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Thomas SpeckView profile

Professor

• Biomimetics
• Biomechanics
• Plant Development
• +2 more

Prof. Dr. Thomas Speck is a Full Professor of Botany (Functional Morphology and Biomimetics) at Albert-Ludwigs-Universität Freiburg. He serves as Principal Investigator for Research Areas B, C, and D, and Coordinator of the Demonstrator Line within the Cluster of Excellence livMatS. As Director of the Botanical Garden, he combines academic leadership with institutional management. His research focuses on biomimetic applications derived from plant biomechanics, including material science, robotics, and sustainable technologies. Key projects involve developing bio-inspired actuators, adaptive materials, and energy-harvesting systems. Speck also explores plant-host interactions (e.g., mistletoe) and integrates biomimetic principles into education and architecture. Recent work includes studies on plant-inspired soft robots, hygromorphic materials, and biohybrid systems for reforestation. His interdisciplinary approach bridges biology, engineering, and design, with applications in healthcare (e.g., speaking valves), renewable energy, and urban sustainability. Education: Advanced academic training in botany and biomechanics. Grants: Cluster of Excellence livMatS funding and DFG projects. Supervised over 15 doctoral and postdoctoral researchers, contributing to 100+ publications. Laboratory facilities include the Botanical Garden and IDEASfactory@FIT for prototyping biomimetic solutions.

Armin NurkanovićView profile

Professor

• Optimal Control
• Numerical Methods
• Hybrid Dynamical Systems
• +4 more

Dr. Armin Nurkanović is an interim professor at the Technical University of Braunschweig's Department of Mathematical Optimization, where he teaches courses on dynamic optimization and numerical methods. Previously, he completed his PhD at the University of Freiburg under Prof. Moritz Diehl, focusing on optimal control of nonsmooth dynamical systems. His research emphasizes numerical methods for hybrid systems, real-time optimization, and applications in robotics and renewable energy systems. He has received the IEEE Control Systems Letters Outstanding Paper Award (2022) and was a finalist for the 2024 European Systems & Control PhD Thesis Award. Education: Bachelor's in Electrical Engineering (University of Tuzla, 2015) Master's in Electrical Engineering and Information Technology (Technical University of Munich, 2018) PhD in Control (University of Freiburg, 2023) Research Interests: Optimal control of hybrid and nonsmooth systems (e.g., Filippov systems, switched systems) Real-time optimization for model predictive control (MPC) Robust control theory and stochastic optimization Applications in robotics and renewable energy systems Teaching & Software: Developed open-source tools nosnoc and nosnoc_py for optimal control Teaching courses on numerical optimization and optimal control at TU Braunschweig Collaborations & Students: Open to academic and industry collaborations Supervises Bachelor's/Master's theses in mathematics, engineering, and computer science

• Applied Mathematics
• Computational Methods
• Control Theory
• +5 more

Sara Grundel is a leading researcher at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg, Germany. Her work focuses on computational methods in systems and control theory, particularly in model order reduction, gas network simulation, and optimization of energy systems. Education: Diplom in Mathematics, ETH Zurich (2005) PhD in Mathematics, Courant Institute of Mathematical Sciences, New York University (2011) Research Interests: Sara’s research encompasses mathematical control theory, stability analysis, and numerical methods for differential-algebraic equations. She applies these techniques to gas and energy networks, epidemic modeling, and multi-agent systems. Her interdisciplinary work bridges computational mathematics with real-world engineering and public health challenges. Recent Publications: Her 15 most recent articles (2024–2012) demonstrate expertise in parametrized PDEs, model reduction for coupled systems, and control strategies for SARS-CoV-2 containment. Key subtopics include adaptive meshing, stability-preserving algorithms, and optimization of nonlinear network dynamics. Scientific Contributions: Developed clustering-based model reduction techniques for networked systems Investigated hyperbolic discretization methods using Riemann invariants Advanced polynomial root radius optimization with affine constraints Collaborations: Sara frequently collaborates with researchers like Peter Benner and Martin Gersen on energy grid simulations and control theory. She participates in international conferences (GAMM, IEEE CDC, MTNS) and contributes to edited volumes in applied mathematics.

Jatinder SinghView profile

Professor

• Accountability in AI Systems
• Responsible AI Development
• Data Governance and Stewardship
• +7 more

Jatinder Singh is a Professor at the RC Trust and Principal Research Associate (equivalent to Research Professor) at the Department of Computer Science & Technology, University of Cambridge. He is primarily affiliated with the University of Duisburg-Essen, Germany, where he leads the Compliant and Accountable Systems research group within the Law department. His work operates at the critical intersection of computer science, legal frameworks, and societal impact, focusing on practical implementations that align technology with regulatory requirements while addressing user and community concerns. Research interests center on accountability mechanisms for AI systems, responsible development practices, data governance, and privacy/security in emerging technologies. He examines governance, agency, trustworthiness, and transparency gaps in algorithmic systems through interdisciplinary socio-technical lenses. Current work addresses bias in LLMs, stakeholder participation frameworks, and human rights implications in domains like healthcare, maritime enforcement, and consumer IoT, emphasizing contextual awareness and real-world applicability. His 15 most recent publications (2025-2024) reveal dominant trends in AI transparency, fairness proxy development, and legal-compliance engineering. Key focus areas include stakeholder involvement in AI governance, bias mitigation in language models, data justice applications for vulnerable populations, and operationalizing human-centered AI in clinical settings. The work consistently bridges technical implementation with regulatory frameworks like the EU Cyber Resilience Act and GDPR. Scientific Awards: No awards or fellowships were mentioned in the provided text. Advising and Grants: The text does not specify PhD/Master's students or grant details. As leader of an active research group publishing high-impact work on EU regulations and human rights, he likely directs funded projects and mentors early-career researchers, though concrete evidence is absent in the source material. His position suggests involvement in interdisciplinary grant consortia addressing socio-technical challenges. Labs and Teams: Singh leads the Compliant and Accountable Systems research group at University of Duisburg-Essen, which collaborates across university-wide clusters including Artificial Intelligence and Society, Human-AI Interaction, Trustworthy Human Language Technologies, and Verification of Machine Learning. The group develops frameworks for legal compliance in AI, focusing on demonstrable accountability through tools for transparency, bias auditing, and stakeholder engagement in real-world deployments.

Anke WeidlichView profile

Professor

• Sustainable Energy Systems
• Electricity Markets
• Grid Integration
• +4 more

Prof. Dr. Anke Weidlich serves as Professor of Control and Integration of Grids at the Institute for Sustainable Technologies (INATECH) of the University of Freiburg, leading research on holistic sustainable energy systems that balance economic, social, and ecological dimensions. Her work addresses the critical interplay between electricity markets, grid infrastructure, and cross-sectoral energy coordination. Her research spans: Sustainable Energy Transformation: Pathways and infrastructure requirements for transitioning to renewable-based systems Electricity Markets & System Integration: Coordination of technologies across markets for efficient energy delivery Flexibility Modeling: Quantifying and harnessing flexibility needs amid rising renewable penetration Network Analysis: European grid dynamics in future energy scenarios Multi-energy Systems: Synergies between electricity, heat, and mobility sectors Current projects include GrECCo (Grid-Sensitive Energy Community Coordination), Formal Modeling of Flexibility in Multi-Scale Multimodal Energy Systems, CO2Map (electricity CO2 intensity tracking), and ASSUME (agent-based market simulation). These initiatives demonstrate her focus on practical solutions for energy system integration and decarbonization. Her contributions have been recognized through: SAP Top Talent Program high-potential designation BMBF Career Promotion Programme fellowship DAAD research scholarship for US collaboration Heinrich Böll Foundation academic support Freiburg–Penn State Virtual Classroom Award Prof. Weidlich teaches Energy System Operations, Optimization for Energy Systems, Forecasting for Energy Systems, Energy System Modeling with Python, and Sustainable Energy Systems courses, preparing next-generation energy specialists through technical and systems-thinking approaches.

• Decision Making
• Cognitive Psychology
• Judgment and Decision Making
• +5 more

Christin Schulze serves as Senior Research Scientist at the Max Planck Institute for Human Development and Adjunct Associate Professor at The Arctic University of Norway since 2019. Her work bridges cognitive psychology and decision science, focusing on how humans develop and execute choices under uncertainty across individual and social contexts. Education Ph.D. Psychology, University of New South Wales (2015) M.Sc. Psychology (Dipl. Psych.), Friedrich-Schiller University Jena (2011) Research Focus : Schulze leads the “Development of Decision Making” research area within the Adaptive Rationality group. Her investigations span experience-based decisions under uncertainty , childhood development of decision strategies , cognitive modeling of judgment , and social/group decision dynamics . She employs experimental paradigms and computational models to dissect how environmental structure, cognitive constraints, and social interactions shape choices from infancy through adulthood. Publication Trends : Her 2015-2021 corpus reveals consistent exploration of probability matching phenomena, social sampling mechanisms, and description-experience gaps. Key contributions demonstrate how group contexts eliminate individual decision biases (Schulze & Newell, 2016) and how bounded rationality governs social information acquisition (Schulze et al., 2021), bridging cognitive, developmental, and social psychology. Scientific Awards Advising & Grants : While specific students and funding sources aren’t detailed in available materials, her leadership of a Max Planck research area implies significant mentorship responsibilities and grant management for decision-science projects. Research Infrastructure : Schulze heads the “Development of Decision Making” unit within the Adaptive Rationality department at Max Planck, directing a team investigating cognitive architectures of choice through behavioral experiments and mathematical modeling.

• Computer Graphics
• Augmented Reality
• 3D Modeling and Reconstruction
• +5 more

Kwan H. Lee is a prominent researcher in computer graphics and augmented reality, affiliated with the University of Alberta in Canada. With a publication record spanning over three decades (1990-2020), he has established himself as a leading figure in visual computing research with 56 documented publications. His research interests focus on Computer Graphics , Augmented Reality , 3D Modeling and Reconstruction , Computer Vision , and Cultural Heritage Computing . Dr. Lee's work demonstrates particular expertise in material appearance modeling, projection mapping techniques, and spatial augmented reality applications. His research has evolved from foundational work in manufacturing systems to cutting-edge applications in cultural heritage preservation and industrial visualization. Analysis of his recent publications (2015-2020) reveals a strong emphasis on practical applications of augmented reality in construction, museum exhibitions, and cultural heritage preservation. His work consistently bridges theoretical computer graphics concepts with real-world implementations, particularly in projection mapping systems and 3D reconstruction techniques. The publications show increasing focus on industrial applications and cultural heritage preservation in his later career. Dr. Lee has collaborated extensively with researchers from Korean institutions, suggesting strong international connections. His co-author network includes Yong Yi Lee, Jong Hun Lee, Min Ki Park, and other frequent collaborators who appear across multiple publications spanning more than a decade.

Matthias AlthoffView profile

Associate Professor

• Cyber-Physical Systems
• Formal Verification
• Autonomous Vehicles
• +5 more

Prof. Dr. Matthias Althoff is an Associate Professor of Cyber-Physical Systems at the Technical University of Munich (TUM), leading the Chair of Cyber-Physical Systems within the TUM School of Computation, Information and Technology. His research focuses on formal safety verification, model-based design, and reachability analysis for systems such as autonomous vehicles, robotics, and power grids. Education: He earned his diploma in Mechatronics and Information Technology (2005) and PhD (2010, summa cum laude) from TUM. He held postdoctoral positions at Carnegie Mellon University (2010–2012) and served as a junior professor at TU Ilmenau (2012–2013) before joining TUM as a full professor in 2013, becoming an associate professor in 2019. Research Interests: His work spans cyber-physical systems, formal methods for safety assurance, autonomous vehicles, modular robotics, and smart grid control. He develops tools like CommonRoad and CORA for scenario-based testing and reachability analysis. Awards: He has received the IEEE/ACM William J. McCalla ICCAD Best Paper Award (2012) and the Best Poster Award at the IEEE Intelligent Vehicles Symposium (2009). Labs/Projects: Leads the Cyber-Physical Systems group, collaborating on projects such as the Scenario Factory for automated vehicle testing and CommonPower for safe smart grid control. He also co-founded startups RobCo and aiina .

Rüdiger von Eisenhart-RotheView profile

Professor

• Regenerative Medicine
• Osteoarthritis Research
• Osteo-Oncology
• +7 more

Prof. Dr. Rüdiger von Eisenhart-Rothe is a full Professor and Chair of Orthopedics at the Technische Universität München (TUM), leading the Department of Orthopedics and Sports Orthopedics at the Klinikum rechts der Isar. His research focuses on regenerative medicine, osteo-oncology, endoprosthetics, and the application of machine learning in surgical planning. He completed his medical studies at LMU Munich and business administration at the University of Hagen, followed by a habilitation in orthopedics at Frankfurt’s Friedrichsheim Hospital. Notably, he received the Perthes Prize twice (2003, 2010) for contributions to shoulder and elbow surgery. His work integrates advanced imaging techniques, virtual planning, and biomaterial research to address challenges in joint replacement, infection control, and sarcoma management. Recent projects emphasize AI-driven diagnostic tools and personalized surgical approaches. Prof. von Eisenhart-Rothe collaborates with interdisciplinary teams to advance clinical outcomes in orthopedic surgery, particularly in knee and hip arthroplasty. Awarded the Perthes Prize twice, his contributions span academic leadership, clinical innovation, and translational research at TUM’s School of Medicine and Health. Current initiatives include optimizing prosthetic alignment via 3D modeling and evaluating synovial biomarkers for infection diagnosis.

• Bio-based Materials
• Sustainable Processes
• Fiber Technology
• +3 more

Prof. Wenwen Fang is a Professor at TUM Campus Straubing, Technical University of Munich, specializing in particle and fiber technology for bio-based materials. Her research focuses on sustainable conversion of bio-based polymers into high-performance materials. She holds a PhD in materials science from Aalto University (2018) and completed postdoctoral research at the University of Freiburg. Prior to joining TUM in 2024, she worked at Aalto University advancing the Ioncell® fiber spinning technology. Her work emphasizes eco-friendly processes for renewable feedstocks and waste utilization. Education: Bachelor/Master: Chemical Engineering at Åbo Akademi University (Finland) PhD in Materials Science: Aalto University (2018) Research interests include: Extraction/isolation of bio-based polymers (cellulose, proteins) Development of sustainable fiber production methods Molecular interaction control for material property optimization Her publications highlight advancements in UV-sensitive fibers, keratin waste upcycling, and biomimetic materials. The 2024 patent on UV-sensitive bio-based textiles exemplifies her innovation in functional materials. She leads interdisciplinary projects bridging chemistry, material science, and engineering. Labs/Teams: Core contributor to the Ioncell® technology development team at Aalto University, now advancing bio-based materials research at TUM.

• 6G Networks
• Telemedicine
• Medical Robotics
• +3 more

Nicolai Kröger is a researcher at the Chair of Communication Networks (Prof. Kellerer) at the Technical University of Munich (TUM). He holds an M.Sc. in Electrical and Computer Engineering from TUM, where his thesis focused on P4 switch performance modeling using queuing theory. His current research centers on 6G networks for critical telemedicine applications, particularly within the 6G-Life project, emphasizing end-to-end communication for medical robotics and surgical systems. He contributes to projects like the 6G Future Lab Bavaria and collaborates with the MITI group at Rechts der Isar Hospital to develop medical testbeds requiring high availability and low latency. Kröger also supervises student theses on 5G/6G security, network optimization, and in-network computing. His technical expertise spans programmable networks (P4), SDN, and performance analysis of network devices. He serves as a supervisor for student projects and internships, including implementations of medical testbeds and security analyses of cellular broadcast messages. His work bridges academic research with practical applications, aiming to advance communication networks for healthcare and future 6G systems.

Sebastian EckertView profile

Researcher

• Representation Theory of Finite Dimensional Algebras
• Amenable Representation Type
• Tame and Wild Algebras
• +3 more

Sebastian Eckert is a researcher at the Faculty of Mathematics , Bielefeld University , with prior postdoctoral experience at the Max Planck Institute for Mathematics in Bonn . His academic career includes PhD research under Prof. Dr. William Crawley-Boevey and MSc supervision by Prof. Dr. Henning Krause at Bielefeld University. Education : BSc (Bielefeld), MSc (Bielefeld), PhD (Bielefeld, 2022). Research Interests focus on the representation theory of finite-dimensional algebr with emphasis on amenable representation type , tame/wild dichotomy , and quiver theory . He explores connections between algebraic structures and graph theory to classify module families, particularly addressing Elek's conjecture linking tame algebras to amenable type. Article Trends reveal a progression from verifying amenable type for tame hereditary path algebras (2023) to generalizing these results to clannish algebras (2022) and Kronecker quivers (2022), while disproving amenability for wild algebras using dimension expanders (2020-2022). His work bridges abstract algebra with concrete applications in mathematical analysis. Grants & Projects include coordination of the International Research Training Group 2235 (IRTG 2235/2: "The Regular in the Irregular") funded by the German Research Foundation (DFG), and participation in third-party funded projects since 2016.

Jan PeleskaView profile

Professor

• Formal Methods
• Dependable Systems
• Distributed Systems
• +8 more

Jan Peleska is a Professor at the Department of Computer Science, Faculty of Mathematics and Computer Science, University of Bremen. He is a member of the Bremen Institute of Safe Systems (BISS) and co-editor of the BISS Monographs series. His research focuses on the application of formal methods and model-based testing to safety-critical embedded systems in domains such as avionics, railways, and automotive engineering. Affiliation: University of Bremen, TZI (Center for Computing Technology), BISS (Bremen Institute of Safe Systems) Academic Role: Professor of Computer Science Research Interests Peleska’s work emphasizes formal methods for dependable systems, particularly distributed and reactive real-time systems. Key areas include: Formal methods (safety, reliability, availability, security) Development of fault-tolerant systems Test automation for reactive systems Tools development for formal methods Integration with software development standards His research is applied to industrial projects involving safety-critical embedded systems, such as avionic systems and railway control systems. A comprehensive overview is provided in his Habilitation Thesis: Formal Methods and the Development of Dependable Systems . Publication Trends Peleska’s recent publications (2012–2022) focus on model-based testing (e.g., symbolic finite state machines, CSP refinement), standardisation of autonomous train control, and tools for automated testing. His work addresses challenges in railway interlocking systems, avionic software verification, and hybrid system validation, often combining formal methods with practical industrial applications. Scientific Awards Best Paper Award at FORMS/FORMAT 2014 Best Paper Award at QA+Test 2007 Other Responsibilities Peleska co-manages the Post Graduate Programme Embedded Systems GESy and serves as a shareholder/consultant for Verified Systems International GmbH. He has delivered invited lectures on industrial verification, model-based testing, and formal methods at institutions like the University of Tunghai (2016) and workshops including CyPhyAssure Spring School (2019).

• Nanophotonics
• Quantum Technologies
• Computational Optics
• +5 more

Dr. Sven Burger is a leading Researcher at the Zuse Institute Berlin (ZIB) within the Modeling and Simulation of Complex Processes department. His work focuses on Nanophotonics , Quantum Technologies , and Optical Resonance Computation , particularly in photonic crystals, plasmonic systems, and quantum light sources. Key projects: NanoLab GRIPS 2024 , MATH+ TES QT , MATH+ PaA-1 (perovskite solar cells), Colour Impression of Solar Cells Collaborations: MATH+ , BIFOLD , Research Campus MODAL His research spans Bayesian optimization for quantum systems, quasinormal mode expansions , chiral plasmonics , and terawatt-scale photovoltaics . Recent work emphasizes RPExpand software for resonance analysis and AAA algorithm applications in photonic design. He contributes to quantum key distribution via plug&play single-photon sources, hot carrier dynamics in plasmonic nanocrystals, and high-efficiency light extraction for deep-UV LEDs. His computational methods address non-Hermitian systems , exceptional points , and self-interference nanoparticle tracking .

Nathanaël FijalkowView profile

Researcher

• Games
• Machine Learning
• Automata Theory
• +9 more

Nathanaël Fijalkow is a Researcher at CNRS in LaBRI (Bordeaux) and a Research Fellow at The Alan Turing Institute in London. His primary research fields include games , machine learning , automata theory , and dynamical systems , with a focus on synthesizing programs from logical specifications and probabilistic models. Research Interests span program synthesis (programming by example), controller synthesis (temporal logic specifications), games on graphs (parity/mean payoff games), probabilistic automata (bounded ambiguity), and invariants for linear dynamical systems. He bridges formal methods with machine learning through projects like DeepSynth . Scientific Contributions include: Undecidability results for probabilistic automata Advances in parity game algorithms (quasi-polynomial lower bounds) Foundations of probabilistic modal logics Efficient synthesis techniques using SMT solvers and distributional learning Supervision involves guiding postdocs and PhD students such as Guillaume Lagarde, Antonio Casares, and Pierre Ohlmann. He has secured grants like the Momentum DeepSynth project (2019-2021) , aiming to merge formal methods with ML for program synthesis.