Find Academic Supervisors

John van de WeteringView profile

Assistant Professor

• Quantum Computing
• Quantum Foundations
• ZX-calculus
• +4 more

John van de Wetering is an active Assistant Professor at the Theoretical Computer Science group of the Informatics Institute of the University of Amsterdam (UvA), working in collaboration with the QuSoft research center. He joined the university in December 2022 after completing his PhD at Radboud University in 2020 and a postdoc position at Oxford University. His research spans two primary domains: diagrammatic techniques in quantum computation (particularly ZX-calculus applications for quantum circuit optimization, classical simulation and verification) and quantum foundations where he explores the nature of quantum mechanics through algebraic and compositional methods. He is the co-creator of PyZX, an open-source optimizing quantum compiler, and has co-authored the book "Picturing Quantum Software" with Aleks Kissinger. His work bridges theoretical computer science with practical quantum computing applications. His publication record shows consistent high-impact output with multiple papers in Physical Review A, Quantum, and proceedings of major conferences like QPL. His recent work focuses on quantum circuit optimization, ZX-calculus completeness, and applications to quantum error correction. His research demonstrates a strong trajectory with publications extending into 2025. VENI grant recipient for quantum computing research He currently supervises three PhD students (Lia Yeh, Sarah Li, and Marc Farreras) and has previously mentored numerous Master's and Bachelor's students whose work has led to publications. He serves as program director for the new Master in Quantum Computer Science at UvA and is an editor for the diamond open-access journal Quantum. His professional activities include developing educational resources like the ZX-calculus website and contributing to the ZX-calculus Wikipedia page.

José A. Á. AntolínezView profile

Assistant Professor

• Coastal Engineering
• Climate Change
• Machine Learning
• +9 more

José A. Á. Antolínez serves as an Assistant Professor in Coastal Engineering within the Hydraulic Engineering department at Delft University of Technology's Civil Engineering & Geosciences faculty. His academic career bridges research, education, and practical applications in coastal engineering with a focus on addressing climate change challenges. His educational background includes a Ph.D. in Civil Engineering (Morphodynamic coastal evolution in a changing climate) from Universidad de Cantabria (2013-2018), an M.Sc. in Integrated Coastal Zone Management from Universidad de Cantabria (2011-2013), and an M.Sc. in Civil Engineering with specialization in structures from Universidade da Coruña (2004-2009). Antolínez's research focuses on understanding coastal dynamics and processes, connecting them with climate and anthropogenic drivers, developing parameterization schemes for coastal modeling, enhancing modeling workflows, and improving the usability of model predictions for coastal management. His experimental designs frequently employ hybrid workflows combining observations, numerical models, and AI. His research spans coastal hydrodynamics, nature-based solutions, geomorphology, climate adaptation, emerging technologies, and uncertainty analysis. His recent publications (2024-2025) demonstrate strong activity in shoreline dynamics, flood risk assessment, coastal modeling, and sea turtle conservation applications. His work shows particular strength in applying machine learning and statistical methods to coastal engineering problems, with publications appearing in journals like Natural Hazards and Earth System Sciences, Coastal Engineering, and Communications Earth and Environment. Among his scientific contributions are the FPU fellowship received during his doctoral studies and leadership of the Coastal Science with AI in a Changing Climate research group. He coordinates the working AI group of the DIGISHAPE network, connecting companies, institutes, and governmental organizations in the Dutch Water sector. Antolínez has supervised students as an External PhD Supervisor at Griffith University (2019-2023) and has held various visiting researcher positions at Texas A&M University, IHE Delft Institute for Water Education, Auckland University, Oregon State University, Duke University, and USGS. Previously, he worked as a medior advisor at Deltares' Applied Morphodynamics section (2018-2020).

Maurice van TiggelenView profile

Researcher

• Polar Meteorology
• Glaciology
• Remote Sensing
• +3 more

Maurice van Tiggelen is a Researcher at Utrecht University's Institute for Marine and Atmospheric Research (IMAU), working within the Physics department specializing in Dynamics Meteorology. Based at the Buys Ballotgebouw in Utrecht, he focuses on polar meteorology, glaciology, and remote sensing, with particular expertise in ice-atmosphere interactions and surface mass balance of ice sheets. His research centers on the coupling between ice surfaces and the atmosphere, especially how atmospheric boundary layer turbulence contributes to ice ablation. Van Tiggelen employs a multi-method approach combining automatic weather station measurements on the Greenland Ice Sheet, drone imagery, satellite altimetry, and atmospheric modeling at various scales. His work has significant implications for understanding sea-level rise, as ice sheet mass loss has contributed substantially to global sea-level rise since 1901. The analysis of his recent publications reveals a consistent focus on quantifying turbulent heat fluxes over ice sheets, improving aerodynamic roughness parameterizations, and developing methods for monitoring surface energy balance. His research spans both the Greenland and Antarctic ice sheets, with increasing attention to high-resolution modeling techniques and remote sensing validation. Van Tiggelen completed his PhD in 2023 with a thesis titled 'Roughish ice, snow and turbulent heat fluxes on the Greenland ice sheet' and maintains active research collaborations with institutions worldwide. His technical skills include Python programming and Geographic Information Systems, which support his data-intensive research approach.

• Computational Subsurface Hydrology
• Discrete Fracture Network Modeling
• Anomalous Transport in Porous Media
• +7 more

Rishi Parashar serves as a Research Professor in Hydrologic Sciences at the Desert Research Institute (DRI), affiliated with the University of Nevada Reno's Graduate Program of Hydrologic Sciences. His work bridges computational hydrology, geothermal systems, and microbial transport processes within fractured rock environments. Education: Ph.D. in Civil Engineering, Purdue University (2008) M.S. in Civil Engineering, Purdue University (2003) B.S. in Civil Engineering, Indian Institute of Technology, Roorkee (2001) Parashar's research centers on computational subsurface hydrology , where he develops discrete fracture network (DFN) models to simulate anomalous transport in porous media and upscaling techniques for complex flow systems. His hydro-bio-chemical systems work examines microbial motility, biofilm growth, and biogeochemical reactions governing contaminant fate. In thermo-hydro-mechanical interactions , he investigates enhanced geothermal systems (EGS) and induced seismicity through coupled process modeling. Recent publications reveal increasing integration of machine learning with traditional hydrological modeling, particularly in particle tracking and reactive transport upscaling. Analysis of his 15 most recent articles (2021-2025) shows dominant focus areas: 40% on microbial transport in porous media (including bacterial motility and biofilm effects), 30% on fracture network modeling and upscaling, 20% on contaminant remediation (particularly arsenic), and 10% on geothermal system dynamics. His collaborative work spans environmental engineering, computational science, and microbiology, with frequent co-authorship patterns indicating strong mentorship of early-career researchers. Parashar actively secures research funding through Department of Energy contracts, particularly for Nevada National Security Site projects involving fractured rock characterization. His advising portfolio includes numerous graduate students leading publications in high-impact journals like Water Resources Research and Advances in Water Resources . Current projects involve quantum algorithms for well capture zone determination and heat-sensitive epoxy foams for geothermal permeability alteration. Research Infrastructure: His work leverages DRI's computational resources for large-scale DFN simulations and collaborates with DOE laboratories on experimental validation through microfluidic devices and field-scale tracer tests. The Hydrologic Sciences division provides access to advanced characterization facilities for fractured rock systems.

Anthony PEREZView profile

Lecturer

• Parameterized Complexity
• Graph Algorithms
• Community Detection
• +3 more

Anthony PEREZ is a Lecturer in Computer Science at the University of Orleans, affiliated with LIFO (Laboratory of Fundamental Computer Science of Orleans) and part of the Graphs, Algorithms, and Computational Models team. He previously held a full-time ATER position at the same university from 2011 to 2012 and completed his PhD at LIRMM (Montpellier II University) under the supervision of Stéphane Bessy and Christophe Paul. Research Focus: Parameterized complexity, graph modification problems, community detection in directed graphs, and sparse graph embeddings Software Development: Created SINr (sparse interpretable node representations), Directed Louvain (modularity optimization for directed networks), and GeST (graph embedding-based image segmentation) His research explores polynomial kernelization for graph editing problems, particularly in triangulated graph subclasses, and challenges the common practice of ignoring edge direction in community detection algorithms. He has co-supervised multiple PhD students including Joanne Dumont and Maël Dumas, and collaborates extensively on graph-theoretical problems with applications to social network analysis.

Toomas Erik AnijärvView profile

Researcher

• Medical imaging science
• Neurology
• Geriatrics
• +7 more

Toomas Erik Anijärv is a Doctoral student and Researcher at Lund University's medical faculty, specializing in clinical memory research through affiliations with MultiPark (a multidisciplinary Parkinson's disease research center). His work bridges neuroscience, neurology, and geriatrics with emphasis on EEG-based neurophysiological analysis. His primary research domains include: Alzheimer's and Parkinson's disease mechanisms through neuroimaging EEG spectral analysis of healthy aging and cognitive decline Neurophysiological impacts of cyberbullying on adolescent development Ketamine treatment response prediction using EEG complexity metrics Eating disorder neurobiology through cognitive and emotional processing Analysis of his 14 most recent publications (2020-2025) reveals sophisticated application of Bayesian statistics, linear regression, and multiscale entropy analysis to neuroimaging data. His work frequently leverages the LEISURE study cohort examining brain-behavior relationships in aging populations. A significant portion investigates hemispheric asymmetry in neurodegenerative diseases and the neurophysiological underpinnings of mental health conditions. Currently active in the "Early brain functional changes in the Alzheimer's disease continuum" project (since August 2023), Anijärv works under Professor Oskar Hansson's supervision. This project appears integral to his doctoral thesis work, connecting EEG biomarkers with early Alzheimer's pathology.

Tyler RobinsonView profile

Associate Professor

• Exoplanet atmospheres
• Radiative transfer modeling
• Climate modeling of planetary atmospheres
• +4 more

Tyler Robinson is an Associate Professor in the Lunar and Planetary Laboratory (LPL) at the University of Arizona, joining in 2022. He specializes in exoplanet and Solar-System atmospheric science, radiative transfer, and direct imaging instrumentation. Education Ph.D., Astronomy/Astrophysics, University of Washington (2012) Research Interests Robinson develops and applies sophisticated radiative-transfer and climate models to study the atmospheres of exoplanets, brown dwarfs, and Solar-System worlds. His work includes retrieval algorithms, instrument performance modeling, and mission concept studies for next-generation space telescopes such as the Nancy Grace Roman Space Telescope Coronagraph, the Habitable Worlds Observatory (HWO), and previously HabEx, LUVOIR, WFIRST/Rendezvous, and Origins Space Telescope. Key focus areas: Exoplanet atmospheric characterization via direct imaging and transit spectroscopy Biosignature and technosignature detection and interpretation Cloud microphysics and climate modeling for terrestrial and sub-Neptune exoplanets Instrument modeling for coronagraphs and starshades Validation of retrieval techniques using Solar-System analog observations Scientific Awards & Honors Cottrell Scholar NASA Sagan Fellow NASA Postdoctoral Program Fellow Grants & Funding Leadership PI, NASA Exoplanets Research – "Titan and Earth as Exoplanet Analogs" PI, NSF Astronomy & Astrophysics – "Moist Convection in Sub-Neptune Atmospheres" PI, NASA Roman Space Telescope Coronagraph Community Participation Program – "Giant Exoplanet Models" PI, NASA Habitable Worlds – "Habitability Signatures for Directly-Imaged Exoplanets" Co-I or collaborator on multiple additional NASA and NSF awards Laboratory & Team Robinson leads the HABLab research group at LPL, currently mentoring two Ph.D. students (Searra Foote and Lily Robinthal) and hosting postdoc Zarah Brown (James Windsor was a former postdoc). The group develops models and retrieval tools that support NASA mission planning and data interpretation.

• Multiphysics Modeling
• Biomedical Engineering
• Fuel Cell Technology
• +2 more

Dr. Guido Sartoris is a researcher at Zurich University of Applied Sciences (ZHAW) in the School of Engineering, affiliated with the ICP Multiphysics Modeling and Imaging group. Based at Technikumstrasse 71, Winterthur, he maintains active research contact via email guido.sartoris@zhaw.ch and phone +41 (0) 58 934 77 95. His research spans multiphysics computational modeling with distinct focus areas: biomedical engineering (blood flow/pressure diagnostics for INOCA), fuel cell technology (solid oxide and polymer electrolyte systems), and organic electronics (OLED device physics). Current projects include completed work on PhysioCath-microcatheter systems for coronary artery diagnostics, demonstrating interdisciplinary application of engineering principles to medical challenges. Publication trends from 2003-2013 reveal evolving expertise from fundamental nanotechnology and fuel cell modeling toward biomedical applications. His computational work consistently addresses transport phenomena, microstructural effects, and multi-dimensional simulation challenges across energy and medical domains, with recent emphasis on cardiovascular diagnostics. Dr. Sartoris participates in research projects as team member, notably the completed INOCA diagnostic initiative. No student advisement details are provided in available materials. He operates within ZHAW's ICP Multiphysics Modeling and Imaging framework, which integrates advanced computational techniques for complex engineering problems requiring coupled physics simulations.

Wallner, JohannesView profile

Professor

• Discretization in Geometry and Dynamics
• Computational Line Geometry
• Freeform Architecture
• +8 more

Johannes Wallner is a Professor of Geometry at the Institute for Geometry , Graz University of Technology (TU Graz), since January 2007. Previously, he held positions at TU Wien, including a part-time professor role (2009-2013) in the Geometric Modeling and Industrial Geometry group. His work bridges theoretical geometry with computational applications in architectural design, machining, and surface analysis. Research Interests: Discretization in Geometry and Dynamics Computational Line Geometry Freeform Architectural Structures Subdivision Algorithms in Riemannian Geometry Geometric Tolerancing and Constraint Problems Publications focus on discrete differential geometry, mesh processing, and geometric modeling for architecture. His 2024 work on quad mesh mechanisms and 2023 studies on developable surfaces exemplify his cross-disciplinary impact. Grants: Led FWF-funded projects including SFB/Transregio (I-705), Doctoral College Discrete Mathematics (W1230), and studies on computational differential geometry, nonlinear subdivision, and geometric tolerancing. Editorial Contributions: Co-edited conference proceedings for Advances in Architectural Geometry (2010, 2012, 2014) and served as editor for Internationale Mathematische Nachrichten (2008-2017).

• Quantum Computation
• Quantum Programming
• Formal Methods
• +6 more

Professor Mingsheng Ying (University of Technology Sydney) is a Distinguished Professor specializing in quantum programming , quantum verification , and the foundations of artificial intelligence . He leads the Centre for Quantum Software and Information and co-founded the Quantum Lab . His work bridges quantum computation with formal methods and reasoning under uncertainty. Education : Mathematics, Fuzhou Teachers College (1981) Research Interests His research spans: Quantum programming languages and verification techniques Model checking quantum systems and cryptographic protocols Quantum machine learning robustness Entanglement theory and distributed quantum computation Recent Publications Key contributions include: Quantum error correction verification frameworks Quantum register machine architecture Hamiltonian simulation parallelization Symbolic execution for quantum debugging Robustness tools like VeriQR Awards & Editorial Roles NSF China Distinguished Young Scholar Award (1997) China National Science Award (2008) Co-Editor-in-Chief, ACM Transactions on Quantum Computing Vice President, International Fuzzy Systems Association (2005) Leadership & Grants He oversees 14 active grants (2010–2029) from: Australian Research Council (ARC Discovery Projects) National Natural Science Foundation of China Sydney Quantum Academy Baidu Contract Research His grants fund research in quantum program verification, entanglement classification, and distributed quantum protocols.

• Theoretical Computer Science
• Computational Complexity
• Logic in Computer Science
• +2 more

Dr. Friedrich Slivovsky is a computer scientist specializing in computational complexity, logic in computer science, and algorithm design. His research focuses on quantified Boolean formulas (QBF), SAT solving, and circuit minimization, with recent contributions to fine-grained complexity analysis and structure-aware lower bounds. He serves as a module co-ordinator for postgraduate and undergraduate courses in optimization at his institution. 2025: Fine-Grained Complexity Analysis of Dependency Quantified Boolean Formulas (QBF complexity, dependency schemes) 2024: Strategy Extraction by Interpolation (proof complexity), eSLIM: Circuit Minimization with SAT (logic synthesis), Hardness of Random Parity Encodings (CDCL solver analysis) 2023: Circuit Minimization with QBF-Based Synthesis (exact circuit optimization), Structure-Aware QBF Lower Bounds (tractability expansion) His work bridges theoretical analysis with practical applications in automated reasoning and formal verification. Teaching roles include coordinating optimization modules, emphasizing algorithmic efficiency and computational problem-solving.

• Efficient Algorithms
• Computational Complexity
• Network Foundations
• +5 more

Dr. George B. Mertzios is an Associate Professor at the Department of Computer Science, Durham University , UK. His career spans roles including Senior Lecturer (2015-2017) and Lecturer (2011-2015) at Durham, with additional positions as an Invited Assistant Professor at LaBRI, University of Bordeaux/CNRS, France (2012), and postdoctoral research fellowships at the University of Haifa and Technion, Israel (2010-2011). He earned his PhD in Computer Science from RWTH Aachen University (2009) and a Diplom in Mathematics from Technische Universität München (2005). Education PhD in Computer Science, RWTH Aachen University, 2009 Diplom in Mathematics (minor in Computer Science), Technische Universität München, 2005 Research Interests focus on efficient algorithms and computational complexity in temporal graphs , with significant contributions to dynamic network optimization , evolutionary graph theory , and parameterized complexity . His work bridges combinatorial optimization , algorithmic game theory , and intersection graph models . Scientific Activities include organizing Co-Chair of the PC for SAND 2026 Co-Organizer of Dagstuhl Seminar 26251 (2026) Organizer of the Algorithmic Aspects of Temporal Graphs workshops (2018-2025) His 15 most recent articles (2025-2021) address problems in temporal graph realization , dynamic network optimization , Hamiltonian cycles , and epidemic control on temporal networks , published in top venues like Theoretical Computer Science , Journal of Computer and System Sciences , and Algorithmica . Scientific Awards include a Gold Medal in the 1998 Balkan Mathematical Olympiad, Distinguished Diploma in the 1998 Bulgarian National Mathematical Competition, and Best Paper Awards at ALGOWIN 2025 and ICALP 2010 Track C. Research Supervision includes advising PhD students: David Fairbairn (in progress), David Kutner (2025), Nina Klobas (2024), Charles Murray (2021), Sepehr Meshkinfamfard (2016), Ioannis Lignos (2016) Postdoctoral researchers: Christoforos Raptopoulos (2020), Viktor Zamaraev (2017-2019), André Nichterlein (2016-2017), Archontia Giannopoulou (2014-2015), Konrad Dabrowski (2012-2013) Grants led include EPSRC grants EP/P020372/1 (2017-2020) on algorithmic aspects of temporal graphs and EP/K022660/1 (2013-2015) on intersection graph models. He also contributed to the EU IP MULTIPLEX (2012-2016).

Andrius RapalisView profile

Researcher

• Biomedical Engineering
• Signal Processing
• Autonomic Nervous System
• +1 more

Dr. Andrius Rapalis is a Senior Researcher at the Kaunas University of Technology Institute of Biomedical Engineering and serves as Laboratory Manager at the Biomedical Device Innovation Laboratory . His research focuses on biosignal parameterization and analysis algorithms, autonomic nervous system assessment, and development of smart wearable devices. Research Interests: Biosignal parameterization and analysis algorithms Autonomic nervous system assessment Smart wearable devices Contact: Email: andrius.rapalis@ktu.lt

Parosh Aziz AbdullaView profile

Professor

• Concurrency
• Distributed Systems
• Program Verification
• +5 more

Parosh Aziz Abdulla is a Chaired Professor at the Department of Information Technology, Uppsala University, Sweden. He is a prominent researcher in the field of theoretical computer science with a focus on formal methods, concurrency, and program verification. His work bridges theoretical foundations with practical applications in software and hardware verification. Professor Abdulla's primary research interests include Concurrency, Distributed Systems, Program Verification, Model Checking, Automata, and Logic. His work spans both theoretical aspects of computer science and practical verification techniques for concurrent and distributed systems. He has made significant contributions to the understanding of memory models, particularly in the context of modern architectures like x86 with persistent memory. His research has evolved from foundational work on infinite-state systems to practical verification techniques for concurrent programs and string constraints. Professor Abdulla has served on numerous program committees for top-tier conferences including PLDI, POPL, CAV, CONCUR, and TACAS, demonstrating his standing in the research community. He has been PC co-Chair for TACAS'11 and has contributed to many other conferences over the years. As an advisor, Professor Abdulla has supervised numerous PhD students to completion, with graduates working on topics ranging from verification of networks of communicating processes to caches, transactions, and memory models. His students have gone on to successful careers in academia and industry. Professor Abdulla maintains an active research agenda, with recent work focusing on verification of quantum circuits, efficient linearizability monitoring, and verification under Intel-x86 with persistency. His research continues to address fundamental challenges in program verification while adapting to new computing paradigms and hardware architectures.

Martin KellerView profile

Professor

• Control Engineering
• Automated Driving Systems
• Model Predictive Control
• +4 more

Prof. Dr.-Ing. Martin Keller is a Professor of Control Engineering at the Department of Electrical Engineering & Information Technology, South Westphalia University of Applied Sciences in Hagen, Germany. He leads research in advanced control systems with a specialization in automotive applications and automated driving technologies. His academic leadership includes directing the Laboratory for Control Engineering where practical courses, project work, and research activities are conducted. Education: Diploma in Electrical Engineering from TU Dortmund (2011), PhD in Control Systems Engineering from TU Dortmund (2017) Professional Experience: Algorithm Development Engineer (2017-2019) and Team Lead (2019-2022) at ZF Group before transitioning to academia Teaching Responsibilities: Courses in Control Engineering 1/2, Medical Control Systems, and Advanced Control Systems Professor Keller's research centers on automated driving systems with emphasis on trajectory planning, collision avoidance, and vehicle guidance algorithms. His work bridges theoretical control concepts with practical automotive implementations, particularly focusing on model predictive control frameworks for real-time applications. The research group develops algorithms for maneuver decision-making, trajectory planning, and tracking control essential for autonomous vehicle functions. Analysis of his 15 most recent publications reveals strong concentration in automated driving control systems , with 80% of works published between 2018-2021 focusing on trajectory optimization, collision avoidance, and model predictive control applications. Key research themes include sampling-based planning methods, environment modeling for optimization, and real-time capable control architectures for lateral vehicle guidance. His scientific contributions appear primarily in IEEE conferences and automotive engineering journals, with notable publications in IEEE Transactions on Intelligent Vehicles and IEEE Intelligent Transportation Systems Conference proceedings. While no specific awards are listed in the provided materials, his consistent publication record in top-tier venues demonstrates significant scholarly impact. Professor Keller actively supervises project work and final theses through the Control Engineering Laboratory, where students engage in hands-on development of control systems. His industry experience at ZF Group informs practical research directions focused on implementable solutions for automotive applications. The laboratory facilities at Haldener Str. 182 serve as the operational base for both teaching and research activities.