Find Academic Supervisors

• Programming Languages
• Concurrent and Distributed Systems
• Formal Methods
• +4 more

Luis Caires is a Full Professor of Science and Methodology of Programming at the Department of Computer Science and Engineering, Técnico Lisboa (University of Lisbon). He is also a Core Researcher at INESC-ID and an ERA Chair Holder under the H2020 BIG initiative. Previously, he served as Full Professor at NOVA FCT’s Department of Computer Science and founded the NOVA Laboratory for Computer Science and Informatics. His research focuses on the theoretical foundations and practical applications of programming languages, emphasizing the development of trustworthy concurrent, distributed, and decentralized systems. Key themes include type systems for resource management in concurrent environments, formal logics (types, process algebra), and tools for compiler design and abstract machines. He also explores interdisciplinary areas like computational theories of mind and quantum programming models. Caires has extensive teaching experience, lecturing 23 courses across BSc, MSc, and PhD levels, including foundational programming courses and advanced topics in formal languages, verification logics, and software security. He coordinated 87 course editions between 1992 and 2023. Professional service includes PC roles at major conferences (ECOOP ’25, FoSSaCS ’25, LICS ’25/’26). His work bridges foundational research with system-building, addressing challenges in concurrency, security, and distributed computing.

Herbert LevineView profile

Professor

• Biological Physics
• Non-linear Dynamics
• Statistical Physics
• +6 more

Herbert Levine is a University Distinguished Professor of Physics at Northeastern University's College of Engineering, with a joint appointment in Bioengineering. His research focuses on Biological Physics, Non-linear Dynamics, and Statistical Physics applied to cancer biology, immunology, and cellular systems. Key research areas include modeling cancer progression/metastasis, tumor-immune system interactions, metabolic plasticity, and the mechanics of collective cell motility. He co-directs the NSF Physics Frontier Center for Theoretical Biological Physics, emphasizing interdisciplinary approaches. His work combines mathematical modeling with experimental data to explore gene regulatory networks influencing cell fate decisions, EMT plasticity, and drug resistance mechanisms. Major contributions include frameworks linking metabolic states to cancer persistence and analyzing immune evasion strategies in tumors. Grants: NSF Physics Frontier Center (Northeastern expansion), DMS/NIGMS funding for EMT stemness research Labs/Teams: Center for Theoretical Biological Physics, interdisciplinary cancer modeling group

• Human-Computer Interaction
• Virtual Reality
• Cinematic Virtual Reality
• +7 more

Heinrich Hußmann is a Professor at Ludwig Maximilian University of Munich with an extensive research career spanning from 1985 to present. His work primarily focuses on Human-Computer Interaction, with significant contributions to Virtual Reality, Tangible User Interfaces, and intelligent systems. Over his career, he has published nearly 250 papers in top-tier conferences and journals. His research interests center around understanding and improving human interaction with emerging technologies. Key focus areas include cinematic virtual reality experiences, tangible interfaces for education and collaboration, privacy in mobile contexts, and user understanding of intelligent systems. His work often bridges theoretical HCI principles with practical applications that address real-world user needs. Analysis of his recent publications (2020-2023) reveals a strong emphasis on tangible interaction for educational contexts, particularly for children's learning. He has also made significant contributions to understanding social aspects of cinematic virtual reality and developing frameworks for user understanding of AI systems. His work consistently demonstrates a user-centered approach that considers psychological, social, and technical dimensions of interaction. Professor Hußmann has mentored numerous students who have become active researchers in the HCI field, including Sarah Theres Völkel, Malin Eiband, and Daniel Buschek, among others. His collaborative network spans multiple institutions and disciplines, reflecting the interdisciplinary nature of modern HCI research. His research has practical implications for the design of more intuitive, privacy-respecting, and educationally effective interactive systems. Current projects suggest continued exploration of how physical and digital elements can be integrated to create meaningful user experiences that support learning, collaboration, and mindful technology use.

Marc RysmanView profile

Professor

• Industrial Organization
• Applied Econometrics
• Network Effects
• +4 more

Marc Rysman is a Professor of Economics at Boston University's Department of Economics within the College of Arts and Sciences. He holds a PhD in Economics from the University of Wisconsin-Madison (1999) and has served as Department Chair, Editor of the RAND Journal of Economics , and President of the Industrial Organization Society. His research focuses on industrial organization, antitrust, and regulation, with expertise in network effects, two-sided markets, and platform economics. Key areas include payment systems, telecommunication, consumer electronics, and Yellow Pages directories. Methodologically, his work combines theoretical frameworks with empirical analysis of consumer and market behavior. Rysman has contributed to understanding market dynamics in financial crises, digital infrastructure (e.g., subsea cables), and illicit drug markets. His recent work explores platform pricing strategies, faster payment systems, and the structural economics of transnational criminal networks. He teaches courses on industrial organization, econometrics, antitrust law, and regulation. His academic leadership roles include editorial positions and policy advisory work on competition matters. Rysman's research has implications for regulatory policy in two-sided markets and network industries.

• Statistics
• Time Series Forecasting
• Bayesian Analysis
• +3 more

Ben Powell is a mathematician/statistician and faculty member at the University of York, where he leads research in time series forecasting and Bayesian analysis within the Statistics and Probability Research Group. He serves as Head of Admissions and teaches modules in Bayesian Statistics and Linear Models. His research focuses on identifying patterns in historical data to predict future outcomes, with applications spanning climatology, economics, bioinformatics, and medical data. Current investigations emphasize forecast aggregation and bioinformatic modeling of biological systems. Dr. Powell actively advises PhD students in statistical methodologies and maintains collaborations across disciplines to solve domain-specific prediction challenges.

Robin YoungView profile

Professor

• Nonlinear Partial Differential Equations
• Hyperbolic Conservation Laws
• Shock Waves
• +3 more

Robin Young is a Professor in the Department of Mathematics and Statistics at the University of Massachusetts Amherst. His research focuses on nonlinear hyperbolic waves and their interactions in systems of conservation laws, particularly in fluid dynamics and classical mechanics. Notably, he has collaborated with Blake Temple to resolve a 175-year-old paradox in acoustics by proving the existence of smooth, time-periodic nonlinear sound waves in the compressible Euler equations, providing a rigorous foundation for linear acoustics models. Young holds a Ph.D. in Mathematics from the University of California, Davis (1991), and B.Sc. degrees from the University of the Witwatersrand (1984 and 1985). His work spans theoretical analysis of shock waves, periodic solutions, and vacuum phenomena, with applications to gas dynamics and nonlinear elasticity. His research highlights include global existence results for large-amplitude solutions in isentropic gas dynamics, studies of resonance-driven wave patterns, and the development of numerical methods like modified front tracking. He has been supported by NSF grants DMS-0104485 and DMS-0507884, advancing the understanding of hyperbolic conservation laws and their connections to KAM theory through small divisor problems in periodic solutions. Key contributions include resolving vacuum dynamics in gas systems, analyzing blowup mechanisms in nonlinear systems, and exploring wave interactions in elastic materials. His work bridges analytical rigor with physical intuition, addressing foundational questions in continuum mechanics and nonlinear wave theory.

Philip MinderhoudView profile

Assistant Professor

• Coastal-Deltaic Environmental Change
• Land Subsidence
• Relative Sea-Level Rise
• +4 more

Dr. Philip Minderhoud is an Assistant Professor at Wageningen University & Research and a Veni laureate, specializing in coastal-deltaic environmental change with a focus on land subsidence and relative sea-level rise. He holds affiliations at the University of Padova (former Marie Curie Fellow) and advises Deltares. His research spans global deltas including the Mekong, Irrawaddy, Mississippi, and West African coasts, emphasizing subsidence drivers, numerical modeling, and policy engagement. He co-founded the International Panel on Land Subsidence (IPLS) to integrate global subsidence data into IPCC projections. Dr. Minderhoud teaches BSc/MSc courses on geology, coastal oceanography, and field geosciences in Spain. His work bridges academia and practice through collaborations with governments, NGOs, and industry to develop mitigation strategies against subsidence-driven risks. Education: PhD in delta land subsidence through the Dutch-Vietnamese Rise and Fall project. Research Focus: Combines geomorphology, hydrogeology, and remote sensing to understand subsidence mechanisms. Current projects include the 3MAP initiative and the InSPiRED EU project. Key regions studied: Vietnam, Indonesia, Ghana, Nigeria, Italy, and the USA. Awards: Veni laureate (Netherlands), EU Marie Curie Fellowship. Impact: Advocates for science-informed groundwater management and delta sustainability, contributing to policy frameworks through IPLS and direct engagement with policymakers.

Elaine CrooksView profile

Professor

• Nonlinear partial differential equations
• Singular limits of elliptic and parabolic systems
• Reaction-diffusion-convection systems
• +3 more

Professor Elaine Crooks is a faculty member at Swansea University's School of Mathematics and Computer Science within the Faculty of Science and Engineering. Based at the Computational Foundry on Bay Campus, her research focuses on nonlinear partial differential equations with applications spanning materials science, ecology, and image processing. She specializes in singular limits of PDEs, reaction-diffusion systems, travelling waves, and geometric methods for feature detection in images. Her research investigates fundamental mathematical phenomena including: Asymptotic behavior of reaction-diffusion-convection systems Front propagation in anisotropic media Spatial segregation in population dynamics Compensated convex transforms for geometric singularity detection Phase transitions in liquid crystals Ecological invasion modeling Analysis of her recent publications reveals strong emphasis on: nonlinear diffusion phenomena, theoretical foundations of convex transforms, travelling wave solutions, and applications of PDEs to biological systems. Her work consistently bridges theoretical mathematics with practical applications in materials science and computational imaging. Professor Crooks actively supervises PhD students in areas including reaction-diffusion systems, mathematical neuroscience, and wave propagation analysis. She teaches foundational mathematics courses including Introduction to Analysis 1 & 2, offered in both English and Welsh.

Ahmad AbdelfattahView profile

Academic

• High Performance Computing
• Parallel Numerical Algorithms
• GPU Computing
• +3 more

Dr. Ahmad Abdelfattah is a Research Assistant Professor at the University of Tennessee's Innovative Computing Laboratory (ICL). He holds a PhD in Computer Science from KAUST (2015), an MS in Computer Engineering from Ain Shams University (2010), and a BS in Computer Engineering (2006). His research focuses on high-performance computing, parallel numerical algorithms, and GPU acceleration, particularly in dense and sparse linear algebra libraries. He leads the MAGMA library and has contributed to NVIDIA's cuBLAS and AMD's rocBLAS libraries. His work emphasizes exascale computing, mixed-precision arithmetic, and optimizing batched operations on GPUs. His research spans algorithm design for GPUs, including batched matrix operations, sparse linear algebra, and high-order finite element methods. He has developed libraries like libCEED and SLATE, targeting exascale systems. His contributions address challenges in memory-bound computations, irregular patterns in matrices, and efficient use of tensor cores. Key trends in his publications include optimizing GPU kernels for small matrices, exploring mixed-precision techniques for solving linear systems, and enabling portable performance across diverse architectures. His work bridges theoretical numerical methods with practical implementation on modern hardware, aiming to accelerate scientific applications. Awards and recognitions include acknowledgments from NVIDIA and AMD for contributions to their BLAS libraries. His advising and grants involve advancing exascale computing through collaborations with ECP (Exascale Computing Project), focusing on CEED-enabled applications and performance tuning. He leads initiatives to enhance software tools for high-order discretizations and scalable linear algebra solutions. Abdelfattah is affiliated with the Innovative Computing Laboratory, contributing to both academic and industrial partnerships. His research impacts fields like computational science, computer vision, and robotics through optimized algorithms and libraries.

Piotr LuszczekView profile

Research Professor

• High-Performance Computing
• Numerical Linear Algebra
• Benchmarking
• +3 more

Piotr Luszczek is a Research Professor and Adjunct Associate Professor at the University of Tennessee, Knoxville's Tickle College of Engineering, affiliated with the Department of Computer Science and the Innovative Computing Laboratory. He holds a Ph.D. and M.S. from the University of Tennessee, Knoxville, and a B.S. from AGH University of Science and Technology in Kraków, Poland. Affiliations : Innovative Computing Laboratory (ICL), Tickle College of Engineering. Roles : Research and teaching in high-performance computing, numerical linear algebra, and performance optimization. Research Interests focus on benchmarking, numerical linear algebra for HPC, automated performance tuning for modern hardware, and stochastic models for performance analysis. His work emphasizes scalable algorithms, GPU acceleration, and efficient use of hybrid architectures. Grants and Collaborations include projects on batched linear algebra, sparse matrix operations, and energy-efficient AI frameworks. He contributes to software libraries like PLASMA and MAGMA, optimizing for exascale computing. Labs/Teams : Active in the Innovative Computing Laboratory (ICL), developing tools for HPC benchmarking (e.g., HPCG) and parallel linear algebra libraries. Engaged in international collaborations for exascale computing initiatives.

Saad MansoorView profile

Senior Lecturer

• Modelling and Simulation
• Non-linear Systems
• Computer Networks
• +5 more

Dr. Saad Mansoor is a Senior Lecturer in Computer Science at Bangor University's School of Computer Science and Engineering , appointed in 2003. He serves as Postgraduate Course Manager and Admissions Tutor, with teaching expertise in computer science, modeling, and simulation. Education: Doctor of Science (DSc), University of Wales, Bangor (2000) Research Interests focus on: Modeling and analysis of non-linear systems Computer network security and dynamics Control theory applications in hydropower systems Simulation methodology development His publications span hydropower plant modeling , optical network innovations , and control system design , with collaborations across academia and industry. Key projects include Water4Cities (2017-2022) and NCTCW (2013-2015). Scientific Awards: 2023 Queen's Anniversary Prize for Grid Stability Research As Head of School, he leads academic strategy while maintaining active research roles in the VDMG research group and supervising postgraduate work.

Chun-Hua OuView profile

Professor

• Mathematical Biology
• Applied Dynamical Systems
• Differential Equations Theory
• +3 more

Chun-Hua Ou is a Professor of Mathematics at the Department of Mathematics and Statistics , Memorial University of Newfoundland . He holds a B.S. from Peking University and a Ph.D. from City University of Hong Kong. Research Interests : Mathematical Biology, Applied Dynamical Systems, Differential Equations Theory, Asymptotic Analysis, and Nonlinear Dynamics. His work focuses on spatial-temporal patterns in physical and biological systems, using both theoretical methods and numerical simulations. Editorial Roles : Associate Editor of Boundary Value Problems (Springer Open) Associate Editor of New Trend in Nonlinear Analysis and Application Teaching : Recently taught advanced courses including Stochastic Differential Equations and Applied Partial Differential Equations , with extensive teaching history in ordinary/partial differential equations, linear algebra, and dynamical systems. Research Trends : His recent publications emphasize traveling wave solutions in competitive systems, population dynamics, and the impact of environmental heterogeneity on wave propagation speeds. Key topics include Lotka-Volterra models, Allee effects, and stability analysis of dynamic systems.

• Econometrics
• Public Health
• Medical Statistics
• +3 more

Fabienne Pradella is a researcher affiliated with the Department of Statistics and Econometrics at Johannes Gutenberg University Mainz. Her work focuses on the intersection of epidemiology, public health, and econometrics, with a particular emphasis on understanding how prenatal environmental factors—including cultural practices like Ramadan fasting during pregnancy—affect long-term health outcomes for offspring. She has conducted extensive research on topics such as maternal dietary intake, neonatal health, and the metabolic consequences of temperature exposure during conception. Dr. Pradella’s research employs advanced statistical methods and quasi-experimental designs to analyze data from diverse populations, including Indonesia, Nigeria, and Australia. Her studies often integrate large-scale biobank datasets and cross-sectional surveys to uncover mechanisms linking early-life conditions to adult health trajectories. Education: Details not explicitly stated in provided texts. Awards: 2017 GMDS Conference Best Poster Prize for her work on in-utero Ramadan exposure in Germany. Research Themes: Prenatal environmental influences on health Ramadan fasting during pregnancy Vaccination impacts on age-related diseases Cultural practices and health outcomes Her recent publications explore novel connections between herpes zoster vaccination and dementia prevention, as well as the role of climate variables in metabolic disorders. She has also contributed to systematic reviews synthesizing evidence on offspring health outcomes linked to Ramadan exposure.

Chao LanView profile

Assistant Professor

• Machine Learning
• Artificial Intelligence
• Data Science
• +4 more

Chao Lan is an Assistant Professor at the School of Computer Science , University of Oklahoma. His research focuses on Machine Learning, particularly in fairness, multi-view learning, kernel methods, and privacy-preserving techniques. He holds a Ph.D. in Computer Science from the University of Kansas, and M.S. and B.S. degrees from Nanjing University of Posts and Telecommunication, China. Key professional roles include Area Chair for ICML'25 and NeurIPS'24, and Senior Program Committee member for PAKDD'25. He serves as an Associate Editor for ACM Transactions on Probabilistic Machine Learning (2024–present) and has received recognition as a Top Reviewer for multiple conferences. Education: Ph.D., Computer Science, University of Kansas M.S., Computer Science, Nanjing University of Posts and Telecommunication, China B.S., Computer Science, Nanjing University of Posts and Telecommunication, China His research emphasizes theoretical and applied machine learning, including fairness-aware algorithms, efficient kernel methods, and distributed systems with privacy guarantees. Recent work explores randomized learning frameworks and debiasing techniques in semi-supervised and multi-view contexts. Lauded for contributions, he has earned awards such as the NSF CRII Award (2019), Distinguished Paper Award at ACSAC 2021, and multiple scholarship recognitions. His publications span top venues like ICML, NeurIPS, KDD, and IJCAI.

• Computability Theory
• Mathematical Logic
• Descriptive Set Theory
• +2 more

Dino Rossegger is a mathematician working at the Institute of Discrete Mathematics at Technische Universität Wien. He serves as Principal Investigator for the international project "Structural Complexity Measures for Foundational Theories" funded by the Austrian Science Fund. Previously, he completed a Marie Skłodowska Curie fellowship called ACOSE (Algorithmic Complexity of Structural Equivalence Relations) which involved a two-year research phase at UC Berkeley under Antonio Montalbán's supervision followed by a return phase at TU Wien under Ekaterina Fokina's supervision. His research focuses on computability theory and its interactions with descriptive set theory and model theory. Rossegger investigates fundamental questions about the algorithmic complexity of mathematical structures, particularly examining degrees of categoricity, bi-embeddability spectra, and the relationship between computational and descriptive complexity measures. His work often bridges the gap between pure computability theory and broader mathematical contexts, as evidenced by his publications on linear orderings, models of arithmetic, and equivalence relations. Rossegger's publication record shows consistent output in top-tier logic journals including the Journal of Symbolic Logic, Proceedings of the American Mathematical Society, and Journal of Mathematical Logic. His recent work demonstrates growing influence in the field of computable structure theory, with particular attention to the interplay between Turing degrees and structural complexity measures. The pattern of his publications reveals a deepening exploration of how computational constraints affect the classification of mathematical structures. Marie Skłodowska Curie Global Fellowship recipient Principal Investigator for Austrian Science Fund project Extensive publication record in mathematical logic journals Rossegger has taught courses at multiple institutions including Technische Universität Wien, University of California Berkeley, and University of Waterloo. His teaching spans advanced mathematical logic topics, recursion theory, and calculus for honors mathematics students. He has developed comprehensive course materials including detailed notes for computability theory and mathematical logic courses. At TU Wien, he has also taught exercise sessions for first-year mathematics courses for computer scientists. His involvement in the local research seminar at TU Wien and organization of the "Computable Structure Theory and Interactions" conference demonstrates his active engagement with the research community.