جستجوی استاد راهنمای دانشگاهی

Christian Webersikمشاهده پروفایل

استاد

• Crisis Management
• Climate Change and Security
• Natural Hazards
• +۳ مورد دیگر

Christian Webersik is a full Professor at the Department of Global Development and Planning, University of Agder, Norway, and Deputy Director of the Centre for Integrated Emergency Management (CIEM). His research focuses on crisis management, climate change security implications, disaster diplomacy, and technology applications in disasters. He holds a visiting scholar appointment at UC Berkeley and has held fellowships at institutions including UNU-IAS in Japan. Education & Positions: PhD (implied via academic career progression) Postdoctoral Fellowships at Columbia University (2005–2007) and United Nations University (2007–2009) Associate Professor at University of Agder (2009–2016) Research Interests: Crisis management frameworks and technology integration Climate-driven migration and conflict dynamics Disaster diplomacy in geopolitically tense regions Social media analysis for crisis response Recent work emphasizes misinformation mitigation on social media, systemic risks in food security, and Norway-Russia Arctic disaster cooperation. Key Contributions: Developed methodologies for disaster diplomacy analysis Advanced frameworks linking climate change to migration patterns Authored influential studies on Somalia's conflict-economy nexus Labs & Teams: Active in CIEM, collaborating with international researchers on crisis simulation and technology applications.

Andrea Pferscherمشاهده پروفایل

مدرس ارشد

• Digital Twins
• Formal Methods
• Computer Science
• +۳ مورد دیگر

Andrea Pferscher is a Senior Lecturer at the University of Oslo's Department of Informatics. Her research focuses on formal methods applied to digital twins, particularly in contexts like vaccination strategy modeling and environmental systems analysis. She is involved in projects such as DART (Digital Arctic Twins), a digital twin for vaccination strategies at geographic scales, and a digital twin of the Oslo Fjord. Her work bridges theoretical computer science with practical applications in system modeling and analysis. She collaborates on stochastic games, user journey strategies, and automated learning techniques for cyber-physical systems. Pferscher's research emphasizes interdisciplinary approaches, combining formal verification with machine learning and systems engineering.

• Formal Methods
• Automata Theory
• Temporal Logic
• +۵ مورد دیگر

Daniel Neider is a Professor at TU Dortmund University, Germany. He holds former affiliations with Carl von Ossietzky University Oldenburg and the Max Planck Institute for Software Systems (Kaiserslautern). His research focuses on formal methods, automata theory, temporal logic, and their applications in verification, AI, and machine learning. Neider earned his PhD in 2014 from RWTH Aachen University and a second PhD in 2022 from Kaiserslautern University. His work bridges theoretical foundations with practical tools, such as developing algorithms for automata learning, robust temporal logics (rLTL), and neuro-symbolic verification frameworks for deep neural networks. Key research areas include: (1) learning-based formal methods for system verification, (2) robust temporal logics for handling noisy environments, (3) reinforcement learning with temporal logic constraints, and (4) automated specification mining from data. He has contributed to tools like libALF (Automata Learning Framework) and Sorcar for property-driven invariant synthesis. His recent work explores: (a) scalable LTL learning from noisy data using MaxSAT, (b) neuro-symbolic verification techniques, and (c) applying large language models to automate reinforcement learning with reward machines. He has published over 135 papers in top venues like AAAI, TACAS, and FMCAD, focusing on formal methods intersections with AI and systems verification. Current projects involve: (i) robustness-aware synthesis for reactive systems, (ii) temporal logic inference from positive examples, and (iii) developing interpretable verification tools for complex operational domains. His lab collaborates on applying formal methods to real-world systems like smart contracts and neural networks.

Isaac Tamblynمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Nanoscience
• +۳ مورد دیگر

Isaac Tamblyn is an Assistant Professor of Physics at the University of Ottawa and an Affiliate Member of the Vector Institute of Artificial Intelligence. He also holds a position as an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. His research focuses on applying AI and deep learning to nanoscience problems, particularly materials and processes related to renewable energy. Tamblyn earned his PhD in Physics from Dalhousie University as a Killam Scholar, followed by postdoctoral studies at the Lawrence Livermore and Lawrence Berkeley National Laboratories. He has also held visiting roles at UC Berkeley and the Carnegie Institution of Washington. His academic journey includes a NSERC Postdoctoral Fellowship and prior work as a senior researcher at the National Research Council of Canada. His research interests span machine learning-driven materials discovery, computational physics, and reinforcement learning frameworks for chemistry and engineering. Tamblyn has pioneered tools like ChemGymRL and fintech-kMC, advancing AI applications in these fields. Key research trends in his publications emphasize machine learning for materials science, algorithmic development in chemistry, and optimization strategies in high-cost environments. His work bridges theoretical physics with practical AI solutions, addressing challenges in renewable energy systems and catalytic materials. Awards: Killam Scholar (2010), NSERC Postdoctoral Fellow Active in collaborative initiatives, Tamblyn leads research groups at both universities and contributes to interdisciplinary projects via Vector Institute affiliations. His lab focuses on leveraging AI to solve complex physical and materials science problems, with a strong emphasis on sustainability and energy innovation.

Loek G.W.A. Cleophasمشاهده پروفایل

استادیار

• Model-Driven Software Engineering
• Algorithm Engineering
• Pattern Matching
• +۵ مورد دیگر

Loek G.W.A. Cleophas is an Assistant Professor in Engineering of Software-Intensive Systems at Eindhoven University of Technology (TU/e), affiliated with the Mathematics and Computer Science department. He holds an Extraordinary Associate Professorship at Stellenbosch University and has held visiting roles at TU Braunschweig (2016-2017) and Umeå University (2014-2016). His academic career includes industry collaborations with ASML and Canon, and leadership as Managing Director of the Dutch research school for Programming and Algorithmics (IPrA). Education: Both his MSc (with honors) and PhD in Computer Science and Engineering were obtained at TU/e. His research focuses on model-driven software engineering (MDSE) and algorithm engineering, with emphasis on pattern matching using finite automata and parallel processing for large datasets. Recent work includes model repository analytics, digital twin systems, and variability analysis in software product lines. Research Trends: Over 129 publications span topics like SAMOS framework for model analytics, VPDSL domain-specific languages, and taxonomy-based algorithm toolkits. His work bridges theoretical foundations with industrial applications in high-tech systems. Advising: Supervised 27 postgraduate students at Stellenbosch and TU/e. Grants/Projects: Led collaborations with ASML on model-driven virtualization, and organized international workshops like AMMoRe (2018-2020). Labs/Tools: Developed SAMOS framework for model analytics and LaMa web application for thematic labeling. Active in open-source tool development for correctness-by-construction methodologies.

Wieger Wesselinkمشاهده پروفایل

استادیار

• Formal Verification
• Concurrent Systems
• Model Checking
• +۲ مورد دیگر

Wieger Wesselink is Assistant Professor in Formal System Analysis at Eindhoven University of Technology, where he specializes in formal verification and concurrent systems. He is a lead developer of the mCRL2 toolset for modeling and verifying concurrent protocols. His research focuses on symbolic model checking, parity games, and efficient algorithm implementation. Awards: Received FMICS-AVoCS Best Paper award in 2017. Teaching: Instructs courses on Foundations of Artificial Intelligence and Provable Programming.

Chrystopher Nehanivمشاهده پروفایل

استاد

• Algebra
• Transformation Semigroups
• Complex Adaptive Systems
• +۵ مورد دیگر

Chrystopher Nehaniv is a full-time Professor in the Department of Biomedical Engineering at the University of Waterloo, actively contributing to research groups including Intelligent and Autonomous Systems, Physical Systems and Mechatronics, and Human Factors and Interfaces. His work bridges mathematical theory with practical applications in robotics and complex systems, reflecting a strong interdisciplinary approach across engineering and cognitive sciences. His research spans algebraic structures in transformation semigroups, complex adaptive systems, and human-robot interaction. Key interests include cellular automata, autopoiesis, dynamical systems theory, and EEG microstate analysis, with significant theoretical contributions to semigroup complexity and practical implementations in domestic service robotics. Recent work emphasizes biologically inspired imitation learning, continual adaptation in human-robot teams, and mathematical modeling of social dynamics in games and neural systems. Analysis of his 15 most recent publications (2024-2025) reveals three dominant trajectories: (1) foundational algebraic work on transformation semigroups and finite groups applied to sandpile models, traffic systems, and game theory; (2) robotics innovations in social referencing, mental imagery, and continual learning for domestic service robots; and (3) neuroscience applications through EEG microstate syntax analysis and neural dynamics modeling. These threads consistently integrate rigorous mathematical frameworks with real-world complex systems challenges. No scientific awards or fellowships were mentioned in the provided materials. While specific student advisees and grant details were absent from the source text, his extensive publication record in human-robot interaction and complex systems suggests active supervision in interdisciplinary robotics projects. The absence of explicit grant mentions contrasts with his high-output research profile across multiple domains. Nehaniv operates within Waterloo's Intelligent and Autonomous Systems research ecosystem, collaborating across physical robotics (mechatronics, human factors) and theoretical frameworks (BIOMICS interaction computing). His work with the iCub robot platform and domestic service robot implementations indicates hands-on laboratory engagement, particularly in social interaction validation and object disambiguation systems.

• Mathematics Education
• Computational Thinking
• Formal Methods
• +۳ مورد دیگر

Mark Timmer is an Associate Professor at the University of Twente, affiliated with the ELAN Teacher Development department. He holds a PhD in Efficient Modelling, Generation and Analysis of Markov Automata (2013), an MSc in Science Education and Communication (2011), another MSc in Computer Science (2008), and a BSc in Telematics (2005), all from the University of Twente. His research spans computational thinking in mathematics education, formal methods in computer science, and curriculum development. He has received awards including the IPA Dissertation Award (2013) and Overijssel PhD Award (2014). His work emphasizes integrating computational thinking into secondary education, particularly through algorithmic concepts like Dijkstra’s algorithm and K-means clustering. He also explores formal verification techniques for probabilistic systems, contributing to the analysis of Markov automata. Timmer actively participates in international educational initiatives, such as the ICME-15 congress, and collaborates with educators to improve teaching methods. Publications highlight his dual focus on theoretical computer science (e.g., confluence reduction in Markov models) and practical educational applications (e.g., lesson study implementations). He has authored book reviews and contributed to educational journals, emphasizing pedagogical innovation and critical analysis of teaching materials.

• Formal Methods
• Safety-Critical Systems
• Probabilistic Verification
• +۴ مورد دیگر

Sebastian Junges is an Assistant Professor in the Software Science Group at Radboud University, Nijmegen, since 2021. He holds a PhD in Computer Science from RWTH Aachen University (2020), and previously worked as a PostDoc at UC Berkeley (2020-2021) and a Research Assistant at RWTH Aachen (2015-2020). His research focuses on formal methods for analyzing safety-critical systems, particularly using extensions of Markov decision processes (MDPs) to ensure dependability in automated systems like network protocols, hardware architectures, and robotics. Education: PhD in Computer Science, RWTH Aachen University, 2020 M.Sc. in Computer Science, RWTH Aachen University, 2015 B.Sc. in Computer Science, RWTH Aachen University, 2012 His research interests include probabilistic verification, policy synthesis for MDPs, and the intersection of formal methods with artificial intelligence. He has contributed to tools like the Storm probabilistic model checker and led projects on scalable analysis of probabilistic models. His work addresses challenges like ensuring safe decision-making in autonomous systems and certifying compliance with safety standards through rigorous algorithmic approaches. Publications focus on advancing MDP analysis, POMDPs, and robust policy synthesis. Recent trends include integrating uncertainty management, decision-tree-based approaches, and compositional verification techniques. He actively contributes to conferences like CAV, AAAI, and TACAS, and serves on program committees and steering groups for formal methods and AI.

• Sustainable Aviation
• Aerospace Computation
• Aircraft Design Optimization
• +۷ مورد دیگر

Dr. Rhea Liem is an Associate Professor in Sustainable Aviation at Imperial College London's Department of Aeronautics, affiliated with the Brahmal Vasudevan Institute for Sustainable Aviation. She holds a PhD from the University of Toronto and prior degrees from MIT and Nanyang Technological University. Her work emphasizes computational science integration into sustainable aviation, focusing on operation-aware aircraft design and air traffic optimization. Her research bridges computational methods with real-world applications, addressing systemic inefficiencies through data-driven frameworks. Education: PhD in Aerospace Engineering (University of Toronto, 2015) S.M. in Aeronautics and Astronautics (MIT, 2010) S.M. in Computation for Design and Optimization (MIT, 2007) B.Eng. in Mechatronics (Nanyang Technological University, 2003) Research Interests: Optimization of aircraft design across flight missions Data-infused physics-based models for fuel efficiency Integration of operational constraints into design frameworks Noise and fuel tradeoffs in trajectory optimization Her work on AirTrafficSim and AeroFuse platforms highlights contributions to education and industry. Awards include the Amelia Earhart Fellowship and Royal Aeronautical Society Fellowship. She has held roles at Hong Kong University of Science and Technology and industry positions in Singapore.

• Geospatial Information Systems
• 3D GIS
• BIM/GIS Integration
• +۷ مورد دیگر

Professor Sisi Zlatanova is a Professor at the University of New South Wales (UNSW), affiliated with the School of Arts, Design & Architecture. She holds a PhD in 3D GIS for Urban Development from Graz University of Technology and has held academic positions globally, including at ITC (Netherlands) and Delft University of Technology. Her research focuses on 3D spatial modeling, BIM/GIS integration, emergency response systems, and indoor navigation. Key projects include UNSW precinct modeling, indoor scanning for emergency response, and voxel-based visibility analysis for safety. Her research activities span over 300 publications and 23 edited books, with notable works on 3D GIS applications and disaster management. She leads international initiatives like ISPRS TC IV (Spatial Information Science) and OGC SWG IndoorGML. Her work emphasizes practical applications in urban resilience, sustainable design, and crisis management. Professor Zlatanova's contributions include developing frameworks for smart indoor models, integrating BIM with GIS for emergency response, and leveraging LiDAR and UAV technologies for urban analysis. She collaborates extensively with global organizations, advancing geospatial solutions for urban challenges.

• Computational Social Science
• Artificial Intelligence Ethics
• Political Science
• +۳ مورد دیگر

Cesare Carissimo is a Lecturer at the Department of Humanities, Social and Political Sciences at ETH Zürich, specializing in Computational Social Science. His work bridges computational methodologies with interdisciplinary social analysis, focusing on ethical implications of AI, algorithmic fairness, and sociotechnical systems. Research interests emphasize artificial intelligence ethics, computational models in societal contexts, and the intersection of robotics with emergent behaviors. His recent work explores topics such as algorithmic governance, reinforcement learning dynamics, and narrative-based AI failure analysis. Publications highlight interdisciplinary approaches to understanding how computational methods can address complex social challenges, including democracy design and robotic systems' autonomy. Email: cesare.carissimo@gess.ethz.ch

Olivier Del Fabbroمشاهده پروفایل

مدرس

• Philosophy of Science and Technology
• US-American Pragmatism
• Philosophy of Complex Systems
• +۳ مورد دیگر

Dr. Olivier Del Fabbro is a Lecturer at the Department of Humanities, Social and Political Sciences at ETH Zürich. His research focuses on French philosophy of science and technology, US-American pragmatism, and the philosophy of complex systems, AI, and cybernetics. He explores topics such as war philosophy, ethical dimensions of technology, and educational approaches in machine learning. In addition to academic writing, he contributes to public discourse through newspapers like Neue Zürcher Zeitung and Frankfurter Allgemeine Zeitung. His recent work includes articles analyzing perpetual warfare dynamics, trauma narratives, and the ethical implications of AI education. He collaborates on interdisciplinary projects, such as philosophy-guided mathematical models for complex systems and the philosophical underpinnings of surgical robotics. Del Fabbro’s publications span journals, conference papers, and monographs, addressing themes like Gilbert Simondon’s process ontology, adaptive systems, and the societal impact of technology. His work bridges philosophy with practical applications in science, medicine, and defense strategy.

Lulu Qianمشاهده پروفایل

استاد

• Biological Engineering
• Molecular Programming
• DNA Nanotechnology
• +۶ مورد دیگر

Lulu Qian is a Professor of Bioengineering at the California Institute of Technology (Caltech), leading the Qian Lab. She holds a B.E. from Southeast University (2002) and a Ph.D. from Shanghai Jiao Tong University (2007). Prior to her current role, she served as an Assistant Professor at Caltech (2013–2018). Her research focuses on designing molecular systems with programmable behaviors, including biochemical circuits, DNA neural networks, and molecular robots. These systems aim to mimic biological intelligence and perform tasks like pattern recognition, decision-making, and spatial organization at the molecular level. Her lab’s key projects include developing DNA strand displacement cascades for scalable computation, creating DNA-based neural networks capable of associative memory, and engineering molecular robots that perform collective tasks like cargo sorting. Notable achievements include the world’s smallest DNA-based Tic-Tac-Toe game, fractal assembly of DNA origami arrays, and a DNA robot capable of sorting molecules. Qian’s work bridges molecular engineering, computer science, and synthetic biology to advance nanotechnology and programmable matter. Her lab actively collaborates with Caltech’s graduate programs in Bioengineering, Computer Science, and Chemical Engineering. Current and past students have contributed to projects ranging from programmable DNA circuits to bio-inspired robotics. The lab emphasizes interdisciplinary training, preparing students for careers in academic research and industry innovation.

Erik Winfreeمشاهده پروفایل

استاد

• Biomolecular Computation
• DNA-Based Computation
• Algorithmic Self-Assembly
• +۵ مورد دیگر

Erik Winfree is a Professor of Computer Science, Computation and Neural Systems, and Bioengineering at the California Institute of Technology (Caltech), where he has held academic positions since 1999. He earned his B.S. from the University of Chicago (1991) and Ph.D. from Caltech (1998), followed by postdoctoral research at Princeton University and MIT. His research focuses on biomolecular computation, DNA nanotechnology, and molecular programming. Key areas include algorithmic self-assembly, DNA strand displacement circuits, molecular robotics, and the study of nucleic acid systems. He leads the Winfree Lab, exploring foundational questions in synthetic biology and molecular engineering. Winfree has received prestigious awards such as the MacArthur Fellowship (2000), Feynman Prize in Theory (2006), and AAAS Fellowship (2015). He teaches advanced courses on biomolecular computation and molecular programming, and his work bridges computer science, bioengineering, and theoretical biology. Administrative Role: Principal Investigator, Winfree Lab Professional Societies: ACM, AAAS, American Chemical Society Collaborations: Molecular Programming Project (2008–2019), international research networks His research lab actively develops tools for nucleic acid design and analysis, including sequence-level simulators and formal verification frameworks for molecular systems.