر

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 Quackenbushمشاهده پروفایل

استاد

• International Conflict
• Deterrence Theory
• Strategic Studies
• +۴ مورد دیگر

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
• +۵ مورد دیگر

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 Tadepalliمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Reinforcement Learning
• +۵ مورد دیگر

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 Huijunمشاهده پروفایل

استاد

• Networked Control Systems
• Signal Processing
• Image Processing
• +۷ مورد دیگر

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 Dimitrovaمشاهده پروفایل

استادیار

• Verification
• Reactive Systems Synthesis
• Control and Robotics
• +۳ مورد دیگر

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
• +۳ مورد دیگر

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 Hansenمشاهده پروفایل

دانشیار

• Formal Methods
• Embedded Systems
• Real-Time Systems
• +۳ مورد دیگر

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.