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Bogdan ChlebusView profile

Professor

• Distributed Computing
• Algorithms
• Wireless Networks
• +3 more

Bogdan Chlebus is a Professor of Computer Science at Georgia Southern University's School of Computer and Cyber Sciences. He holds a Ph.D. in Computer Science from Warsaw University (1983). His research focuses on distributed computing, algorithms, wireless networks, and fault-tolerant systems. He has contributed significantly to consensus protocols, adversarial network environments, and transactional memory systems. Dr. Chlebus teaches courses such as Theory of Computation, Algorithm Analysis, and Ethics in Computer Science. He is actively involved in academic service, serving as an editor for Fundamenta Informaticae and on steering committees for international conferences like FCT and ALGOSENSORS. He has also held roles on university committees, including the Promotion & Tenure Committee and the University Senate Committee. His work emphasizes scalable solutions for distributed systems, with a focus on robustness against failures and adversarial conditions. He has published extensively on topics including consensus algorithms in Byzantine networks, energy-efficient routing, and adversarial contention resolution.

• Computational Complexity
• Graph Algorithms
• Distributed Algorithms
• +4 more

Roles and Affiliations: Aristides Pagourtzis is a Professor at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA), leading the Computer Science Division. He also serves as Lead Researcher at the Archimedes Research Center (Athena RC) and heads the Computation and Reasoning Laboratory (CORELab). His academic career includes positions at institutions like the University of Liverpool and ETH Zürich. Education: Ph.D. in Electrical and Computer Engineering (1999) and Diploma in Electrical Engineering (1989), both from NTUA. Research Interests: Computational Complexity, Graph Algorithms, Distributed Algorithms, Cryptography, and Network Algorithms. Teaching: Teaches courses such as Algorithms and Complexity, Cryptography, and Advanced Topics in Theoretical Computer Science. Courses span undergraduate and postgraduate levels, emphasizing foundational and applied computer science concepts. Publications & Grants: Over 80 publications in journals like Theoretical Computer Science and conferences like CIAC and FCT. His research has been funded by grants from the US, EU, and national resources. Notable contributions include work on approximation algorithms, distributed computing, and cryptographic protocols. Service & Leadership: Served as co-chair for CIAC 2017 and FCT 2021. Active in academic service, organizing workshops and participating in committees for conferences such as IWOCA and ACM. Labs & Teams: Leads the CORELab, focusing on theoretical computer science and its applications. Collaborates on projects involving algorithm design, complexity analysis, and secure systems.

Karen PetrieView profile

Professor

• Constraint Programming
• Genetic Algorithms
• Educational Technology
• +3 more

Karen Petrie is a Professor (Teaching and Scholarship) of Algorithms and Education in the School of Computing at the University of Dundee. Her research focuses on constraint programming, genetic algorithms, and educational technology, with notable contributions to HIV intervention analysis in Malawi and the integration of social media like Facebook in higher education. She actively engages in public outreach, including organizing events such as Discovery Days and the School of Computing Christmas Lecture. Her work bridges theoretical computer science with practical applications in education and health, emphasizing reproducibility in computational research. She has supervised five students but their names are not listed here. Her activities include school engagement initiatives and contributions to workshops on computing education and computational methods.

Anna MelnykovaView profile

Researcher

• Mathematical Neuroscience
• Stochastic Processes
• Neuronal Network Dynamics
• +3 more

Anna Melnykova is a researcher in applied mathematics at the Avignon Mathematics Laboratory (UPR 2151 LMA), part of Avignon Université. Her work focuses on mathematical modeling of neuronal activity, particularly the stochastic aspects of neural communication. She investigates how electrical discharges ('spikes') in neurons can reveal network structures and physical parameters, emphasizing probabilistic methods. Currently, she collaborates on simulating the stochastic Hodgkin-Huxley model, aiming to rigorously prove the efficacy of their numerical methods. Her research integrates stochastic processes, statistical inference, and computational biology. She actively contributes to the laboratory’s three core teams: nonlinear analysis, dynamic systems, and statistics, promoting interdisciplinary collaboration. Melnykova emphasizes curiosity, autonomy, and intellectual humility as key traits for researchers, advocating for self-driven problem-solving in academic work.

• Algorithmic and complexity
• Periodic Scheduling
• Telecom Networks
• +3 more

GUIRAUD Maël is a Researcher-Lecturer at CESI’s Nanterre Campus, affiliated with the Engineering and Numerical Tools department. He teaches in engineering programs, focusing on algorithmic, programming, operational research, and embedded systems. His research emphasizes periodic scheduling, telecom networks, and Industry 4.0 applications. Education: PhD in Computer Science (DAVID Lab, Université Paris Saclay, 2021), Master AMIS (Université Paris Saclay, 2016), and a Computer Science degree from Université de Versailles Saint-Quentin (2014). Research interests span algorithmic complexity, deterministic scheduling for low-latency networks, and smart infrastructure. Key contributions include work on Cloud RAN scheduling, TSN platforms, and smart building modeling. Recent publications address predictive maintenance in smart buildings and 5G/6G network optimization. His lab focuses on bridging theoretical algorithms with real-world applications in telecommunications and Industry 4.0 systems.

• Calculus of Variations
• Nonlinear Partial Differential Equations
• Optimal Transport
• +4 more

Emanuela Radici is an Assistant Professor at the Università degli Studi dell'Aquila, specializing in advanced mathematical analysis with a focus on Calculus of Variations, Nonlinear PDEs, and Deterministic Particle Approximation. Her research explores topics such as optimal transport, aggregation-diffusion equations, and traffic models. She has organized workshops on Calculus of Variations and PDEs, demonstrating leadership in academic collaboration. Her work bridges theoretical analysis with applied problems, including opinion dynamics and congestion modeling. Key contributions include particle approximation methods for conservation laws and studies on BV homeomorphisms. She actively participates in international conferences and research events, contributing to the advancement of geometric methods in calculus of variations. Dr. Radici’s research output includes 22 published papers, with recent works addressing nonlinear mobilities, degenerate traffic models, and minimal extensions in geometric norms. Her interdisciplinary approach integrates functional analysis, differential geometry, and numerical methods.

Zachary MainenView profile

Professor

• Neuroscience
• Neural Circuits
• Predictive Coding
• +4 more

Zachary Mainen is a Professor and Principal Investigator at the Champalimaud Foundation's Systems Neuroscience lab, leading research on neural mechanisms underlying perception, decision-making, and serotonergic modulation. His lab investigates how the brain constructs internal models of the world and evaluates sensory data to guide actions, with a focus on serotonin's role in cognitive processes and behavioral persistence. Mainen holds a PhD in Neuroscience and has extensive experience in electrophysiology, optogenetics, and computational modeling. His research integrates behavioral experiments with neural recordings in rodents to address questions about uncertainty, confidence, and neural circuit dynamics. Key areas of interest include olfactory processing, spatial navigation, stress physiology, and the neural basis of decision-making. He has mentored numerous PhD and postdoctoral researchers, fostering collaborations across institutions via initiatives like the International Brain Laboratory. Mainen's work has been published in top journals such as Nature , Neuron , and Nature Human Behaviour , with recent focus on serotonin's role in behavioral persistence and stress-induced controllability perception.

• Internet of Things (IoT)
• Cyber-Physical Systems (CPS)
• Smart Manufacturing
• +4 more

Dirk H J Pesch is a Professor at the School of Computer Science and Information Technology , University College Cork (UCC), and currently serves as Head of School. His research focuses on future networked systems for the Internet of Things (IoT) and Cyber-Physical Systems (CPS), with applications in smart communities, health, and manufacturing. He leads the Science Foundation Ireland-funded ADVANCE CRT and is a co-PI of the CONNECT Centre . Prior to UCC, he was at Cork Institute of Technology (now Munster Tech U), where he founded the Nimbus Research Centre. He holds a PhD from the University of Strathclyde and a Dipl.Ing from RWTH Aachen University. Research Interests include IoT/CPS protocols, system architectures, interoperability challenges, and AI-driven analysis for well-being. He has authored/co-authored over 250 publications and co-edited a book on energy-positive urban systems. His work spans conference organization (e.g., IEEE SmartComp 2025 General Chair) and industry collaborations, with €80M+ in grant funding. Key contributions include developing low-power wireless protocols (e.g., MeshMAC), smart building monitoring systems, and frameworks for IoT in energy-positive neighborhoods. His recent work explores loneliness detection via passive sensing and 6G-V2X technologies for autonomous driving. Grants & Leadership: Directed €16M of his own research grants, managed large-scale EU/Irish projects, and advised on industrial IoT implementations. His Nimbus Centre became a leader in IoT applications under his leadership. Labs/Teams: Founded Nimbus Research Centre; active in Cork Smart Gateway initiative. Supervised numerous students and researchers in interdisciplinary projects.

• Biophysics
• Neuroscience
• Cell Biology
• +3 more

Victor Matveev is a Professor in the Department of Mathematical Sciences at New Jersey Institute of Technology (NJIT). His research focuses on biophysical modeling of calcium-dependent processes in cellular systems, particularly presynaptic calcium signaling and synaptic plasticity. He has led multiple NSF-funded projects exploring calcium dynamics, including studies on cell calcium spatiotemporal dynamics and mechanisms of synaptic facilitation. Key research areas include calcium nanodomains, synaptic vesicle fusion mechanisms, and mathematical approaches to modeling neural systems. His work bridges applied mathematics, neuroscience, and biophysics, with applications in understanding cellular communication pathways. Recent projects include the 2022 FACM conference on mathematical biology and a 2015 NSF grant studying cell calcium dynamics. He collaborates with researchers in computational neuroscience, as evidenced by contributions to the Encyclopedia of Computational Neuroscience (2022). Grants and funding history spans over two decades, with notable projects on presynaptic calcium dynamics (2004-2008), spatiotemporal calcium dynamics (2015-2018), and applied mathematics conferences (2022-2023). His research outputs combine theoretical modeling with experimental insights, yielding 39 publications and over 1,100 citations.

• Quantum Information Science
• Quantum Computing
• Quantum Information Theory
• +2 more

Hlér Kristjánsson is an Adjunct Professor at the Faculty of Arts and Science within the Department of Computer Science and Operations Research at Université de Montréal. His research focuses on quantum information science, quantum computing, and theoretical physics, with affiliations at Mila - Quebec Artificial Intelligence Institute. He teaches IFT6760C – Seminar in Machine Learning and oversees research projects funded by the Natural Sciences and Engineering Research Council of Canada (NSERC). Key projects include exploring causal structures and functional programming in quantum computation (2025–2031), supported by NSERC Discovery Grants and Tremplin programs. His work bridges quantum mechanics with computational models, addressing topics like quantum switch simulation, indefinite causal order, and resource-theoretic frameworks. Collaborations involve experimental quantum communication enhancements and second-quantized Shannon theory. Teaching responsibilities span master’s (e.g., Machine Learning), doctoral programs in computer science, and specialized DESS programs. Funding milestones include a 7-year NSERC grant (PVX20965/RGP) and a PVXXXXXX/DGECR initiative. No scientific awards are explicitly listed, though his contributions to quantum gravity as a communication resource and routed quantum circuits highlight innovative directions. Research is anchored at Mila, emphasizing interdisciplinary applications in AI and quantum systems.

Kamil KhanView profile

Associate Professor

• Deterministic Global Optimization
• Process Systems Engineering
• Sensitivity Analysis
• +6 more

Dr. Kamil Khan is an Associate Professor of Chemical Engineering at McMaster University , part of the Faculty of Engineering . His research focuses on deterministic global optimization, nonsmooth optimization, and dynamic optimization of chemical process systems, integrating applied mathematics and algorithm development. He holds a B.S.E. from Princeton University, M.S. and Ph.D. from MIT, and completed a postdoc at Argonne National Laboratory. He teaches CHEM ENG 4E03/6E03: Digital Computer Process Control , covering digital control systems and model predictive control. His lab, the Khan Research Group , explores topics like convex relaxations, automatic differentiation, and adjoint sensitivity analysis for process optimization. Recent work includes advancements in computational methods for dynamic systems, membrane fouling prediction in water treatment plants, and subgradient evaluation for global optimization. His research bridges theoretical mathematics with practical engineering challenges.

Francesco Giacinto LavaccaView profile

Associate Professor

• All-optical networks
• Switching architectures
• 5G networks planning and design
• +4 more

Francesco Giacinto Lavacca is an Associate Professor at Link Campus University in Rome. Previously, he held a Researcher (RTDA) position at Sapienza University of Rome's DIET Department, where he conducted postdoctoral research. His work has involved national/international projects like AAA (Advanced Avionic Architecture), NMLV (Nano Micro Launch Vehicle), NGLVCS (Next Generation Launch Vehicle Communication System), HydRON, PANTSAT, and DINOS5G, funded by ASI and ESA. Research focuses on all-optical networks, 5G infrastructure design, Network Function Virtualization, and deterministic communication protocols. His expertise bridges telecommunications with aerospace applications through collaborations with space agencies. Education includes a Laurea (M.Sc.) in Electronic Engineering (cum laude, 2013) and a Ph.D. in Information Technology (2017), both from Sapienza University of Rome. Office hours: Available post-classes or by email appointment.

• 6G Networks
• Low-Latency Communications
• Network Design
• +3 more

Sofiane MESSAOUDI is a Research Fellow at EURECOM, affiliated with the Communication Systems department. His work focuses on deterministic network design and optimization for low-latency communications in 6G networks. He holds a postdoctoral position within the Communication Systems research group at EURECOM. His research interests center on advancing telecommunication networks, particularly in 6G architecture, latency reduction, and network optimization strategies. The deterministic approaches he explores aim to enhance reliability and efficiency in future communication systems. No specific grants, awards, or advised students are listed in the provided information. His current work contributes to foundational research in next-generation network technologies.

Zacharias AnastassiView profile

Associate Professor

• Numerical Analysis
• Computational Mathematics
• Scientific Computing
• +5 more

Dr. Zacharias Anastassi is an Associate Professor/Reader in Computational Mathematics at De Montfort University (DMU), serving as Deputy Subject Group Leader of Games, Mathematics & Intelligent Systems and Deputy Programme Leader of the Mathematics BSc. He holds a PhD in Numerical Analysis (2006) and a Civil Engineering diploma (2002). Previously, he served as Assistant Professor at Qatar University and in various Greek institutions. His research focuses on numerical methods for differential equations, computational algorithms, parallel computing, and applications in physics, engineering, and medicine. He has secured significant research grants and organized scientific conferences. Research Interests: Numerical solution of ODEs/PDEs, algorithm development, scientific computing, parallel algorithms, machine learning, and optimization. He has published extensively in journals like Computational and Applied Mathematics and Journal of Computational and Applied Mathematics , with recent work on hybrid block methods, nonlinear Schrödinger equations, and Parkinson’s disease classification using AI. Articles Summary: His recent work (2020–2023) emphasizes efficient numerical methods for PDEs, machine learning applications in healthcare, and dark soliton dynamics. Notable contributions include hybrid block methods for the FitzHugh-Nagumo model and parametric Runge-Kutta schemes for time-dependent NLS equations. Awards: Young Scientists Prize in Numerical Analysis (2005) and Ericsson Excellence in Telecommunications (2005). He serves on editorial boards of Mathematics , Axioms , and Foundations , and has reviewed for leading journals like Journal of Computational and Applied Mathematics . Grants & Leadership: Lead PI of a $763k Qatar grant on nonlinear metamaterials and Co-PI of an $810k grant on rogue waves. Active in academic leadership, teaching numerical methods, and supervising research in computational mathematics.

• Machine Learning
• Big Data Analytics
• Smart Cities
• +4 more

Luis Francisco Sánchez Merchante is an Assistant Professor at Comillas Pontifical University's School of Engineering (ICAI), affiliated with the Institute for Research in Technology (IIT). He holds a Ph.D. in Information Technology from the Technological University of Compiègne, specializing in Machine Learning, and degrees from UPM and UC3M. His expertise spans Big Data analytics, smart cities, and AI applications in transportation. He has 12+ years in the private sector, including roles at Alstom, Bankia, and Amadeus, and has taught at multiple institutions since 2004. Education : Ph.D. in Information Technology (Machine Learning), Technological University of Compiègne Master's in Multimedia and Communications, UC3M Telecommunications Engineering, UPM Research Interests : Advanced analytics on Big Data platforms Machine Learning applications in smart cities and transportation Unsupervised learning (clustering), supervised learning (neural networks/random forests), and reinforcement learning Image/video/audio processing for AI-driven solutions Key Projects : EU-funded Injury Mitigation for Vision-Zero (2024-2028) WHO Global Road Safety Data Analysis (2023) AI for E-Scooter Safety (Comillas, 2023-2024) Grants & Awards : No explicit awards noted, but active in competitive EU/WHO grants. Advising & Labs : Supervising PhD candidate P. López-Adeva Fernández-Layos (Rigid Body Simulation). Active in IIT's AI and transportation research groups.