Find Academic Supervisors

Anton KlimovskyView profile

Senior Lecturer

• Probability Theory
• Stochastic Processes
• Statistical Mechanics of Disordered Systems
• +7 more

Anton Klimovsky is a Senior Lecturer at the University of Würzburg since 2022, affiliated with the Applied Stochastics department. His career includes visiting professorships at the University of Stuttgart (2022) and the University of Bonn (2014), along with lecturing at the University of Duisburg-Essen (2013-2022). Education : Habilitation (2019), Ph.D. in Mathematics (2008, TU Berlin, advisor: Anton Bovier), M.Sc. in Applied Mathematics (2002, Kharkiv National University, advisor: Mariya Shcherbina). Klimovsky’s research focuses on stochastic models of complex systems , including statistical mechanics of disordered systems , range-free spin glasses , and stochastic processes on evolving networks . His work bridges high-level heuristic ideas from statistical physics (e.g., cavity method, renormalization group) with rigorous probabilistic techniques. The 15 most recent articles highlight his expertise in disordered systems , hierarchical structures , population genetics , and network dynamics . Key trends include analysis of phase transitions in branching Brownian motion, renormalization of Lambda-Cannings processes, and Gaussian fluctuation theory in random energy models. Scientific awards include the Marie Curie Intra-European Fellowship (2010-2012) DFG Ph.D. Fellowship (2003-2005) National Academy of Sciences of Ukraine Ph.D. Fellowship (2002-2003) He has held visiting positions at Leiden University , EURANDOM , and Technische Universität Berlin , and has taught courses on Stochastic Processes , Markov Chains , and Spin Glasses . His grants include DFG funding for stochastic processes on evolving networks (2019-2024) and collaborative projects on hierarchical self-organization (2020-2026).

• Edge Computing
• Internet of Things
• Vehicular Networks
• +5 more

Muhammad Bilal is an Associate Professor at Zhejiang University's School of Computer Science, Department of Computer Science and Technology. His research spans multiple cutting-edge domains in computer science and engineering, with a particular focus on edge computing, Internet of Things, and vehicular networks. His research interests include Edge Computing , Internet of Things , Vehicular Networks , Federated Learning , Digital Twins , and Cloud Computing . His work addresses critical challenges in resource allocation, latency optimization, privacy preservation, and intelligent decision-making in distributed computing environments. He has made significant contributions to developing novel frameworks for service caching, computation offloading, and secure data processing in next-generation networks. His recent publications reveal a strong trend toward integrating artificial intelligence with edge and cloud infrastructure, particularly focusing on privacy-preserving techniques and resource-efficient algorithms. His work spans applications from intelligent transportation systems to healthcare monitoring and meteorological services, demonstrating the versatility and real-world impact of his research. Dr. Bilal has established a prolific publication record with numerous high-impact papers in top-tier journals and conferences, reflecting his active engagement in the academic community. His collaborative approach is evident through extensive co-authorship networks, particularly with researchers in China, Pakistan, and internationally.

• Graph Theory
• Infinite Graphs
• Structural Graph Theory
• +5 more

Paul Knappe is a researcher at the University of Hamburg within the Faculty of Mathematics, Computer Science and Natural Sciences, specifically the Department of Mathematics. His work centers on structural graph theory, infinite graphs, and discrete mathematics. Supervised by Reinhard Diestel Recipient of a doctoral scholarship from the Studienstiftung des Deutschen Volkes Focus areas: tree-decompositions, edge-connectivity, tangle-tree duality, and local-global aspects in graphs His research includes groundbreaking contributions to the classification of typical infinitely edge-connected graphs via strong immersion, the extension of tangle-tree duality to infinite graphs, and new insights into cyclic structures in edge-connected graphs. He has published in journals like the Journal of Graph Theory and Journal of Combinatorial Theory, Series B , with recent work on Farey graphs and Cantor-Bernstein theorems in infinite graph settings. Paul actively disseminates his findings through open-access summaries and preprints, collaborating with scholars such as Max Pitz, Jan Kurkofka, and Raphael W. Jacobs. He maintains a personal website for project updates and correspondence.

Guillaume DucoffeView profile

Associate Professor

• Algorithmic Graph Theory
• Computation in Large Graphs
• Parameterized Algorithms
• +12 more

Guillaume Ducoffe is an Associate Professor at the Faculty of Mathematics and Informatics, University of Bucharest, Romania, and a Senior Research Scientist at the National Institute of Research and Development in Informatics (I.C.I.), Romania. He is also affiliated with a joint research team between ICI and the Research Institute of the University of Bucharest (I.C.U.B.). Previously, he was a PhD student at Université Côte d'Azur, France, under the supervision of David Coudert, within the COATI project-team at Inria Sophia Antipolis. PhD, Université Côte d'Azur, France (2016) Master's Thesis, MPRI-ENS Cachan (2013) His research centers on algorithmic graph theory , with emphasis on computation in large graphs , including parameterized algorithms for problems like Diameter and Maximum Matching. He investigates metric tree-likeness in real-life networks through Gromov hyperbolicity, which has implications for routing efficiency and congestion. His work extends to information propagation using game-theoretic models such as coloring and hedonic games, and to online targeting detection , where he develops theoretically sound algorithms to uncover sensitive attribute targeting on the web via reductions to PAC learning of k-juntas. He also explores combinatorial topics like proper connectivity and Randic indices with applications in cryptography and chemistry. The analysis of his recent publications reveals a strong trend in theoretical computer science , particularly in the design and complexity of graph algorithms, structural graph properties, and their applications in network science and privacy. His work bridges pure graph theory with practical concerns in data centers, web transparency, and social networks. Guillaume Ducoffe has made significant contributions to both journal and conference literature, publishing in venues such as Discrete Applied Mathematics , SIAM Journal on Discrete Mathematics , ACM SIGMETRICS , and USENIX Security . His research is highly interdisciplinary, combining insights from algorithms, game theory, and network analysis. He actively supervises and mentors students, though specific names are not listed in the provided materials. He has been involved in research grants, including a postdoc grant from I.C.U.B., and has collaborated with prominent researchers such as David Coudert, Nicolas Nisse, Augustin Chaintreau, and Roxana Geambasu. His teaching includes core courses such as Data Structures and Algorithms , Advanced Graph Algorithms , and Advanced Programming Techniques at the University of Bucharest. Guillaume Ducoffe is a key member of collaborative research initiatives, including the joint ICI-I.C.U.B. team and the former COATI project at Inria. His work continues to advance the theoretical foundations of graph algorithms while addressing pressing issues in web transparency and network design.

• Information Retrieval
• Search Engine Technologies
• Data Compression
• +4 more

Alistair Moffat is a prominent faculty member at the University of Melbourne's School of Computing and Information Systems, with an extensive publication record spanning over four decades from 1980 to the present. His career demonstrates sustained contributions to information retrieval, data compression, and evaluation metrics within the field of computer science. Moffat's primary research interests encompass: Information Retrieval and Search Engine Technologies Data Compression Algorithms and Indexing Techniques Development and Analysis of Evaluation Metrics Process Mining and Event Log Analysis User Modeling in Information Seeking Behavior Theoretical Foundations of Search Effectiveness His recent work (2023-2025) reveals a continued focus on refining search evaluation methodologies, with particular attention to user-oriented metrics, rank-biased quality measurement, and the relationship between query variations and experimental consistency. Moffat has also expanded into process mining applications, developing entropy-based metrics like Entropia for measuring log representativeness. His publications consistently appear in top-tier venues including SIGIR, ACM Transactions on Information Systems, and Information Processing & Management. Moffat maintains extensive research collaborations, most notably with Justin Zobel (70 joint publications), J. Shane Culpepper (35), and Matthias Petri (32), demonstrating a strong network within the information retrieval research community. His work bridges theoretical computer science with practical applications in search technology, medical information retrieval, and process analysis. As evidenced by his continuous publication output through 2025, Moffat remains an active and influential researcher in his fields of expertise, contributing both to foundational theories and practical implementations in information access systems.

Tobias MömkeView profile

Professor

• Algorithmic Optimization
• Theoretical Computer Science
• Resource-Aware Computing
• +4 more

Tobias Mömke is a Professor for Theoretical Computer Science at the University of Augsburg , Germany. His research focuses on algorithmic optimization for problems with limited resources , particularly in Traveling Salesman Problem (TSP) variants , approximation algorithms , and online computation . He leads the Resource Aware Algorithmics team. Fields of Interest : TSP, Approximation Algorithms, Online Algorithms, Graph Theory Advising : Mentors students like Michael Ruderer, Aida Roshany-Tabrizi, and Morteza Alimi. Scientific Contributions : His recent work includes path cover techniques for TSP variants, bridge lemmas in algorithm design, and normalizing graphs for edge coloring. He has developed linear-time and polynomial-time solutions for scheduling and flow problems. Awards : DFG Heisenberg Grant (2020) , DFG Sachbeihilfe (2020) Email : moemke@informatik.uni-augsburg.de

• Hardware Trojan Design
• Netlist Reverse Engineering
• Neuro Engineering
• +2 more

Alexander Hepp serves as a Lecturer at the Chair of Security in Information Technology, Technical University of Munich (TUM), where he contributes to both teaching and cutting-edge hardware security research. His current teaching responsibilities include C++ Lab, Embedded Systems and Security, and Strategic Management for Engineers, where he acts as primary lecturer for the latter course. His research centers on hardware trojan design/identification and netlist reverse engineering within the chair's broader security initiatives. His research portfolio demonstrates deep specialization in hardware security vulnerabilities, with emphasis on hardware trojan insertion/detection methodologies and reverse engineering countermeasures. Recent work explores neuro engineering applications and RISC-V-based security implementations, often leveraging open-source hardware frameworks. His publications reveal consistent innovation in hardware obfuscation techniques and netlist analysis tools, addressing critical gaps in pre-silicon security validation. His 12 publications from 2021-2024 show strong focus on hardware security conferences like DATE and DDECS, with recurring themes in trojan detection, reverse engineering challenges, and cryptographic hardware validation. The research trajectory indicates growing emphasis on practical countermeasures against physical attacks and standardized vulnerability assessment frameworks. Scientific Awards: Best Paper Award at DDECS 2022 for 'Hardware Obfuscation of Digital FIR Filters' No verifiable information exists regarding student advising or grant funding in available sources. He operates within Prof. Sigl's research ecosystem which actively pursues projects in fault attacks, IoT security, physical unclonable functions, and post-quantum cryptography implementations, with recent work emphasizing hardware reverse engineering challenges in advanced semiconductor designs.

Martin MiddendorfView profile

Professor

• Swarm Intelligence
• Bioinformatics
• Genome Rearrangement Analysis
• +7 more

Prof. Dr. Martin Middendorf is a faculty member at the Department of Computer Science , Faculty of Mathematics and Computer Science , Leipzig University , Germany. He leads the Swarm Intelligence and Complex Systems Group and focuses on interdisciplinary research at the intersection of computational methods and biological systems. Fields of Interest Swarm Intelligence Bioinformatics Genome Rearrangement Analysis Combinatorial Optimization Evolutionary Algorithms Task Allocation in Multi-Agent Systems His recent research emphasizes mitochondrial genome annotation , predator-prey dynamics in swarm systems , and metaheuristic algorithms for dynamic optimization . Key trends include de-Bruijn graph applications , pheromone-dependent movement modeling , and automated behavior tracking in social insects . Supervised Students Dr. Nicolas Wieseke Dr. Hoang Thanh Le Dr. Fatma Turna Tobias Jagla Carsten Seemann Prof. Middendorf's group develops tools like DeGeCI 1.1 for mitochondrial gene annotation and explores swarm-controlled emergence in ant clustering systems. They apply swarm intelligence principles to solve real-world problems in vehicle routing , sewer network design , and biomedical signal processing .

Matthew DicksonView profile

Researcher

• Probability Theory
• Stochastic Processes
• Random Graphs
• +2 more

Dr. Matthew Dickson is a postdoctoral researcher in the Department of Mathematics at Ludwig Maximilian University of Munich, affiliated with the Stochastics and Mathematical Finance Group. His research focuses on advanced probabilistic modeling within mathematical physics and finance. His primary research domains include: Probability Theory Stochastic Processes Random Graphs Mathematical Finance Statistical Mechanics Recent publications demonstrate expertise in large deviations analysis, spatial cycle models, and combinatorial partition theory, with applications spanning quantum systems and financial mathematics. No scientific awards were documented in the source material. Dr. Dickson leads the DFG SPP 2265 project "Critical behaviour of the weight-dependent random connection model" (2020-2023) and taught "Gibbsian Point Processes" (winter term 2022/2023) with M. Heydenreich. His research collaborations include S. Adams and Q. Vogel, though no graduate students are listed. As a core member of the Stochastics and Mathematical Finance Group, he advances theoretical frameworks for bosonic loop soups, random interlacements, and condensation phenomena in complex systems.

Peter MoertersView profile

Professor

• Probability Theory
• Random Graphs
• Large Deviations
• +3 more

Peter Moerters is a Professor of Applied Mathematics at the University of Cologne , specializing in probability theory and its applications. His research spans random graphs, large deviations, Brownian motion, stochastic processes in random media, and geometric measure theory. He has extensive collaborations and editorial service, including contributions to journals like Stochastic Processes and their Applications and Journal of Theoretical Probability . Research Interests : Probability theory, random graphs, large deviations, Brownian motion, stochastic processes in random media, and geometric measure theory. Notable Coauthors : Yuval Peres, Jochen Blath, Wolfgang König, and others. Publications : Recent works include studies on percolation phase transitions, competing growth processes, tangent graphs, and branching with selection and mutation. Editorial Service : Serves on the editorial boards of Journal of Theoretical Probability and Stochastic Processes and Applications .

Mario WolterView profile

Researcher

• Computational Chemistry
• Quantum Chemistry
• Theoretical Chemistry
• +3 more

Mario Wolter is a Researcher at the Institute of Physical and Theoretical Chemistry within the Faculty of Life Sciences at Braunschweig University of Technology. He has been working in Professor Christoph Jacob's research group since October 2014, contributing to various computational chemistry projects. He also serves on the Institute's Board since 2015. Bachelor of Science in Chemistry, TU Braunschweig (2005-2009) Master of Science in Chemistry, TU Braunschweig (2009-2010) PhD with thesis 'Charge Transfer in DNA - Insights from Simulations' (2013) Postdoctoral researcher at Karlsruhe Institute of Technology (2013-2014) Dr. Wolter's research focuses on computational and theoretical chemistry, particularly in quantum chemical methods, protein fragmentation schemes, vibrational spectroscopy, and DNA charge transfer phenomena. His work bridges theoretical approaches with practical applications in biochemistry and materials science. He has developed innovative computational methods for studying complex molecular systems, including specialized algorithms for protein partitioning and quantum-chemical calculations. His publication record shows a strong trajectory of research output with recent contributions spanning quantum chemical fragmentation methods, vibrational spectroscopy, biocatalysis, and energy transfer phenomena. His work demonstrates expertise in developing and applying computational techniques to solve complex problems in physical chemistry and biochemistry. LehrLeo-Award 2020 for the Computational Chemistry Research Lab Dr. Wolter has been actively involved in research projects related to quantum chemistry software development, molecular simulations, and theoretical approaches to understanding complex biochemical systems. His work often involves interdisciplinary collaboration across chemistry, physics, and biology domains. His research group focuses on developing computational methodologies for studying large biomolecular systems, with particular emphasis on making quantum chemical calculations feasible for proteins and other complex biological molecules through innovative fragmentation approaches.

• Bioinformatics
• High-Performance Computing
• Parallel Algorithms
• +3 more

Lukas Hübner is a Doctoral Researcher at the Karlsruhe Institute of Technology (KIT) and a Visiting Scientist at the Heidelberg Institute for Theoretical Studies (HITS) . He holds a B.Sc. in Molecular Biotechnology from Heidelberg University and an M.Sc. in Computer Science from KIT. His research focuses on integrating computational methods with biological data analysis, particularly in phylogenetic inference, high-performance computing, and parallel algorithm design. He explores fault-tolerant systems, MPI optimizations, and reproducibility in computational workflows. Key research interests include: Parallel algorithms for large-scale phylogenetic analysis Optimization of MPI-based distributed systems Reproducibility in high-performance computing Fault-tolerance mechanisms in parallel algorithms His work often bridges computer science and bioinformatics, addressing challenges in genetic data processing and algorithm scalability. Recent publications emphasize techniques like memoization for genealogical forests and zero-overhead C++ bindings for MPI. He has collaborated on tools like RAxML-NG and ReStore, advancing robust computational methods for phylogenetic studies.

• Graph Theory
• Combinatorics
• Theoretical Computer Science
• +3 more

Christian Elbracht is a Researcher in the Department of Mathematics within the Faculty of Mathematics, Informatics and Natural Sciences at the University of Hamburg. He is based in Geomatikum (Bundesstraße 55), Room 232, Hamburg, with office hours conducted online by appointment. His primary academic activities involve teaching exercise sessions for mathematics courses targeting computer science students and physicists. His research focuses intensely on advanced graph theory, particularly tangle theory, separation systems, and structural decompositions in both finite and infinite graphs. Key themes include tree structures, connectivity hierarchies, submodular systems, ubiquity conjectures, and combinatorial optimization. His work bridges theoretical mathematics with applications in clustering algorithms and data science, as evidenced by collaborations extending into machine learning domains. Christian's publication trends reveal a concentrated specialization in tangle-tree duality and structural graph theory since 2018, with significant contributions to abstract separation systems and infinite graph theory. His collaborative work frequently involves researchers like J. Kneip and M. Teegen, with publications appearing in journals such as the Journal of Combinatorial Theory and Advances in Combinatorics . While no scientific awards are publicly documented, his research output demonstrates consistent contributions to combinatorial theory. His teaching responsibilities include leading exercise sessions for foundational mathematics courses for computer science students (Mathematics I/II) and specialized topics like Graph Theory I and Optimization. Christian maintains active research collaborations across multiple institutions, particularly evident in his work on graph ubiquity theorems and clustering applications. His technical work centers on structural analysis of graphs, with implications for theoretical computer science and discrete mathematics.

• Algorithmic Game Theory
• Computational Social Choice
• Theoretical Computer Science
• +3 more

Themistoklis Melissourgos is a Lecturer (Assistant Professor) in the School of Computer Science and Electronic Engineering at the University of Essex. He is a member of the Artificial Intelligence research group and the Centre for Computational Finance and Economic Agents. Prior to joining Essex, he held postdoctoral positions at TU Munich in the Operations Research group under Prof. Andreas S. Schulz, and at the University of Liverpool. PhD in Computer Science, University of Liverpool (supervised by Prof. Paul Spirakis) BSc in Electrical and Computer Engineering, University of Patras His research lies at the intersection of Theoretical Computer Science and Economics , with a primary focus on Algorithmic Game Theory and Computational Social Choice . He investigates the computational complexity of problems in these domains and develops exact and approximation algorithms. His work often addresses fundamental questions in market equilibria, fair division, and strategic computation. The recent publications of Dr. Melissourgos span top-tier conferences such as FOCS , STOC , ICALP , AAAI , and AAMAS . A clear trend in his work is the establishment of strong inapproximability results for problems in computational economics and game theory, particularly within complexity classes like PPAD and PPA. His research on the Pure-Circuit problem and consensus halving has provided foundational hardness results. He also explores applications in computational finance, such as optimizing trading strategies with genetic algorithms. Scientific Service: Program Committees: AAMAS 2025, ECAI 2024/2025, SAGT 2022/2023/2025, IJCAI 2021-2024, AAAI 2020/2023-2025 Reviewer: For numerous top conferences (STOC, FOCS, SODA, etc.) and journals (JACM, SICOMP, etc.) Organizing: SAGT 2016, MFCS 2018; Co-organized seminars on Complexity of Total Search Problems and Fair Division at TU Munich Dr. Melissourgos has an active teaching record, having served as a Teaching Assistant and Instructor at the University of Liverpool for courses in algorithms, AI, and computational game theory. At the University of Essex, he is a Module Supervisor for courses in quantitative finance and financial engineering. He has not been awarded any specific scientific prizes mentioned in the text, and there is no information about research grants. He has not published a list of advisees, suggesting he may be early in his faculty career. He is actively involved in his research community and contributes significantly to the academic service of his field.

Van Bang LeView profile

Professor

• Graph Algorithms
• Computational Complexity
• Theoretical Computer Science
• +2 more

Van Bang Le serves as an Extraordinary Professor in Theoretical Computer Science at the Institute of Computer Science, University of Rostock. His academic profile reflects deep specialization in graph theory and computational complexity, with institutional affiliation clearly established through university contact details and course listings. His research focuses on fundamental problems in graph algorithms, particularly examining matching cuts, graph coloring, vertex deletion problems, and structural graph properties. Key contributions include complexity analyses of Strong Conflict-Free Vertex-Connection, polynomial kernelization for stable cutsets, and optimal leaf roots computation. His work demonstrates consistent theoretical rigor with publications spanning from 2020-2025. Teaching responsibilities include advanced courses in Logic and Predictability, Theoretical Computer Science I (Complexity and Formal Languages), Cryptography seminars, Operations Research, and Efficient Graph Algorithms. His course portfolio directly aligns with his research expertise in discrete structures and algorithmic complexity. Analysis of his 15 most recent publications reveals dominant research trajectories: (1) Matching cut problems across various graph classes (2022-2024), (2) Parameterized complexity in vertex deletion problems (2023-2024), and (3) Structural graph theory with emphasis on chordal graphs and cographs (2023). The publications exhibit strong theoretical consistency despite the anomalous medical-themed papers in the 2025 list which appear unrelated to his core computer science profile. Professional functions include membership on the Computer Science Examination Board (IN) and the IEF Library Commission, indicating active institutional service beyond research and teaching responsibilities.