Find Academic Supervisors

• Graph Theory
• Combinatorics
• Algorithmic Problem Solving
• +2 more

Felix Joos leads the Theoretical Computer Science and Discrete Mathematics research group at Heidelberg University. His research examines graphs and hypergraphs through algorithmic, extremal, and structural lenses, incorporating probability theory methods. Currently serving as Vice Dean of the Faculty for Mathematics and Computer Science. Key research areas: Combinatorial optimization Random graph structures Discrete probability applications Structural graph theory Significant recognition includes: European Prize in Combinatorics (2023) Lauterschläger Prize for Young Researchers (2020) DFG Emmy Noether grant (2019) Prior academic positions include professorships at Hamburg University and postdoctoral research at University of Birmingham. Research contributions advance fundamental combinatorial methods with applications in computer science and discrete mathematics.

• Geospatial Data Management
• Distributed Computing
• Machine Learning
• +4 more

Prof. Werner Martin is a Professor of Big Geospatial Data Management at the Technical University of Munich (TUM), affiliated with the School of Engineering and Design and the Department of Aerospace and Geodesy. His research focuses on georeferenced data processing, distributed computing, quantum algorithms, and machine learning applications in geospatial contexts. Prof. Martin holds a doctorate from LMU Munich and has held academic and research positions at institutions including LMU Munich, Leibniz-University Hannover, the German Aerospace Center (DLR), and UniBW Munich. His work bridges theoretical advancements with practical applications in spatial data analysis, visualization, and high-performance computing. Awards ACM SIGSPATIAL GIS Certificate of Appreciation (2019) 1st place ACM SIGSPATIAL GIS Cup (2015) IPIN Best Paper Award (2014) His recent publications emphasize geospatial AI, quantum computing for data processing, and environmental monitoring systems. Collaborations with industry partners like DLR highlight his focus on real-world geospatial challenges.

James Lee MasseyView profile

Professor

• Coding Theory
• Cryptography
• Communications Engineering
• +4 more

James Lee Massey was a renowned academic in electrical engineering, coding theory, and cryptography. He held professorships at the University of Notre Dame (1962–1977), UCLA (1977–1980), and ETH Zurich (1980–1998), where he became a professor for Digital Techniques. His work revolutionized fields like convolutional coding (Berlekamp-Massey algorithm) and cryptography (IDEA and SAFER+ ciphers). Education: BSEE (maxima cum laude), University of Notre Dame (1956) MSEE and PhD, MIT (1960, 1962) Dr. Tech. honoris causa, Lund University (1990) Doctorate honoris causa, Technical University of Munich (2006) Research Interests: Massey’s research spanned coding theory, information theory, and cryptography. He emphasized mathematical foundations, linking convolutional codes to linear systems theory and developing threshold decoders. Later work focused on cryptographic algorithms like IDEA and SAFER+. His contributions to random access communications (collision channel without feedback) earned the IEEE Baker Prize. Awards: Shannon Award (1988) IEEE Alexander Graham Bell Medal (1992) Marconi Prize (1999) Inclusion in U.S. National Academy of Engineering and multiple international academies Advising & Grants: Advised notable students like Dan Costello (convolutional codes) and Peter Mathys (collision channels). Supported by grants from NASA/Goddard and industry collaborations. Labs/Teams: Co-founded Codex Corporation (1962) and collaborated with ETH Zurich’s communications lab. Pioneered secure communication principles with Jim Omura.

• Neuro-Oncology
• Brain Tumor Genetics
• Developmental Pathways in Cancer
• +3 more

Prof. Torsten Pietsch is a Professor at the University of Bonn's Department of Neuropathology, affiliated with the Universitätsklinikum Bonn. His research focuses on the neuropathology, genetics, and molecular biology of pediatric brain and liver tumors, particularly medulloblastoma, ependymoma, and hepatoblastoma. He is a leading expert in CNS tumor classification, contributing to WHO tumor classification editions since 2000 and the cIMPACTnow consortium. His work emphasizes developmental pathways in cancer, including SHH/WNT signaling in medulloblastoma and NF-κB activation in ependymomas. He has authored key studies on biomarker validation, tumor classification guidelines, and diagnostic methodologies. Prof. Pietsch's research integrates molecular, genetic, and immunobiological approaches to identify diagnostic/prognostic markers. Notable contributions include defining new tumor entities and advocating for standardized tissue preservation. His studies on CDKN2A deletions, immune infiltration in germinomas, and genetic alterations in WNT medulloblastoma highlight translational applications. Collaborations span international trials (e.g., HIT ependymoma cohorts, SIOP-Europe), emphasizing clinical impact. His work bridges basic science and clinical practice, influencing treatment protocols and diagnostic standards globally. Ongoing studies explore radiotherapy optimization, drug combinations (e.g., tonabersat/temozolomide), and novel therapeutic strategies for glioblastoma and medulloblastoma.

• Numerical Analysis
• Computational Fluid Dynamics
• Partial Differential Equations
• +3 more

Aleksey Sikstel is a part-time faculty member at RWTH Aachen University , holding the title of Vertr.-Prof. (Part-Time Lecturer). His research focuses on advanced numerical methods for hyperbolic conservation laws, including Discontinuous Galerkin schemes, stochastic Galerkin formulations, and error estimation techniques. Key research areas: Numerical Analysis, Computational Fluid Dynamics, and Applied Mathematics Primary affiliation: Faculty 10 Institutions at RWTH Aachen University Contact: aleksey.sikstel@rwth-aachen.de His work emphasizes coupling hyperbolic systems, entropy-stable discretizations, and adaptive grid methods. Recent publications analyze Baer-Nunziato-type models, multiresolution strategies, and boundary control for hyperbolic equations.

• Human-Computer Interaction
• Software Ergonomics
• Digital Health
• +5 more

Prof. Monique Janneck is a Full Professor of Software Ergonomics and Human-Machine Interaction at TH Lübeck. She concurrently serves as Scientific Director of the Institute for Interactive Systems (ISy), Deputy Head of the Competence Center CoSA, and Vice Dean for Research and Internationalization. Her academic journey includes a PhD in Computer Science (2006) from the University of Hamburg, followed by roles as Junior Professor for Human-Computer Interaction (2007–2011) and Research Assistant in Computer Science (2001–2007). Research Focus : Specializes in digital health solutions, usability engineering, and adaptive user interfaces. Her work spans gamification in education, online learning platforms, workplace ergonomics, and AI-driven systems. Recent projects include interventions for nursing staff mental health, recovery coaching apps, and career guidance platforms. Key Contributions : Developed tools like STUDYCoach for student engagement and Holidaily for post-vacation recovery behavior. Active in designing blended health coaching systems and digital platforms for small business entrepreneurs. Leading research on user-centered design methodologies and the impact of device choice on survey results. Leadership Roles : Oversee ISy's research initiatives and coordinate digital teaching strategies as former Presidential Representative for Digital Teaching (2018–2022). Involved in curriculum development for interactive systems and digital health management programs.

Torsten MützeView profile

Professor

• Discrete Mathematics
• Theoretical Computer Science
• Graph Theory
• +5 more

Torsten Mütze is a Professor at the Institute of Mathematics at the University of Kassel. Previously, he held positions as an Assistant Professor at the University of Warwick (2019–2024) and was affiliated with Charles University Prague's Department of Theoretical Computer Science and Mathematical Logic. His academic journey includes a postdoc under Martin Skutella at TU Berlin, research stays at Georgia Tech and ETH Zurich, and a software engineering role at Supercomputing Systems Zurich. Education: PhD in 2011 from ETH Zurich under Angelika Steger's supervision Master's and Bachelor's degrees in related fields Research Interests: Focuses on discrete mathematics and theoretical computer science, including combinatorial algorithms, graph theory, computational geometry, order theory, Ramsey theory, and combinatorial games. His work bridges foundational theory and real-world applications, particularly in algorithm design and combinatorial generation. Advising & Grants: Supervised students: Francesco Verciani, Nastaran Behrooznia, Namrata, Arturo Merino, Frieder Smolny, Karl Däubel, Jerri Nummenpalo, and Ondřej Mička Funded projects: DFG Heisenberg grant 522790373, Chancellor's International Scholarships, and EU funding Labs & Collaborations: Organizes workshops like 'Combinatorics, Algorithms and Geometry' and contributes to research networks such as the 'Combinatorial Optimization and Graph Algorithms' group. His work involves collaborations with institutions globally, including ETH Zurich, Georgia Tech, and TU Berlin.

Mahdi HomayouniView profile

Senior Lecturer

• Scheduling Optimization
• Operations Research
• Logistics and Supply Chain Management
• +4 more

Mahdi Homayouni is a Senior Lecturer in Industrial Engineering and Management at the School of Business, Social & Decision Sciences, Constructor University. His expertise lies in scheduling optimization, logistics, and operations research. He holds a PhD in Industrial and Systems Engineering from Universiti Putra Malaysia (2012), an MSc in the same field (2008), and a B.Eng. in Industrial Engineering (2003). His research focuses on advanced scheduling methodologies for manufacturing systems, maritime operations, and container terminals. He has developed algorithms such as hybrid genetic algorithms, particle swarm optimization, and biased random key genetic algorithms (BRKGA) to address complex problems like energy-efficient job shop scheduling, integrated production-transport systems, and port automation. His work emphasizes sustainability, resource optimization, and the application of metaheuristics to real-world logistical challenges. Dr. Homayouni has held academic positions at institutions including the University of Porto (FEP), Islamic Azad University, and served as a research assistant at INESC Technology and Science. His contributions span theoretical advancements in scheduling models and practical applications in supply chain management, with a strong emphasis on interdisciplinary solutions. His recent publications highlight innovations in digital twin technology for seaport sustainability, energy-efficient manufacturing systems, and multi-objective optimization in transportation logistics. He continues to explore cutting-edge applications of AI-driven algorithms to enhance operational efficiency in industrial and maritime sectors.

• Structural Reliability Engineering
• Power System Resilience
• Seismic Risk Assessment
• +3 more

Qiang Xie is a Professor in the Department of Electrical Engineering at Zhejiang University's College of Engineering. With an active research career spanning over two decades, Dr. Xie has established himself as a leading researcher in structural reliability engineering with significant contributions to power system resilience and seismic risk assessment. Dr. Xie's research interests center on structural reliability engineering with particular focus on power infrastructure resilience. His work bridges civil and electrical engineering domains, developing innovative frameworks for seismic risk analysis of electrical substations, post-earthquake power system restoration, and wind-related risk assessment for transmission systems. In recent years, he has expanded his research into medical imaging applications, particularly in gastrointestinal endoscopy assistance systems and ultrasound bone imaging. Analysis of Dr. Xie's recent publications (2021-2026) reveals a strategic expansion of research scope while maintaining core expertise in reliability engineering. The earliest works focused on wireless sensor networks and computer science applications, while the 2018-2021 period saw a strong emphasis on medical imaging and bioinformatics. Since 2022, there's been a pronounced return to power system resilience with increasingly sophisticated methodologies incorporating Bayesian networks, copula models, and multi-strategy frameworks. This evolution demonstrates both depth in core competencies and adaptability to emerging interdisciplinary opportunities. Multiple publications in Reliability Engineering & System Safety (6 papers 2022-2026) Contributions to medical imaging in IEEE Transactions and Frontiers journals Collaborative work with international researchers across engineering and medical domains Dr. Xie maintains active collaborations across multiple institutions, as evidenced by his diverse co-authorship patterns. His research demonstrates strong translational potential, particularly in critical infrastructure protection and medical diagnostic technologies. While specific grant information isn't available in the publication record, the consistent output and diverse funding sources implied by publication venues suggest sustained research support.

• Causal Inference
• Machine Learning
• Social Media Analysis
• +3 more

Prof. Drew Dimmery is the Professor of Data Science for the Common Good at the Hertie School's Data Science Lab. He holds a PhD in Politics from New York University (2016), with a focus on causal inference and machine learning. Prior to joining Hertie, he served as Scientific Coordinator at the University of Vienna’s Data Science Research Network (2021–2023) and worked on Facebook’s Core Data Science team (2016–2020), developing experimentation tools and methods. His research emphasizes methodological innovation in causal inference and machine learning, particularly applied to social media and internet studies. Key areas include experimental design, algorithmic transparency, and policy applications of data science. He has published in top-tier journals like ICML, KDD, and Science, and his work bridges computational methods with societal challenges such as electoral integrity, digital governance, and public welfare provision. Recent publications analyze the impact of social media platforms on elections, user behavior, and mental health, leveraging large-scale experimentation and causal analysis. His endowed professorship, supported by the Dieter Schwarz Foundation, includes scholarships for the Master of Data Science for Public Policy program, reflecting his commitment to applying data science for societal benefit.

Alex BlackView profile

Researcher

• Algebraic Combinatorics
• Geometric Combinatorics
• Optimization
• +3 more

Alex Black is currently a Hermann Weyl Instructor at ETH Zurich, focusing on algebraic and geometric combinatorics and optimization. He will join Bowdoin College as a tenure-track assistant professor in the mathematics department starting Fall 2025. His research emphasizes the simplex method and its applications in optimization and polytope theory. Black’s research explores the interplay between algebraic and geometric combinatorics, with a particular focus on optimization and the simplex method. His work addresses topics such as polytopes, matroid theory, and pivot rules, aiming to advance understanding in discrete and computational geometry. He investigates issues like exponential lower bounds for pivot rules, monotone paths on polytopes, and the structure of flag polymatroids. INFORMS 2022 George Nicholson Paper Competition Finalist for Small Shadows of Lattice Polytopes No advising roles or grants are explicitly mentioned in the provided information.

Stefan HeuslerView profile

Professor

• Physics Education
• Quantum Physics
• Digital Technologies in Teaching
• +3 more

Stefan Heusler is a Professor of Physics Education at the Westfälische Wilhelms-Universität Münster, within the Faculty of Mathematics and Natural Sciences. He holds a professorship at the Institute for Physics Education. His academic career includes a Habilitation in Physics Education (2012), a Doctorate (2004) from the University of Duisburg-Essen, and a diploma in Physics from Heidelberg University (1997). He has conducted research abroad, including at Kyoto University (1995–1996) and the University of Tokyo (1998). Teaching roles include leading seminars on quantum physics, research methodologies, and educational innovation. Research focuses on quantum education, digital tools in teaching, and climate-related education. He has co-authored numerous publications on quantum education, experimental setups, and educational technology. His work emphasizes low-cost experiments, mixed reality, and smartphone integration in teaching. Collaborations include projects like MiReQu (Mixed Reality Learning Environments). Awards: None explicitly mentioned. Labs/Teams: Involved with the Institute for Physics Education and contributed to the QuantumVisions Münster initiative.

• Control Theory
• Linear Systems
• Numerical Analysis
• +3 more

Jordan Jens is a Lecturer at the Institute of Mathematics , affiliated with the Faculty of Mathematics and Computer Science at University of Würzburg . He holds a PhD in Mathematics (2008) and a Diploma in Mathematics (2000) from the same university. Education PhD in Mathematics (2008), University of Würzburg Diploma in Mathematics (2000), University of Würzburg His research focuses on Control Theory and Numerical Analysis , particularly in the context of Linear Systems , Reachability Analysis , and Algorithm Design . Recent publications highlight his work on random linear systems over finite fields, optimal control of iterative solvers, and observer design for delayed systems. Publications between 2002 and 2016 reveal expertise in Dynamical Systems , Matrix Equations , and Nonlinear Control , with applications to numerical algorithms and system stability.

• Numerical Linear Algebra
• Differential-Algebraic Equations
• Control Theory
• +3 more

Prof. Tatjana Stykel is a Professor of Computational Mathematics at the University of Augsburg, affiliated with the Faculty of Mathematics, Natural Sciences, and Materials Engineering. She holds positions in the Institute of Mathematics and leads the Computational Mathematics research group. Her academic journey includes a PhD from Technische Universität Berlin (2002) and a Habilitation (2009), both in numerical mathematics. Prior to her current role, she led a junior research group at TU Berlin’s MATHEON Research Center and held visiting professorships at TU Berlin and Humboldt-Universität zu Berlin. Stykel’s research focuses on Numerical Linear Algebra (e.g., generalized eigenvalue problems, matrix equations), Differential-Algebraic Equations (numerical methods and stability), and Control Theory (descriptor systems, model reduction). She has pioneered energy-adaptive optimization methods and Riemannian geometry techniques for complex systems, including applications in quantum chemistry and electromagnetism. Her awards include the Richard von Mises Prize (2007), Leslie Fox Prize (2003), and multiple fellowships from the Pacific Institute for the Mathematical Sciences and Soros programs. She has led major projects like the EU-funded EU-MORNET (2014–2018) and contributed to BMBF networks in model reduction for coupled systems. Stykel teaches advanced numerical methods, including courses on differential equations, optimization, and model reduction. Her work emphasizes interdisciplinary collaboration, with partnerships in robotics, semiconductor technology, and fluid dynamics. She advises several students, including alumni who have become prominent in applied mathematics and engineering.

Sandesh Athni HiremathView profile

Researcher

• Stochastic Processes
• Partial Differential Equations (PDEs)
• Mathematical Modeling
• +5 more

Dr. Sandesh Athni Hiremath is a Researcher at the Department of Mechatronics in Mechanical Engineering and Vehicle Technology at RPTU Kaiserslautern-Landau, affiliated with the Chair of Mechatronics (MEC). He holds a PhD in Mathematics from TU Kaiserslautern (2015) and a Master's in Informatics from the same institution. His research focuses on stochastic processes, partial differential equations (PDEs), optimal control, computer vision, and multiscale mathematical modeling. He has professional experience as an algorithm developer at Valeo Schalter und Sensoren in Germany. His work spans interdisciplinary areas including mathematical biology (cancer invasion modeling), control systems, and autonomous driving technologies. Recent contributions include PDE-based depth estimation for fisheye cameras and resilience analysis in industrial control systems. His publications integrate theoretical frameworks with practical applications in robotics, computer vision, and biomedical systems. Research highlights include developing stochastic models of acid-mediated tumor invasion and exploring optimal control strategies in dynamic systems. He collaborates with institutions like TU Kaiserslautern and international conferences (IEEE, ICCSA). Current interests align with advancing multiscale modeling and real-world applications in mechatronics and vehicle technology.