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Carlos Esteve YagüeView profile

Researcher

• Nonlinear Parabolic PDEs
• Optimal Control Theory
• Hamilton-Jacobi Equations
• +3 more

Carlos Esteve Yagüe is an Associated Researcher at the ERC Advanced Grant project DyCon under the Deusto Chair of Computational Mathematics, supervised by Prof. Enrique Zuazua. His research focuses on nonlinear parabolic PDEs, optimal control theory, Hamilton-Jacobi equations, and differential games applied to degenerate elliptic equations. Education: PhD in Applied Mathematics (2015-2019), Université Paris 13, France MSc in Fundamental Mathematics (2014-2015), Université Paris 13, France BSc in Mathematics (2010-2014), Universidad de Alicante, Spain Research Interests: Carlos investigates singularity formation in nonlinear parabolic equations, optimal control strategies for complex systems, and applications of Hamilton-Jacobi equations to degenerate elliptic problems. His work bridges theoretical analysis with numerical methods and practical control applications. Key Contributions: His publications explore reachable sets for Hamilton-Jacobi equations, multilevel harmonic modulation via optimal control, and the turnpike phenomenon in nonlinear systems. Recent work includes studies on differentiability properties of PDE solutions and inverse problems in Hamilton-Jacobi frameworks. Awards & Grants: Funded by the ERC Advanced Grant DyCon, his research is supported through collaborative projects with institutions like FAU and Universidad Autónoma de Madrid. Presentations: Carlos has presented on topics such as reversibility properties of Hamilton-Jacobi equations and touchdown localization in MEMS problems at conferences and universities including the University of Alicante and Universidad de Buenos Aires.

• Stochastic Optimal Control
• Hamilton-Jacobi-Bellman Equations
• Numerical Methods for Partial Differential Equations
• +4 more

Athena Picarelli is a Full Professor at the Department of Economics at the University of Verona. She holds a PhD in Applied Mathematics from ENSTA ParisTech (2018) and completed postdoctoral fellowships at the University of Oxford (Nomura Fellowship) and Imperial College London (CFM Fellowship). Her research focuses on stochastic optimal control, Hamilton-Jacobi-Bellman equations, numerical methods for PDEs, and computational finance. She teaches courses on quantitative methods for business and economics at the undergraduate and graduate levels, as well as specialized modules on stochastic optimization and control in PhD programs. She serves on multiple institutional committees, including the PhD School Board and the QA Board of the PhD in Economics and Finance. Her academic leadership roles include coordinating the Collegio didattico for Economics and Finance programs. She is affiliated with research centers like CRIEP and CIDE, and her work includes contributions to the Verona Experimental Lab in Economics (VELE). Her research interests span control theory, numerical analysis, and financial applications of stochastic control, with a focus on robust optimization and computational methods. Her teaching responsibilities include modules such as 'Mathematics' for the Bachelor's in Economics and Business and 'Quantitative Methods for Business and Economics' for Master’s programs. She has been actively involved in academic governance, including membership in the Economics Department Council and the Research Advisory Board (RAB). Her institutional duties emphasize quality assurance and academic program development.

• Linear Algebra
• Matrix Analysis
• Nonnegative Matrices
• +7 more

Michael J. Tsatsomeros is a Professor in the Department of Mathematics & Statistics at Washington State University (WSU), affiliated with the College of Arts and Sciences. His academic journey includes positions at the University of Regina (Canada), University of Wisconsin, and the Indian Institute of Technology-Madras. He holds a Ph.D. from the University of Connecticut (1990), an M.Sc. from Concordia University (1986), and a Diploma in Mathematics from the University of Patras, Greece (1984). His research focuses on Linear Algebra and Matrix Analysis , with emphasis on nonnegative matrices, numerical range, and applications in dynamical systems, control theory, and AI. He has supervised numerous Ph.D. and Master’s students, including notable advisees such as Samir Mondal, Hung Le, and Pietro Paparella. His work has been recognized with awards like the 2024 Tom & Julie Lutz Teaching Excellence Award and the 2021 Excellence in Advising Award. Key publications include studies on P-matrices, Cayley transforms, and semimonotone matrices, often appearing in Linear Algebra and its Applications and Electronic Journal of Linear Algebra . He co-authored textbooks like Matrix Positivity (2020) and Linear Algebra and Matrix Methods (2024). Tsatsomeros serves as an Advisory Editor for Electronic Journal of Linear Algebra and Associate Editor for Linear Algebra and its Applications . His grants include the SPARC Collaboration Grant (2019–2021) and NSERC research funding. Beyond academia, his postdoctoral mentorship includes Fei Zhou and Panos Psarrakos, who now hold academic and industry roles. His research bridges theoretical matrix analysis with applied problems in engineering and computer science.

• Programming Languages
• Information Security
• Software Security
• +12 more

Dr Yi Lu is a Senior Lecturer at the Queensland University of Technology (QUT), Faculty of Science, School of Computer Science. He serves as Deputy Academic Lead (HDR) for the School of Computer Science, contributing to higher degree research leadership. His academic journey includes a PhD in Computer Science from the University of New South Wales (2008) and prior roles as a Lecturer at UNSW (2007–2013) and Principal Researcher at Oracle Labs (2013–2019). PhD in Computer Science, University of New South Wales, 2008 Bachelor of Information Technology (Honours), Queensland University of Technology, 2002 Dr Lu's research lies at the intersection of programming languages and information security, with a focus on theoretical and practical aspects of software security. His work includes type systems for object synchronization, ownership types, information flow control, and the application of deep learning to vulnerability detection. He has made significant contributions to static analysis, points-to analysis, and secure multithreaded programming. His recent publications span topics such as threat hunting in industrial control systems, nontransitive security types, and multi-class vulnerability prediction using graph neural networks. These works reflect a strong trend toward combining formal methods with machine learning to enhance software security, particularly in complex and critical systems. Dr Lu has been involved in significant research initiatives, including the Cyber Security Cooperative Research Centre and the ARC Linkage Project on Java language-based security conformance. His industry experience at Oracle Labs led to patented solutions for real-world cybersecurity problems, demonstrating the practical impact of his research. He supervises research projects on fine-grained vulnerability detection, reproducible deep learning workflows, and open-source supply chain analysis. His teaching includes courses such as Principles of Software Security and Object-Oriented Design, aligning closely with his research expertise. Dr Lu is affiliated with the School of Computer Science at QUT, a research-active unit within the Faculty of Science, contributing to cybersecurity education and innovation in Australia.

Melina FreitagView profile

Professor

• Numerical Linear Algebra
• Data Assimilation
• Inverse Problems
• +6 more

Melina Freitag is Professor for Data Assimilation at the Institute for Mathematics, University of Potsdam. Her research spans numerical linear algebra, inverse problems, and model order reduction, with applications in geophysics, image processing, and machine learning. She leads the Data Assimilation Group and contributes to the SFB 1294 Collaborative Research Center. Education : Prof. Freitag earned her Diplom in Mathematics at TU Chemnitz (2004) and PhD in Mathematical Sciences from University of Bath (2007). Research Themes : Her work focuses on Krylov subspace methods, low-rank approximations, and preconditioning for large-scale systems. She bridges classical numerical analysis with modern data assimilation, addressing challenges in: Bayesian inverse problems with unstable systems Optimized spectral sampling in X-ray imaging Physics-informed neural networks for Navier-Stokes inversion Parameter-dependent eigenvalue analysis Collaborations & Grants : She collaborates with institutions like KTH Stockholm and Arizona State University. Her group secures funding through SFB 1294 and participates in INI Cambridge networks. Leadership : Co-Chair of GAMM Activity Group on Applied Numerical Linear Algebra SIAM Activity Group on Linear Algebra Chair (2022) Teaching : Delivers courses on numerical optimization, matrix methods in data science, and inverse problems, integrating computational theory with real-world applications.

• Theoretical Computer Science
• Computability Theory
• Algorithmic Learning Theory
• +7 more

Pavel Semukhin is a Lecturer in the Department of Computer Science at Liverpool John Moores University, where he contributes to research and teaching in theoretical computer science and mathematical logic. His research interests include: Reachability problems in linear dynamical systems Finite and probabilistic automata Algorithmic learning theory Computability theory Computable model theory Matrix semigroups and decidability His recent work focuses on decidability and reachability in low-dimensional matrix semigroups, probabilistic automata, and logical structures, with publications in top venues such as CONCUR, MFCS, ICALP, and SODA. His research often bridges theoretical computer science and mathematical logic, especially in the context of automata, algebra, and learning models. His collaborative work with researchers like Igor Potapov, Sanjay Jain, and others has led to significant results in matrix problems and algorithmic learning. Though no formal list of students is provided, his publications suggest mentorship and collaboration with early-career researchers. He has also contributed to editorial work, including a special issue for International Journal of Foundations of Computer Science (2018) related to DLT 2015.

Petr JancarView profile

Professor

• Theoretical Computer Science
• Language and Automata Theory
• Computability and Complexity Theory
• +4 more

Petr Jancar is a Professor at the Department of Informatics, Faculty of Science, Palacký University in Olomouc. He has previously held academic positions at VŠB-Technical University of Ostrava and the University of Ostrava. His research is centered in theoretical computer science, with deep contributions to automata theory, Petri nets, system verification, and computational complexity. Education RNDr, Theoretical Cybernetics and Mathematical Informatics, Faculty of Mathematics and Physics, Charles University, Prague (1982) CSc. (PhD equivalent), Dissertation: "Questions of Decidability of Dynamic Properties of Petri Nets", Charles University (1989) Appointed Associate Professor in Informatics, Faculty of Informatics, Masaryk University (1996) Appointed Professor in Informatics, VŠB-TU Ostrava (2008) His primary research interests include theoretical computer science , focusing on language and automata theory, computability and complexity, algorithm theory, and mathematical logic. A significant portion of his work addresses system verification , particularly using Petri nets and infinite-state systems. He investigates fundamental questions of bisimilarity, equivalence checking, decidability, and complexity in models like pushdown and one-counter automata. Jancar's recent publications (2020–2025) show a strong trend in advancing the theory of Petri nets, especially structural liveness, reachability, and home-space problems, often establishing high complexity bounds (e.g., Ackermann-complete). His work combines deep theoretical insight with formal rigor, frequently published in top venues like LICS, CONCUR, and LogMethCS. He has long-standing collaborations with researchers such as Jérôme Leroux, Zdeněk Sawa, and Antonín Kučera. Scientific Service and Recognition Member, Editorial Board, Information and Computation (since 2015) Member, Scientific Councils at Masaryk University, VŠB-TU Ostrava, Palacký University, and Brno University of Technology Chairman, GAČR Panel P202 Informatics (2015–2017) Member, Program Committees of major international conferences He has been a co-investigator and researcher on multiple GAČR projects, including those on algorithms for infinite-state systems, computational complexity of verification, and modeling of parallel systems. He has also participated in the Center for Applied Cybernetics. He has held research stays supported by grants in Germany, France, Sweden, and the UK. Laboratories and Research Groups His work is closely associated with formal methods and verification research groups at Palacký University and former affiliations. He has contributed to collaborative projects involving MPI verification and infinite-state system analysis.

• Control Engineering
• Nonlinear dynamical systems
• Control of Unmanned vehicles
• +3 more

Soumya Ranjan Sahoo is an Associate Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur. His academic career at IIT Kanpur began with a contract position as Assistant Professor in 2014, progressing to Assistant Professor in 2016, and currently holding the position of Associate Professor since December 2020. Prior to joining IIT Kanpur, he worked as a Scientist Fellow at the National Aerospace Laboratories in Bangalore. PhD in Systems and Control Engineering from IIT Bombay (2013) Thesis Title: Coordination problems with minimal sensing and coarse actuation Thesis Supervisors: Prof. Ravi N. Banavar and Dr. Arpita Sinha B.Tech in Electrical Engineering from University College of Engineering, Burla, Odisha (2008) Dr. Sahoo's research spans the complex intersection of control theory and practical engineering applications. His work primarily focuses on nonlinear dynamical systems, with significant contributions to the control of unmanned vehicles and coordinated control systems. His research has evolved to address modern power system challenges, particularly in the domain of AC and DC microgrids, where he has developed innovative control strategies for improved performance. His work on discontinuous systems demonstrates his ability to tackle mathematically challenging control problems with practical implications. Analysis of Dr. Sahoo's publication record reveals a clear evolution from fundamental control theory to applied research with significant practical impact. His early work focused on theoretical aspects of multi-agent systems and network control, which has progressively shifted toward power systems applications, particularly microgrids. The consistent theme across his publications is the development of robust control strategies that work effectively under realistic constraints such as communication delays, incomplete information, and system heterogeneity. His research bridges theoretical control concepts with practical engineering implementations, particularly in the domains of autonomous systems and modern power grids. Dr. Sahoo teaches several key courses in the Electrical Engineering curriculum including Introduction to Electrical Engineering, Control Systems Analysis, Basics of Modern Control Systems, Nonlinear Systems, Adaptive Control Theory, and advanced topics in Nonlinear Systems. His teaching portfolio reflects his deep expertise in control theory and its applications. His laboratory work, particularly through the DiSCo Lab (as referenced in his homepage), focuses on practical implementations of control algorithms for various applications including unmanned vehicle coordination and microgrid management. This laboratory work bridges the gap between theoretical control design and real-world implementation challenges.

Igor PotapovView profile

Professor

• Theoretical Computer Science
• Algorithmic Complexity
• Matrix Semigroups
• +6 more

Igor Potapov is a Professor at the University of Liverpool , leading the Algorithms, Complexity Theory and Optimisation (ACTO) Group within the Department of Computer Science. His career includes progressive academic roles from Lecturer (2002) to Professor (current), with a focus on theoretical computer science and formal verification. Research Themes : Reachability problems in matrix semigroups, robot scheduling, broadcasting automata, and computational complexity. Grants & Awards : EPSRC grant (£459K, 2014-2018) on reachability problems NATO Collaborative Linkage Grant (€15,000, 2008-2010) Royal Society International Joint Projects and Travel Grants Nuffield Foundation Grant (£5,000, 2003-2005) Royal Academy of Engineering Fellowship (£3,940, 2008-2009) Recent Work Trends : Focus on geometric coverage algorithms (2025) Collision-free scheduling for robotic systems (2024-2025) Advances in matrix semigroup decidability (2024) Applications to programmable matter and crystal structure prediction (2022-2023) Contact : potapov@liverpool.ac.uk

Paul C. BellView profile

Senior Lecturer

• Theoretical Computer Science
• Computability Theory
• Automata Theory
• +22 more

Dr Paul C. Bell is a Reader in Computability and Automata Theory at the School of Computer Science and Mathematics, Liverpool John Moores University, UK. He has held academic positions at Keele University (Reader), Loughborough University (Lecturer), and the University of Liverpool (University Teacher). He completed his PhD at the University of Liverpool in 2007 and held postdoctoral positions at Université catholique de Louvain (Belgium) and the University of Turku (Finland). Current Affiliation: Liverpool John Moores University, School of Computer Science and Mathematics Previous Positions: Keele University (Reader), Loughborough University (Lecturer), University of Liverpool (University Teacher) Postdoctoral Experience: UCLouvain (Belgium), University of Turku (Finland) PhD: University of Liverpool, 2007 Paul C. Bell's research lies at the intersection of theoretical computer science and mathematics. His work focuses on foundational problems in computability, automata, and formal systems. Key areas include reachability in dynamical and hybrid systems, matrix semigroups, linear recurrence sequences, and algorithmic verification. He also explores quantum and probabilistic automata, Markov chains, Petri nets, and complexity in algebraic and logical systems. Additional interests span online algorithms, GPU computing, energy-aware scheduling, and computational geometry. His research is supported by grants from the Royal Society and London Mathematical Society, and he has received an NVIDIA hardware grant. He is an active supervisor, having guided four PhD students to completion and currently mentoring two more. He serves on the editorial board of The Computer Journal and is involved in numerous programme committees, including STACS and ICTCS-FAW. Royal Society International Exchange Grant Two London Mathematical Society travel grants NVIDIA hardware grant (2015) Dr Bell has supervised four PhD students to completion and is currently supervising two PhD candidates in Theoretical Computer Science and Pure Mathematics. He has served as an external examiner for MEng programmes at the University of Liverpool and for PhD theses at Loughborough, Liverpool, and Turku universities. He has received research grants and collaborates internationally, particularly with institutions in Belgium and Germany. He has organized major conferences such as RP 2021 and BCTCS 2014. Dr Bell has been involved in organizing significant academic events, including serving as co-chair of the 15th International Conference on Reachability Problems (RP 2021) in Liverpool, co-chair of BCTCS 2014, and organizer of a special session on Reachability Problems at Computability in Europe 2022. He has also served on multiple programme committees and as an organizing chair for ICIDM 2018 at LJMU.

Liliana PasqualeView profile

Associate Professor

• Cybersecurity
• Requirements Engineering
• Adaptive Systems
• +4 more

Liliana Pasquale is an Associate Professor at the School of Computer Science, University College Dublin (UCD), and a funded investigator at Lero – the SFI Research Centre for Software. She holds a PhD in Information and Communication Technology from Politecnico di Milano (2011) and has conducted research at IBM TJ Watson Research Center (2008). Her research focuses on requirements engineering, adaptive security, forensic readiness, and GDPR compliance in cyber-physical systems, with applications in transportation networks, industrial control systems, and smart spaces. **Education**: PhD in Information and Communication Technology (Politecnico di Milano, 2011); Professional Certificates in University Teaching & Learning (UCD). **Research Interests**: She investigates adaptive security mechanisms, forensic readiness for software systems, and runtime models for complex systems. Key areas include vulnerability assessment of transportation networks, stealthy attack detection in industrial systems, and human-centric cybersecurity for smart homes. **Grants & Awards**: Recipient of the Lero Research Award (2024), Runner-Up for IEEE Best Paper Award (2023), and numerous best reviewer recognitions. Active in grant initiatives such as the €1.2M 'Towards Forensic-Ready Software Systems' (2018–2019). **Teaching**: Coordinates UCD's MSc in Cybersecurity, including modules like 'Secure Software Engineering' and 'Leadership in Security'. Develops blended learning strategies for professional learners. **Professional Activities**: Serves on program committees for ICSE, SEAMS, and FSE. Co-chaired the Student Volunteer Committee for ESEC/FSE 2024 and participates in industry collaborations through UCD’s IT Strategy Group. **Lab/Teams**: Leads the SPARE research group, focusing on secure software engineering and adaptive systems. Collaborates with Lero and industry partners on cybersecurity challenges.

• Design and analysis of algorithms
• Graph algorithms
• Combinatorial optimization
• +3 more

Loukas Georgiadis is a Professor at the Department of Computer Science & Engineering, University of Ioannina, Greece. He has held previous academic positions including Assistant Professor at the University of Western Macedonia (2008-2011) and visiting roles at LUISS, Italy (2023-2024) and Università di Roma Tor Vergata (2016). His research focuses on design and analysis of algorithms , graph algorithms , combinatorial optimization , and computational geometry . Education includes a B.Sc. from the University of Patras (1999), M.A. and Ph.D. in Computer Science from Princeton University (2002, 2005). Professional experience includes roles at HP Laboratories (2007-2008) and the University of Aarhus (2005-2006). His recent work emphasizes faster algorithms for graph connectivity , fault-tolerant systems , and experimental algorithm analysis . He co-organized the 14th International Conference on Algorithms and Complexity (CIAC 2025) in Rome. Research trends include advancing linear-time algorithms for graph decomposition and exploring dynamic graph properties like dominators and low-high orders. Grants and advising details are not explicitly stated, but his visiting professorships and conference organizing roles highlight active collaborations. His research lab focuses on theoretical and applied aspects of algorithm design, with contributions to both foundational theory and practical implementations.

Edward F SchmeichelView profile

Professor

• Graph Theory
• Complexity of Algorithms
• Computational Mathematics
• +3 more

Edward F. Schmeichel is a Professor in the Mathematics Department at San José State University. His research focuses on Graph Theory and Complexity of Algorithms, with a strong emphasis on algorithm design, network optimization, and computational complexity. He holds a Ph.D. from Northwestern University (1974), an M.A. from Northwestern (1968), and a B.A. from Grinnell College (1967). His work spans theoretical and applied mathematics, including topics like NP-hard problem analysis, graph orientation, and time-varying network optimization. Notable contributions include studies on dominating cycles, star arboricity, and approximation algorithms for facility allocation. His publications reflect interdisciplinary approaches to discrete mathematics and computational challenges. Dr. Schmeichel’s articles explore themes such as polynomial algorithms for NP-hard hypotheses, Voronoi partitions in network location theory, and the Jeep problem’s optimization. His research bridges pure mathematics with practical applications in operations research and distributed systems. He currently serves at SJSU with office hours on TTH 10:00-10:30, 1:30-2:00, and 5:00-5:30. No scientific awards are explicitly listed in the provided materials.

Edon KelmendiView profile

Lecturer

• Algorithmic Verification
• Dynamical Systems
• Logics in Computer Science
• +3 more

Dr. Edon Kelmendi is a Lecturer in Computer Science at Queen Mary University of London, affiliated with the School of Electronic Engineering and Computer Science and the Centre for Fundamental Computer Science. His research focuses on algorithmic verification, dynamical systems, logics in computer science, game theory, and automata theory. He holds a position combining teaching and research responsibilities (T&R). His research interests revolve around theoretical computer science, particularly in the algorithmic analysis of dynamical systems, decision procedures for ω-regular properties, and stochastic games. He explores topics such as linear recurrence sequences, reachability problems in hybrid systems, and submixing properties in stochastic environments. Dr. Kelmendi’s recent work includes advancements in decidability questions for discrete and continuous linear dynamical systems, the design of learning algorithms for stochastic games, and formal verification techniques for automata and logical systems. His publications span venues like the ACM/IEEE Symposium on Logic in Computer Science (LICS) and the International Journal of Game Theory. He is actively involved in the Centre for Fundamental Computer Science, contributing to research themes such as formal methods, theoretical computer science, and algorithmic foundations. No specific grants or advising roles are explicitly listed in the provided materials.

Mateus De Oliveira OliveiraView profile

Associate Professor

• Theoretical Computer Science
• Automated Theorem Proving
• Parameterized Complexity
• +3 more

Mateus De Oliveira Oliveira is an Associate Professor in the Department of Informatics at the University of Bergen. His research focuses on theoretical computer science, automated theorem proving, parameterized complexity, formal verification, graph theory, and computational logic. His work spans algorithm design for constraint satisfaction problems, automated reasoning systems, and formal verification techniques. Notable contributions include advancements in width-based automated theorem proving, Petri net synthesis, and parameterized complexity analysis for graph algorithms. He leads the Autoproving project funded by the Research Council of Norway, exploring automated theorem proving through parameterized complexity theory. Recent publications highlight developments in symbolic functional decomposition, state canonization for theorem proving, and optimal dynamic programming algorithms. His research bridges foundational theory with practical applications in automated systems and formal methods.