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Michael MonaganView profile

Professor

• Computer Algebra
• Symbolic Computation
• Polynomial Algebra
• +4 more

Michael Monagan is a Professor in the Department of Mathematics at Simon Fraser University (SFU), part of the Faculty of Science. He holds a Ph.D. from the University of Waterloo (1990) and is a leading researcher in Computer Algebra and Symbolic Computation. His work focuses on polynomial algebra, parallel algorithms, and the design of computer algebra systems, particularly Maple. Monagan has developed foundational algorithms for polynomial GCD, factorization, and sparse interpolation. Research interests include computational algebra, probabilistic algorithms, algebraic simplification, and high-performance computing. He leads SFU's Computational Algebra Group (CAG) and has collaborated on projects like NSERC grants for polynomial GCD and factorization algorithms. Monagan teaches courses in calculus, computer algebra, and algebraic geometry. Monagan has advised numerous graduate students and supervised undergraduate research in areas like Hensel lifting, sparse interpolation, and polynomial systems. He has authored over 100 articles, with recent work on black box GCD algorithms, transposed Vandermonde solvers, and parallel polynomial multiplication. His contributions to Maple and theoretical computer algebra have been internationally recognized. Key collaborations include the Magma Group (University of Sydney) and Maplesoft through NSERC grants. Monagan's work bridges theory and practice, emphasizing efficient algorithm design and implementation.

Ron WakefieldView profile

Professor

• Construction Information Technology
• Industrialization of Construction
• Simulation of Engineering Systems
• +9 more

Professor Ron Wakefield is the Dean of the School of Property, Construction and Project Management and Associate Deputy Vice Chancellor, International at RMIT University. He holds a Professorship in Construction and has held leadership roles globally, including at Virginia Polytechnic Institute and State University and UNSW Sydney. His research focuses on construction information technology, industrialization of construction, occupational health and safety, and renewable energy integration. He has received several awards, including Excellence in Scholarship (Virginia Tech, 2003) and the Certificate of Teaching Excellence (Virginia Tech, 2001). Wakefield's academic journey includes roles as Program Director for the Cooperative Research Centre’s Built Assets project and Director of Virginia Tech’s Environmental Design and Planning PhD program. His work spans industrialized building systems, safety training efficacy, and BIPV design optimization. He has supervised over 17 research projects, including studies on renewable energy adoption and blockchain in construction. Education: Graduate Research Assistant at Princeton University (1985–1987), prior to academic roles. Awards: Multiple recognitions for scholarship, teaching, and contributions to construction safety and innovation. Research Themes: BIPV systems, construction automation, and sustainable urban energy solutions. He collaborates internationally on projects like the CIB World Building Congress and advises on renewable energy transitions (e.g., Bendigo’s energy feasibility study). His recent publications address VR-based safety training, reinforcement learning for virtual power plants, and fire safety in BIPV systems.

Michael BurkeView profile

Part-Time Lecturer

• Program Analysis
• Static Analysis-based Tools
• Mobile Security
• +6 more

Michael Burke is a Senior Research Scientist and Part-Time Lecturer at Rice University's Computer Science Department. He holds a PhD from New York University (1983) and a BA from Yale University (1973). His research focuses on program analysis, static analysis tools, mobile security, parallel computing, and compiler optimization. Previously, he worked at IBM Research for over 25 years, contributing to projects like the PTRAN parallelization system, XJ XML programming language, and Jalapeno Java virtual machine. Dr. Burke has been recognized with numerous awards, including the ACM SIGPLAN Distinguished Service Award (2008), ACM Distinguished Scientist (2007), and IBM Research Division Technical Group Award (2005). He has authored over 60 technical papers and holds multiple patents related to compiler optimization and data analysis. His teaching includes courses on automata theory, compiler construction, and algorithmic thinking. Burke has advised on projects such as the Habanero Multicore Software Research Project and collaborated with organizations like Intel and Lawrence Livermore National Lab on parallel computing frameworks.

• Homotopy Type Theory
• Formal Verification
• Compositional Game Theory
• +4 more

Neil Ghani is a Professor in the Department of Computer and Information Sciences at the University of Strathclyde. His research focuses on foundational aspects of computer science including Homotopy Type Theory, formal verification, and compositional game theory. He has led major projects such as the Homotopy Type Theory: Programming and Verification initiative, which aims to bridge theoretical foundations with practical programming tools. Education details are not explicitly stated in the provided texts. His work emphasizes scalable formal verification systems, modular game theory frameworks, and categorical semantics. Recent research includes coalgebraic approaches to extensive form games and ordinal notation systems in cubical Agda. Notable Awards: Distinguished Presentation Award (2021), ETAPS 2016 EATCS Best Paper Award Collaborations: Active in interdisciplinary projects with co-investigators like Fredrik Nordvall Forsberg, Crawford Revie, and others Current Projects: Sea lice dispersal models (2024), Trusted Systems (2019-2024) Neil's contributions span academic leadership, doctoral training supervision, and industrial partnerships, reflecting a commitment to both theoretical innovation and practical software reliability.

• Control Engineering
• Hydrodynamics
• Marine Control Systems
• +3 more

Asgeir Johan Sørensen is a Professor at the Department of Marine Engineering, Faculty of Engineering at NTNU. He holds a Dr. Eng. in Technical Cybernetics (1993) and an M.Sc. in Marine Engineering (1988), both from NTH (now NTNU). His research focuses on control engineering, hydrodynamics, autonomous systems, and marine robotics. He leads projects like Oppdrag Mjøsa , advancing autonomous marine operations and environmental monitoring. Key contributions include risk-based path planning, hydrogen fuel cell systems for marine propulsion, and hyperspectral imaging for underwater mapping. Research interests emphasize autonomous systems integration, underwater vehicle control, and sustainable marine technologies. He co-founded the Marine Cybernetics Laboratory (MC-lab) and Applied Underwater Laboratory (AUR-Lab) . His work bridges academia and industry, addressing challenges in marine robotics, energy systems, and satellite-based Earth observation. Recent publications highlight advancements in marine autonomy, including collision avoidance algorithms, hybrid power systems, and Arctic satellite missions. He collaborates widely, contributing to national and international initiatives in marine technology and environmental data governance.

Edmond ChowView profile

Professor

• High-Performance Computing
• Scientific Computing
• Numerical Linear Algebra
• +7 more

Edmond Chow is a Professor and Associate Chair in the School of Computational Science and Engineering at Georgia Institute of Technology. His research focuses on numerical methods, high-performance computing, and scientific computing applications in quantum chemistry, molecular dynamics, and machine learning. He holds awards including the 2009 ACM Gordon Bell Prize and 2002 PECASE. He leads the Intel Parallel Computing Center, advancing computational chemistry algorithms for Intel architectures. Education: Ph.D., Computer Science (minor in Aerospace Engineering), University of Minnesota, 1997 Honors B.A.Sc., Systems Design Engineering, University of Waterloo, 1993 Research Interests: Parallel algorithms for sparse linear systems and preconditioning High-performance quantum chemistry simulations Asynchronous iterative methods for extreme-scale computing Kernel-based methods and hierarchical matrices for Gaussian processes Applications in biological macromolecule dynamics and machine learning Awards & Recognition: ACM Gordon Bell Prize (2009) PECASE (2002) SIAM Fellow (2021) SC23 Test of Time Award Advising & Grants: Advised 11+ PhD/MSc students in numerical methods and HPC Funded by NSF, DOE, DARPA, and Intel Developed software tools like H2Pack (hierarchical matrices), GTFock (quantum chemistry), and Simint (electron integrals) Labs & Teams: Leads the Intel Parallel Computing Center and collaborates with institutions like LLNL, Sandia, and Temple University on asynchronous computing and quantum chemistry projects.

Arthur P. GuillauminView profile

Lecturer

• Mathematical Data Science
• Spatial Statistics
• Environmental Data Analysis
• +4 more

Dr Arthur P. Guillaumin is a Lecturer in Mathematical Data Science at Queen Mary University of London (QMUL), affiliated with the School of Mathematical Sciences and the Centre for Probability, Statistics and Data Science. He holds a PhD from University College London (UCL) under Prof. Sofia Olhede and Dr. Adam Sykulski, followed by postdoctoral positions at UCL and New York University (with Prof. Laure Zanna). His research focuses on spatio-temporal data modeling, particularly in environmental sciences, using advanced statistical methods like quasi-likelihood estimation and probabilistic neural networks. He collaborates with the NASA-funded Northwest Research Associates on Sea Surface Height (SSH) analysis, aiming to improve climate change understanding through innovative covariance models. Education: PhD in Statistical Science, University College London (UCL) Masters in France (details unspecified) Research Interests: Development of parametric covariance models, quasi-likelihood estimation techniques, and applications to SSH analysis. He addresses challenges like heterogeneous spatial dependence and computational efficiency in environmental data. His work bridges statistical theory with practical environmental monitoring, impacting fields like oceanography and econometrics. Advising & Collaborations: Supervising a PhD project on SSH modeling with NW Research Associates. Collaboration with NASA-funded teams on SSH mapping software. Labs/Teams: Part of QMUL’s Centre for Probability, Statistics and Data Science, focusing on interdisciplinary data science applications.

• Computer Vision
• Scene Understanding
• Machine Learning
• +7 more

Kasim Terzić is a Lecturer in the School of Computer Science at the University of St Andrews, where he conducts research and teaches in computer vision, machine learning, and robotics. He is affiliated with the Centre for Research into Ecological & Environmental Modelling and the Coastal Resources Management Group, reflecting his interdisciplinary focus on technology for environmental conservation. Education: PhD in Computer Science, University of Hamburg MSc in Information and Communication Systems, Hamburg University of Technology MSc in Global Technology Management, Hamburg University of Technology BEng (Hons) in Electronic Engineering, University of East Anglia His research interests center on computer vision and machine learning with applications in ecological monitoring and robotics. He focuses on bridging low-level pixel data with high-level semantic understanding, active vision, and the perception-action loop, often implemented on robotic platforms. He also advocates for open-source software and open data to democratize access to technology. Recent publications highlight his work in robotic manipulation of deformable objects like cloth and applications of deep learning in biological monitoring, such as fish age estimation and seal counting. His research spans computer science, ecology, and conservation, demonstrating a strong interdisciplinary approach. Professional Activities: External Examiner at Robert Gordon University (2020–2024) Invited speaker on machine learning in conservation and automated seal counting Organizing committee member for EAI MobiHealth conference Participant in public outreach events like Doors Open @ Computer Science Kasim Terzić supervises postgraduate research students and contributes to teaching in core and specialized computer science modules, including Computer Graphics, Machine Learning, programming, Operating Systems, and Databases. He is actively engaged in research output, dataset creation (e.g., Arctic charr re-identification), and promoting sustainable technology through open-source initiatives.

Martin DillerView profile

Researcher

• Formal Argumentation
• AI Systems
• Probabilistic Argumentation
• +3 more

Martin Diller is a Researcher at the International Center for Computational Logic (ICCL) at TU Dresden, where he has been since May 2019. He is part of the 'Logic Programming and Argumentation' group led by Sarah Gaggl. His current research focuses on formal models of argumentation and their application in AI systems, particularly within the SEMECO interdisciplinary cluster on AI-assisted regulatory workflows for medical systems and cybersecurity. Education: Holds a joint MSc in Computational Logic from TU Wien, TU Dresden, and University of Bolzano (via the EMCL program with an Erasmus Mundus scholarship). Previously completed a MA in Philosophy (Logic & Epistemology) and BSc in Computer Science at Universidad Nacional de Córdoba, Argentina, with postgraduate funding from CONICET. Also conducted research internships at University of Aberdeen, UCL, NICTA (Canberra), and others. Key Projects: Active in the Transregional Collaborative Research Center ‘Foundations of Perspicuous Software Systems’ (2019–2022), and the Center for Scalable Data Analytics and Artificial Intelligence (2023). Currently leads research in probabilistic argumentation and flexible dispute derivations for assumption-based arguments. Key Contributions: Developed the 'flexABle' system for argumentation framework analysis, contributed to admissibility criteria in probabilistic argumentation, and advanced methods for integrating natural language processing with formal argumentation systems. Grants & Funding: Involved in EU-funded interdisciplinary projects and German collaborative research initiatives. Labs/Teams: Core member of the Logic Programming and Argumentation group at ICCL, collaborating with institutions worldwide.

• Biomedical Signal Processing
• Embedded Systems
• FPGA Hardware Implementation
• +7 more

Jose Vicente Frances Villora is an Associate Professor in the Department of Electronic Engineering at the School of Engineering, University of Valencia, Spain. He is an active researcher in digital systems and biomedical signal processing, with a strong focus on real-time embedded systems and hardware acceleration. His research interests include: Biomedical Signal Processing, particularly ECG and microelectrode recordings FPGA-based hardware implementation of neural networks and real-time algorithms Machine learning applications in healthcare, including arrhythmia detection and Parkinson’s disease treatment Neuromorphic computing and spiking neural networks Digital signal processing in embedded and real-time systems The analysis of his recent publications (2017–2015) reveals a consistent focus on leveraging machine learning—especially KNN and neural networks—for clinical applications such as ventricular fibrillation detection and deep brain stimulation. A significant portion of his work emphasizes hardware implementation on FPGAs, aiming to achieve real-time performance and low resource consumption in medical and robotic systems. He has contributed to educational materials, including textbooks and OCW resources, and supervises academic theses. While no specific scientific awards are mentioned in the provided text, his sustained publication output and integration of theory with hardware systems underscore his technical expertise. He advises students in thesis work and has supervised doctoral research, though specific student names are not listed. His research is supported by practical applications in medical diagnostics and robotics, and he is affiliated with the GPDD (Group for Digital Design and Processing), which focuses on digital system design and processing. He is actively involved in laboratory development, including a remote laboratory for industrial robots, and his team works on co-design environments for neural network hardware, FPGA acceleration, and real-time biomedical systems.

Kam Pui ChowView profile

Associate Professor

• Computer Forensics
• Digital Investigation
• Data Privacy
• +4 more

Dr. Kam Pui Chow is an Associate Professor and Associate Director of the Center for Information Security and Cryptography (CISC) at the University of Hong Kong's Department of Computer Science and Information Systems. He holds an MA and PhD from the University of California, Santa Barbara. His academic career began post-doctorate with contributions to establishing HARNET, Hong Kong's first academic research network. His research spans expert systems, Chinese computing, and later shifted to computer forensics, digital investigations, and cybersecurity. He leads the Computer Forensics Research Group (CFRG) and designed tools like the bilingual Digital Evidence Search Kit (DESK) and Lineament systems for piracy monitoring. Dr. Chow has been involved in over 30 publications, including best paper awards in 2008/2011, and serves on committees for digital forensics conferences and societies. Education: MA and PhD from UC Santa Barbara. Research Interests: Digital forensics, computer security, cryptography, and data privacy. His work includes forensic tool development, Bayesian models for evidence analysis, and live system forensics. He contributed to Hong Kong's Customs systems and provided expert testimony in legal cases involving digital evidence. Professional Roles: Associate Programme Director for the MSc in E-Commerce and Internet Computing, instructor for courses on e-Crime and digital forensics, and chairman of the Information Security and Forensics Society (Hong Kong). He has advised law enforcement and provided consultancy on distributed computing and software quality assurance. Awards: Notable recognition includes best paper awards for research on forensic reasoning and privacy-preserving investigations.

• Formal Methods in Computer Science
• Cybersecurity
• Insider Threat Analysis
• +4 more

Dr. Florian Kammueller is an Associate Professor in Software Engineering at Middlesex University , specializing in formal methods for cybersecurity and privacy. His research focuses on attack trees , GDPR compliance , insider threat modeling , and quantum cryptography using the Isabelle theorem prover. He has published extensively on formal verification of security protocols, privacy in IoT healthcare systems, and trust in AI. Recent publications emphasize federated learning , differential privacy , and distributed ledger security , often applying formal verification techniques to address regulatory and technical challenges. His work bridges theoretical computer science with practical applications in critical infrastructure security.

Fabio Massimo ZennaroView profile

Associate Professor

• Machine Learning
• Causal Abstraction
• Structural Causal Models
• +9 more

Fabio Massimo Zennaro is an Associate Professor in Machine Learning at the Department of Informatics, University of Bergen, and holds an honorary position at the University of Warwick. His research centers on causal abstraction, structural causal models, and the systematization of machine learning, with applications in reinforcement learning, computer security, and societal AI. His educational background includes a PhD from the University of Manchester, postdoctoral work at the University of Oslo and University of Warwick, and MSc degrees from the University of Oxford and Politecnico di Milano. His research interests span causal machine learning , fairness , uncertainty modeling , reinforcement learning , and AI ethics . He explores how causal models at different levels of abstraction can be related and exploited in real-world systems. The recent publications (2023–2025) demonstrate a strong focus on causal abstraction , interventional consistency , and surrogate modeling , published in top venues like NeurIPS, UAI, and CLeaR. His work combines theoretical rigor with practical applications in cybersecurity and decision systems. Scientific awards include: Best paper at UAI 2022 Workshop on Causal Representation Learning Turing Post-doctoral Award (PDEA), 2022 Kilburn Scholarship (2013–2016) Isabella Sassi-Bonadonna Scholarship (2012) Vulcanus Scholarship (2009) He advises students and collaborates on interdisciplinary research, though no formal list of advisees is provided. He has secured postdoctoral funding and contributes to the academic community through program committees (UAI, NeurIPS, ICLR, IJCAI) and journal reviewing (JMLR, Neural Networks, Computers & Security). He is involved in organizing the Causal Abstractions and Representations Workshop at UAI 2025. His research is conducted within the Machine Learning Group at the University of Bergen, focusing on foundational and applied aspects of AI with societal impact.

Mingshuai ChenView profile

Assistant Professor

• Formal Verification
• Programming Theory
• Logical Aspects of Computer Science
• +5 more

Mingshuai Chen is an Assistant Professor at Zhejiang University, leading the Formal Verification Group. He previously held a postdoctoral position at RWTH Aachen University. Education: Ph.D. in Computer Science from Institute of Software, Chinese Academy of Sciences (2019) B.Sc. in Computer Science from Jilin University (2013) His research focuses on formal verification, synthesis, programming theory, and probabilistic/quantum systems. Notable contributions include Exact Bayesian Inference and Lower Bounds for Probabilistic Programs . Scientific awards include: NSFC Excellent Young Scientists Fund Program (Overseas) Distinguished Paper Award at ATVA 2018 Best Paper Award at FMAC 2019 CAS-President Special Award (2019) 2nd Prize@ChinaSoft'24 He serves on program committees for OOPSLA 2026, TACAS 2026, and multiple other conferences.

Einar Broch JohnsenView profile

Professor

• Programming Models
• Formal Methods
• Concurrency
• +3 more

Einar Broch Johnsen is a Professor at the Department of Informatics , University of Oslo . His research focuses on formal methods , distributed systems , and digital twins , with applications in cloud computing , robotics , and healthcare . Leadership: Strategy Director of SIRIUS (2015-2023), Coordinator of EU projects Envisage and HyVar . Community Roles: Board member of Formal Methods Europe , editorial board member of Formal Aspects of Computing , and chair of conferences like FM 2015 and FASE 2022 . His recent work explores symbolic execution , probabilistic logic , and self-adaptive systems , as reflected in his 15 most recent publications . He teaches courses such as IN2031 – Project in Programming and IN5170: Models of Concurrency .