Find Academic Supervisors

Bernhard J. BergerView profile

Lecturer

• Software Security
• Static Code Analysis
• Machine Learning
• +4 more

Bernhard J. Berger is a Lecturer in the Department of Computer Engineering at the Institute of Embedded Systems, Hamburg University of Technology (TUHH). His research focuses on software security, static code analysis, machine learning, optimization, and research data management. He has held significant roles such as Program Committee member for ICPC 2025 and MSR 2025, and has received awards including the Best Reviewer Award (ICPC 2023) and Best Engineering Paper Award (SCAM 2019). His work spans interdisciplinary applications including maritime systems security, GPU-accelerated AI, and evolutionary algorithms. Recent studies emphasize AI-driven security tools (e.g., ML-SAST) and domain-specific language approaches to optimization (EvoAl). He has contributed to over 30 peer-reviewed publications, with notable work in IEEE Transactions on Software Engineering and Science of Computer Programming. Berger collaborates closely with industry through DAAD review committees and serves on artifact evaluation boards for ISSTA and ARES conferences. Education: Doctoral Thesis (2022), Diploma in Computer Science (2007) Key Projects: ArchSec tool suite, Threat Modeling Frameworks, Bauhaus static analysis methodology Lab Affiliation: Embedded Systems Design Group His advisory roles include Deputy of TUHH's Election Verification Committee and Session Chair at IEEE Congress on Evolutionary Computation 2023. Current research trends integrate machine learning with static analysis for automated vulnerability detection, while also exploring explainable AI techniques for neural network optimization.

• Theoretical Computer Science
• Computational Geometry
• Algorithms
• +3 more

Günter Rote is a Professor in the Department of Computer Science at Freie Universität Berlin, specifically within the Theoretical Computer Science group (Arbeitsgruppe Theoretische Informatik). He holds a formal academic title of Professor Dr. and is affiliated with the Faculty of Mathematics and Computer Science. His research focuses on theoretical computer science, computational geometry, algorithms, and discrete mathematics. Key research interests include geometric algorithms, optimization problems (e.g., shortest paths, traveling salesman problems), and algorithm design for parallel computing systems. His work spans topics such as systolic arrays, convex hulls, and combinatorial optimization. Rote’s contributions include foundational studies on computational geometry problems, algorithmic complexity, and practical applications in energy equity and infrastructure design. Publications highlight contributions to solving extremal equations, polygon transformations, and the quadratic assignment problem. He has been active in academic leadership, mentoring students, and contributing to computational science communities. His email is rote@inf.fu-berlin.de, and his office is located at Takustraße 9 in Berlin.

Ruben MartinsView profile

Assistant Professor

• Constraint Programming
• Program Synthesis
• Formal Verification
• +3 more

Ruben Martins is an Assistant Professor at Carnegie Mellon University's School of Computer Science and serves as the program director of the Master of Science in Computer Science (MSCS) . His research focuses on the intersection of constraint programming, program synthesis, analysis, and verification, with recent work aiming to make formal methods tools more accessible through automated reasoning. Ruben earned his Ph.D. with honors from the Technical University of Lisbon, Portugal (2013) , followed by postdoctoral research at the University of Oxford (2014-2015) and UT Austin (2015-2017) . Research Interests : Ruben's work bridges constraint programming and program synthesis , with applications in software verification , optimization , and automated reasoning . He has developed award-winning tools like Open-WBO , a modular MaxSAT solver that has won gold medals in international competitions. His publications span top-tier venues such as POPL , PLDI , FSE , SAT , and CP , often addressing real-world challenges from program analysis to network security. Scientific Awards include: Distinguished Paper Award at PLDI 2018 Distinguished Paper Award at FSE 2021 Distinguished Paper Award at SAT 2022 Gold medals for Open-WBO in MaxSAT competitions Teaching & Advising : Ruben mentors Ph.D., Master’s, and undergraduate students in research projects related to program synthesis, formal methods, and constraint solving. He teaches courses such as Bug Catching: Automated Program Verification and Advanced Topics in Logic: Automated Reasoning and Satisfiability , emphasizing hands-on experience with tools like Why3. His advising spans topics from AI-driven program repair to network protocol verification , fostering collaboration across disciplines.

• Algorithms for Big Data
• Parallel Computing
• External-Memory Algorithms
• +5 more

Ulrich Meyer is a Professor at the Institute for Computer Science at Goethe University Frankfurt. He serves as a prominent researcher in algorithms for big data, with extensive contributions to parallel and external-memory graph algorithms. His work spans theoretical foundations and practical implementations for processing large-scale data sets. Spokesperson of the DFG priority program (SPP 1736) on Algorithms for Big Data in Germany SEA23 Symposium on Experimental Algorithms, Steering Committee Chair ALENEX23 Algorithm Engineering and Experiments, Program Committee Member Professor Meyer's research interests focus on the theoretical and experimental aspects of processing large data sets on advanced computational models. His work particularly emphasizes parallel and external-memory graph algorithms, with recent focus on efficient large-scale network generation according to various stochastic models. His research has produced significant contributions including the parallel Delta-Stepping algorithm (which received the ESA Test of Time Award in 2019) and the first BFS approach with sublinear I/O. He has also explored more specialized topics like energy-efficient sorting (with records in the JouleSort competition 2009/10 and the Germany Land of Ideas Award) and fragile computing (which earned him a best-paper award at ESA 2019). His recent publications demonstrate a strong focus on graph algorithms, network generation, and parallel computing techniques. The research trends show consistent advancement in scalable algorithms for massive graphs, with particular emphasis on efficient sampling methods, shortcutting techniques, and communication-free distributed approaches. His work bridges theoretical computer science with practical engineering considerations for real-world big data applications. ESA Test of Time Award 2019 for Parallel Delta-Stepping algorithm Records in the JouleSort competition 2009/10 Germany Land of Ideas Award Best-paper award at ESA 2019 for fragile computing research Professor Meyer has made substantial contributions to the academic community through his leadership in the DFG priority program on Algorithms for Big Data, which has fostered significant research collaborations across Germany. His extensive publication record in top venues demonstrates sustained research productivity and impact in the algorithms community. While specific grant details aren't provided in the text, his role as spokesperson for a major DFG priority program indicates substantial research funding and leadership responsibilities. His work appears to be conducted within collaborative research environments focused on algorithm engineering and experimental evaluation. His research appears to be conducted within the Institute for Computer Science at Goethe University Frankfurt, likely involving collaborations with other researchers in the Algorithms for Big Data priority program. The extensive list of co-authored publications suggests active participation in research teams focused on parallel algorithms, graph processing, and network generation.

Liji ShenView profile

Professor

• Operations Management
• Supply Chain Management
• Scheduling Optimization
• +7 more

Liji Shen is Professor of Operations Management and Chairholder at WHU – Otto Beisheim School of Management, Campus Vallendar, Germany. She is affiliated with the Supply Chain Management Group and leads research in scheduling, optimization, and sustainable manufacturing. Her academic journey includes a Ph.D. and Habilitation from Technische Universität Dresden, and she has held visiting scholar positions at institutions including École des Mines de Saint-Étienne and Huazhong University of Science and Technology. Ph.D. (Dr.rer.pol.), summa cum laude, Technische Universität Dresden (2009) Habilitation, Technische Universität Dresden (2015) Master of Business Administration (Dipl.-Kffr.), Technische Universität Dresden (2006) Liji Shen's research focuses on Operations Management , particularly scheduling optimization in manufacturing systems. Her work spans flexible job shops , parallel machine scheduling , energy-efficient production , and sequence-dependent setup times . She applies advanced techniques such as evolutionary algorithms , hybrid metaheuristics , and mathematical programming to solve complex industrial problems. Her recent publications emphasize sustainability through energy-aware scheduling and time-of-use pricing models. The 15 most recent publications highlight a consistent research trajectory in production scheduling , with increasing emphasis on energy efficiency , distributed manufacturing , and real-world constraints like eligibility and delivery times. Her work frequently appears in top journals such as European Journal of Operational Research , IEEE Transactions on Evolutionary Computation , and Computers & Operations Research , often in collaboration with leading researchers like Dauzère-Pérès, Mönch, and Buscher. Scientific Awards: European Journal of Operational Research, Best Paper Award (2021) DFG and TU Dresden, 'Support the Best' Prize for Outstanding Researchers (2013) Dr. Feldbausch-Prize for Best Dissertation, TU Dresden (2010) Scholarship for Young Researchers in Saxony (2006–2009) DAAD Prize for Best Foreign Students (2007) Best Master’s Thesis, German Operations Research Society (2007) Liji Shen has been an active advisor and researcher, leading projects in operations research and industrial optimization. Her editorial role on Operations Research Perspectives underscores her standing in the academic community. She has directed research labs and collaborated internationally, contributing to both theoretical advancements and practical applications in manufacturing and logistics. No specific grants are mentioned, but her sustained publication record and leadership roles indicate strong research support. She leads the Operations Management research group at WHU, focusing on algorithmic solutions for complex scheduling problems. Her team investigates energy-aware production, hybrid flow shops, and distributed systems, aiming to bridge the gap between theoretical models and industrial implementation. The lab collaborates with researchers across Europe and China, fostering a global research network in operations research and supply chain management.

Manuel PenschuckView profile

Research Fellow

• Algorithm Engineering
• Random Graphs
• Parallel and Distributed Computing
• +3 more

Manuel Penschuck is a Research Fellow at the Institute of Computer Science , Goethe University Frankfurt, Germany. His research focuses on algorithm engineering, graph theory, and scalable network generation, with emphasis on parallel computing, I/O-efficient algorithms, and random graph models. He actively contributes to conferences like ESA, SEA, and IPDPS, and has co-authored publications in top venues including LIPIcs , IEEE Transactions , and SIAM . His work includes engineering algorithms for non-linear preferential attachment , parallel shuffling , and hyperbolic graph generation . He has co-organized program committees for ESA, EuroPar, and SEA, and his collaborations span institutions such as MPI-INF, TU Darmstadt, and Australian National University. Recent publications highlight advances in uniform graph sampling, geometric network models, and distributed systems. His research integrates theoretical rigor with practical implementation, addressing challenges in big data and high-performance computing. He is a key contributor to the Networkit toolkit for large-scale network analysis.

Christian TominskiView profile

Professor

• Data Visualization
• Visual Analytics
• Human-Computer Interaction
• +5 more

Christian Tominski serves as an apl. Professor (non-tenured) at the University of Rostock, holding the außerplanmäßige Professur for Human-Data Interaction within the Institute for Visual and Analytic Computing. His academic work spans teaching in Visual Computing and Computer Science programs, with active research contributions in data visualization and visual analytics. His research focuses on multi-variate data visualization, time-series and geo-visualization, graph visualization, and coordinated multiple views. He investigates interaction techniques including interactive lenses, visual comparison, navigation, and guidance mechanisms, alongside computational aspects such as efficient algorithms and asynchronous processing for visualization systems. Recent work emphasizes task-driven approaches and analytic support for interactive exploration. Analysis of his publication trends reveals strong emphasis on visual analytics for complex data structures, particularly in process mining and multivariate graphs. His work consistently explores guidance frameworks, progressive computation models, and novel interaction paradigms for large high-resolution displays, bridging theoretical foundations with practical applications in visual data analysis. Tominski holds professional roles as a member of the Faculty Council of IEF and the System Technical Group of Computer Science Institutes at the University of Rostock. He actively participates in the Informatik-Forum Rostock (INFO.RO), contributing to the regional computer science community through collaborative initiatives and knowledge sharing.

Rolf WankaView profile

Professor

• Algorithms
• Combinatorial Optimization
• Swarm Intelligence
• +3 more

Prof. Dr. Rolf Wanka is a Professor at the Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), specializing in efficient algorithms and combinatorial optimization. His research focuses on swarm intelligence, discrete optimization algorithms, and scheduling problems, particularly in timetabling and robotics applications. Education : Sc.D. (Dr. rer. nat.) in Computer Science His work includes theoretical and experimental analyses of particle swarm optimization (PSO) algorithms, addressing runtime complexity, stagnation behavior, and convergence properties. He has developed novel heuristics for timetabling and sorting problems, with applications in multi-robot systems and medical imaging. Notable collaborations include studies on Markov chain-based PSO and fairness in academic scheduling. Key trends in his recent publications span swarm intelligence , discrete optimization , and scheduling heuristics , with a focus on robust timetabling , runtime analysis , and stochastic algorithm behavior . While no explicit scientific awards are listed, his mentorship in the Max Weber-Programm highlights his advisory role in academia. His publications demonstrate interdisciplinary applications of algorithms in robotics , medical imaging , and parallel computing , leveraging both theoretical rigor and practical experimentation. The full description below provides exhaustive details on his academic contributions and affiliations.

Matthias BeckerView profile

Professor

• Human-Computer Interaction
• Simulation and Modeling
• Distributed Systems
• +6 more

Matthias Becker is a Professor at the Institute for Practical Computer Science within the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover, where he has been a core member of the Human-Computer Interaction group since 2019. He serves as Internship Coordinator for Computer Science and Computer Engineering and holds key roles in the Computer Science Examination Board and Selection Committee, actively shaping academic governance and student development. His academic journey began with PhD studies at the University of Bremen (1996-2000) supported by a DFG grant, followed by a postdoctoral permanent position at Leibniz University Hannover (2000-2019), an Associated Assistant Professor role at École des Mines de Nantes (2000), and a Habilitation in Computer Science in 2013. This foundation enabled his transition to a full professorship in 2019. Becker's research spans Human-Computer Interaction, Simulation and Modeling, and Bio-inspired Computing, with applications in agriculture, renewable energy, and manufacturing. His work integrates distributed systems, optimization algorithms, and wireless sensor networks to solve complex real-world problems, such as greenhouse monitoring, wind farm logistics, and tire noise reduction. Recent publications reveal a strategic focus on practical validation of simulation models and cross-domain applications of nature-inspired algorithms. His 15 most recent publications (2018-2024) demonstrate consistent innovation in applying simulation techniques to offshore wind farm installation, agricultural pest management, and sports science. These works emphasize real-world validation, collaborative problem-solving, and the development of domain-specific optimization frameworks that bridge theoretical algorithms and industrial implementation. As Internship Coordinator, Becker facilitates critical industry-academia connections for students, while his examination board responsibilities ensure rigorous academic standards. His leadership in the Human-Computer Interaction group drives research on interactive systems for agriculture, energy, and health, with particular emphasis on user-centered design in complex operational environments like wind farm logistics and greenhouse automation.

• Theoretical Computer Science
• Algorithm Engineering
• Parallel Computing
• +3 more

Prof. Dr. Peter Sanders is a full professor in Theoretical Computer Science at the Karlsruhe Institute of Technology (KIT), leading the Algorithm Engineering group. His academic career includes a doctoral degree from Karlsruhe University and research stints at institutions like the Max Planck Institute for Informatics. He specializes in algorithm theory and engineering, focusing on parallel computing, large-scale data processing, and graph partitioning. His research bridges theoretical foundations with practical implementations, emphasizing real-world applications in optimization, route planning, and distributed systems. Education: Ph.D. in Computer Science, Karlsruhe University (1996) Bachelor/Master studies at Karlsruhe University (1988-1996) Research Interests: Algorithm design and analysis Parallel and distributed algorithms Graph algorithms and partitioning Algorithm engineering for big data High-performance computing Publications: Over 250 papers, emphasizing parallel algorithms, distributed systems, and graph theory. Recent work includes scalable SAT solving, hypergraph partitioning, and distributed string sorting. His contributions have advanced practical applications in route planning, load balancing, and large dataset processing. Awards: Recipient of the prestigious Leibniz Prize (DFG) and Baden-Württemberg State Research Prize. He coordinated the DFG Priority Program on Algorithm Engineering and is an active reviewer for major funding bodies. Consulting: Engages with companies like SAP and Google, focusing on optimization, route planning, and database algorithms. Leads projects on algorithm scalability and real-world problem-solving. Labs/Teams: Heads the Algorithm Engineering group at KIT, fostering collaborations in distributed computing and algorithmic research.

Thorsten KochView profile

Professor

• Mathematical Optimization
• High-Performance Computing
• Artificial Intelligence
• +4 more

Thorsten Koch is a Professor for Software and Algorithms for Discrete Optimization at Technische Universität Berlin , with multiple leadership roles including Head of the Applied Algorithmic Intelligence Methods (A²IM) , Digital Data and Information for Society, Science, and Culture (D²IS²C) , Kooperativer Bibliotheksverbund Berlin-Brandenburg (KOBV) , and Forschungs- und Kompetenzzentrum Digitalisierung Berlin (digiS) . Based at Zuse Institute Berlin and affiliated with TU Berlin's Institute for Mathematics, he focuses on integrating mathematical optimization with high-performance computing and artificial intelligence to solve complex real-world problems. Research Pillars : Mathematical optimization algorithms Quantum computing applications AI/ML integration in decision systems Energy systems optimization Scientific software development Leadership Roles : Head of Applied Algorithmic Intelligence Methods (A²IM) Head of Digital Data & Information for Society, Science, and Culture (D²IS²C) Head of Kooperativer Bibliotheksverbund Berlin-Brandenburg (KOBV) Head of Forschungs- und Kompetenzzentrum Digitalisierung Berlin (digiS) Key Collaborations : Working with IBM Quantum on quantum optimization Collaborating across institutions for energy system modeling Developing open-source optimization tools like SCIP Contributing to digital library infrastructure Recent Research Trends : Quantum optimization benchmarking Machine learning-aided optimization Multi-objective decision frameworks Energy infrastructure optimization Adaptive algorithm design CO2 network modeling Impact : Advancing hybrid optimization methods Developing open-source tools for scientific computing Building digital infrastructures for libraries and research Exploring quantum-classical algorithm synergies

Rainer KolischView profile

Professor

• Airport Operations Management
• Health Care Operations Management
• Project Management and Scheduling
• +2 more

Rainer Kolisch is a Professor of Operations Management at the TUM School of Management, Technical University of Munich , where he has held a chair since 2002. He currently serves as Head of the Operations & Technology Department (since 2024) and previously as Dean of the QTEM Masters Network (2016–present) and Vice Dean of International Affairs (2007–2020). His career includes academic roles at Technical Universities of Dresden (Full Professor, 2002) and Darmstadt (Associate Professor, 1999–2002). Affiliations: TUM School of Management, Technical University of Munich Editorial Roles: Editor-in-Chief of OR Spectrum (2014–2020), Member of editorial boards for journals like International Journal of Production Research Research Interests focus on Airport Operations Management , Health Care Operations Management , Project Management and Scheduling , and Engineer-to-Order Manufacturing . His work addresses dynamic scheduling, resource allocation, and robust optimization in transportation and healthcare systems, with recent studies on electric vehicle charging networks and agile project management. Scientific Awards include: Best Teaching Award (2022) Excellence in Reviewing (2022) OMEGA Best Paper Award (2021) Handelsblatt Research Recognition (2005) DFG Habilitation Fellowship Advising spans numerous PhD and Master’s students , including Christopher Bersch, Robert Brachmann, and Giacomo Dall'Olio. His grants likely include DFG funding, though specifics are not detailed here.

Guillermo Payá VayáView profile

Professor

• Embedded Systems
• Processor Architecture
• FPGA Design
• +5 more

Prof. Dr.-Ing. Guillermo Payá Vayá leads the Chair for Chip Design for Embedded Computing at Technical University of Braunschweig's Faculty of Electrical Engineering, Information Technology, and Physics. His research focuses on processor architecture design, FPGA/ASIC implementations, and optimization techniques for embedded systems, particularly in high-performance, low-power, and radiation-hardened computing domains. Primary research interests include: Application-Specific Instruction Set Processors (ASIPs) and compiler co-design Radiation effects characterization and fault-tolerant hardware Ultra-low-power processor architectures for embedded AI Hardware acceleration of neural networks and computer vision algorithms Memory subsystem optimization and parallel computing techniques Recent publications demonstrate strong emphasis on radiation-hardened electronics (35% of recent works), AI accelerator design (27%), and ultra-low-power systems (20%), with growing interest in biomedical applications. Experimental validation through FPGA prototyping and semiconductor testing is a consistent methodology across research domains. Leads research team investigating: Radiation-tolerant FPGA architectures (Trumann, Weide-Zaage) Vector processor optimization (Gesper, Thieu) Nano-scale controller design (Weißbrich) AI-hardware co-design (Kautz, Beyer)

• Organic Computing
• Evolutionary Algorithms
• Learning Classifier Systems
• +6 more

Professor Jörg Hähner holds the Chair of Organic Computing at the University of Augsburg's Faculty of Applied Computer Science within the Institute of Computer Science. He leads a research team focused on evolutionary computation, self-organizing systems, and intelligent computing approaches. His educational background includes computer science studies at TU Darmstadt. His academic career progression shows steady advancement in the field of organic and self-organizing computing systems. Prof. Hähner's research spans multiple interconnected domains in computational intelligence. His primary focus is on Organic Computing, which involves developing systems that can adapt and self-organize in complex environments. Within this framework, he has made significant contributions to Evolutionary Algorithms, particularly Cartesian Genetic Programming and Learning Classifier Systems. His work explores how these techniques can be applied to real-world problems such as predictive maintenance, energy systems optimization, and industrial automation. The research demonstrates a strong emphasis on both theoretical foundations and practical applications of self-adaptive systems. An analysis of his recent publications reveals a strong concentration on evolutionary computation techniques, particularly Cartesian Genetic Programming variants and Learning Classifier Systems. His research group has been actively developing frameworks like CRust_GP and GRAHF to advance modular construction of evolutionary algorithms. There's a clear trend toward applying these techniques to industrial problems including predictive maintenance, resource allocation in networks, and energy management systems. The publications show consistent exploration of fundamental questions about algorithm behavior while maintaining strong connections to practical applications. Prof. Hähner leads an active research group with numerous PhD students and collaborators, including Karen Poloczek, Henning Cui, Victor Gerling, Dr. Michael Heider, Marco Hüller, Neele Kemper, Helena Stegherr, Jonathan Wurth, and Roman Sraj. His team regularly publishes in top-tier conferences and journals in evolutionary computation, intelligent systems, and industrial applications. The Organic Computing research group maintains a strong presence in both theoretical and applied research, with projects spanning from foundational algorithm development to industrial applications in manufacturing, energy systems, and network optimization. The group's work demonstrates a cohesive research vision centered on creating adaptive, self-organizing computational systems that can operate effectively in complex real-world environments.

Paul MannsView profile

Assistant Professor

• Mathematical Optimization
• PDE-Constrained Optimization
• Integer Programming
• +1 more

Paul Manns is an Assistant Professor of Optimization at TU Dortmund University's Department of Mathematics, appointed in 2021. His research specializes in mathematical optimization involving partial differential equations and integer constraints, with emphasis on regularization techniques and trust-region algorithms. Education includes: Ph.D. in Mathematics, TU Braunschweig (2019) Computational Engineering studies, TU Darmstadt Prior research experience includes positions at Heidelberg University, TU Braunschweig, and Argonne National Laboratory (USA), including a James H Wilkinson Fellowship. Recent publications develop novel methods for mixed-integer control problems, domain decomposition, and convergence analysis in non-convex optimization spaces.