Find Academic Supervisors

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +7 more

Prof. Dr. Michael Guckert is a Professor of Business Informatics - Artificial Intelligence at the Department of MND (Management, Natural Sciences, Design) at Technische Hochschule Mittelhessen (THM). He serves as Spokesperson of the KITE Competence Center, Board member at hessian.AI, and Director at StudiumPlus. His research spans multiple domains with a strong focus on AI applications in medical contexts and multi-agent systems. Dr. Guckert's research interests center on applying artificial intelligence to solve complex problems across multiple domains. His primary focus is on medical applications, particularly using AI for electrocardiogram (ECG) analysis, cardiac pathology detection, and clinical decision support systems. He also maintains significant research in multi-agent systems for traffic simulation, model-driven development approaches, and trustworthy/explainable AI systems. His work bridges theoretical AI development with practical applications in healthcare, manufacturing, and transportation. Analysis of Dr. Guckert's recent publications reveals a clear trend toward medical AI applications, particularly in cardiology. His work on the RisKa project demonstrates how AI can interpret ECG data to detect heart conditions, with significant emphasis on explainability and trustworthiness. Parallel to this medical focus, he maintains active research in multi-agent traffic simulation systems (AGADE), acoustic emission analysis, and model-driven development approaches. The publications show increasing collaboration with medical researchers, indicating a strategic focus on interdisciplinary AI applications in healthcare. Dr. Guckert leads the RisKa project (2022-2024), a €736,682 initiative funded by the Ministry for Digital Strategy and Development, which develops an AI-based clinical decision support system for ECG analysis. His research group at THM KITE Competence Center collaborates with Justus Liebig University in Giessen on biomarker research. He has secured multiple research grants for projects involving AI in medical diagnostics, traffic simulation, and manufacturing quality control. His work demonstrates strong industry-academia collaboration, particularly in applying AI to solve real-world problems in healthcare and transportation. Dr. Guckert directs the KITE Competence Center at THM, which focuses on information technology research and applications. His team includes researchers specializing in medical AI, multi-agent systems, and model-driven development. The RisKa project team specifically brings together computer scientists and cardiologists to develop clinically useful AI tools. His work with hessian.AI positions him at the forefront of AI development in the Hesse region of Germany, facilitating collaboration between academic and industry partners.

Sonja UngerView profile

Researcher

• Specialty Optical Fibers
• Fiber Laser Technology
• Photodarkening in Rare-Earth Doped Fibers
• +5 more

Sonja Unger is a Scientist at the Leibniz Institute of Photonic Technology (IPHT) in Jena, Germany, working within the Technology Group Competence Center for Specialty Optical Fibers. Her research focuses on the material science and engineering aspects of specialty optical fibers for laser and sensing applications. Dr. Unger's research interests center on the fundamental properties of doped silica glasses for optical fiber applications. She investigates photodarkening phenomena in rare-earth doped fibers, particularly examining how co-dopants like cerium and aluminum can mitigate degradation effects in ytterbium and thulium fiber lasers. Her work also explores the viscous flow behavior of various doped silica glasses during fiber manufacturing processes, including collapsing techniques used in MCVD (Modified Chemical Vapor Deposition). Analysis of her publication record reveals consistent focus on specialty optical fiber development, with particular emphasis on thulium and ytterbium doped systems. Her research spans from fundamental material characterization to practical high-power laser applications, with significant contributions to understanding photodarkening mechanisms and developing mitigation strategies. Recent work has expanded into crystal-derived fiber approaches, combining crystalline and amorphous materials to create novel fiber structures with enhanced performance characteristics. Dr. Unger actively collaborates with researchers across the IPHT institute and with external partners, as evidenced by her co-authorship on numerous publications with colleagues from various research groups. Her work contributes significantly to advancing high-power fiber laser technology and specialty optical fiber development.

Benny MoldovanuView profile

Professor

• Auctions
• Mechanism Design
• Microeconomic Theory
• +2 more

Benny Moldovanu is a Professor at the University of Bonn , affiliated with the Department of Economics and institutions like the Hausdorff Center for Mathematics , ECONtribute , and CRC TR 224 EPoS . His research focuses on Auctions and Mechanism Design and Microeconomic Theory , with recent work exploring entropy-regularized optimal transport in information design, security design for risk-averse investors, and dynamic voting games. His scientific contributions include groundbreaking papers on auction theory, voting systems, and contract design, published in top journals like the Review of Economic Studies and American Economic Review . Notably, he won the AEA Best Paper Award for AEJ: Microeconomics . His collaborations span institutions such as the University of Cambridge, MIT Press, and the Bonn Graduate School of Economics (BGSE) , where he mentors future economists. His work addresses real-world issues like Brexit, spectrum licensing, and nuclear weapons sales through theoretical and experimental lenses.

Piotr KowalskiView profile

Professor

• Computational Materials Science
• Electrochemistry
• Battery Materials
• +5 more

Dr. Piotr Kowalski serves as Head of Department at the Jülich Research Centre , leading the Theory and Computational Modeling of Materials in Energy Engineering (IET-3) group. His research focuses on computational materials science , electrochemistry , and nuclear waste management , leveraging density functional theory and quantum computing to model energy-related materials. Research Trends : His recent work explores high-entropy materials for batteries, protic ionic liquids in fuel cells, and quantum annealing for optimizing ionic configurations. He investigates radionuclide retention mechanisms in nuclear waste repositories and electrocatalytic interfaces for hydrogen evolution. Lab & Infrastructure : Piotr's team operates within IET-3 , contributing to the Institute of Energy Technologies at Jülich. Their computational studies support advanced energy storage solutions and nuclear safety research, with a focus on solid-state electrolytes and actinide immobilization .

Frank PuppeView profile

Professor

• Artificial Intelligence
• Medical Image Analysis
• Document Analysis
• +5 more

Frank Puppe is a Full Professor of Computer Science at the University of Würzburg, Germany, where he holds the Chair of Computer Science VI (Artificial Intelligence and Applied Computer Science) within the Faculty of Mathematics and Computer Science. He is also affiliated with the Center for Artificial Intelligence and Data Science (CAIDAS) and leads research in artificial intelligence, knowledge systems, and applied computer science. His educational background includes a Diploma in Computer Science from Bonn University (1983), a dissertation on Diagnostic Problem Solving from Kaiserslautern University (1986), and a habilitation on Problem Solving with Expert Systems from Karlsruhe University (1991). Professor Puppe's research spans multiple domains of artificial intelligence and its applications. His primary focus areas include Medical Image Analysis , where he develops AI systems for endoscopic disease detection and medical information extraction; Document Analysis and OCR , with significant contributions to processing historical documents and musical manuscripts; and Information Extraction from diverse domains including medical, legal, and literary texts. His work in E-Learning and E-Assessment has led to innovative systems for automatically evaluating programming assignments and argumentation structures. His recent publications demonstrate a strong interdisciplinary approach, bridging computer science with medicine, digital humanities, and law. A notable trend is the application of deep learning techniques to historical document analysis and medical imaging, while maintaining a strong foundation in knowledge-based systems. His research consistently focuses on practical applications of AI that solve real-world problems across multiple domains. 2015-2017: Senator at University of Würzburg 2011-2013: Dean at University of Würzburg 2008-2011: Dean of Students at University of Würzburg Professor Puppe leads multiple significant research projects including KINERGY (optimization of heating systems), DZ-PTM (order entry optimization in radiology), Corpus Monodicum (edition of medieval Latin music), and projects related to adenoma detection in colonoscopy. His laboratory develops tools such as OCR4all for historical document processing and it4all for programming assessment.

Matthias SchererView profile

Professor

• Actuarial Science
• Mathematical Finance
• Probability
• +6 more

Prof. Dr. Matthias Scherer is a Professor of Risk and Insurance at the TUM School of Computation, Information and Technology since 2019, with a prior appointment as Professor of Mathematical Finance (2010–2019). He is actively involved in bridging academic research and industry practice through memberships in the board of the Deutsche Gesellschaft für Versicherungs- und Finanzmathematik , leadership of the graduate school ISAM , and editorial roles for scientific journals. University of Ulm: Diplom in Business Mathematics (2005) Syracuse University (USA): Master of Science in Mathematics (2004) University of Ulm: Doctorate in Structural Credit-Risk Models (2007) Research Interests span actuarial science , mathematical finance , and stochastic modeling , with a focus on: Valuation of complex financial/insurance products Dependency structures and copula modeling Credit portfolio analysis Quantitative risk management Cyber risk and parametric insurance Stochastic gradient algorithms and simulation Scientific Awards include multiple Golden Circle Teaching Awards (2010, 2012, 2017), the Gauss Award (2011), and the ISAM Supervisory Award (2018). He leads the RiskFactory lab and collaborates with industry partners like Allianz , Munich Re , and Celonis through the TUM CAIR Labs initiative.

• Public Economics
• Political Economy
• Labor Economics
• +1 more

Emanuel Hansen is an Associate Professor of Economics at LMU Munich, holding the Chair of Public Economics. He serves as Research Director and Program Director at the Center for Economic Studies (CES) and is a Principal Investigator of the CRC TRR 190 "Rationality & Competition". His research appears in leading journals including Econometrica and the American Economic Journal. Hansen's research spans public economics, political economy, labor economics, and economic theory. He investigates tax policy (particularly Earned Income Tax Credits), welfare program design, political competition mechanisms, and multi-margin labor supply responses. His work combines theoretical modeling with empirical analysis to evaluate Pareto-improving reforms and policy interactions in social security systems. Recent publications reveal strong emphasis on German and French tax-transfer systems, with growing focus on gender inequality dynamics and family policy impacts. His political economy work explores endogenous party formation and optimal power concentration. This research directly informs welfare reform design, particularly regarding transfer withdrawal rates and work incentive structures across European contexts. As Research Director of CES, Hansen leads interdisciplinary teams within LMU's economic research ecosystem. The CRC TRR 190 collaboration under the German Research Foundation provides infrastructure for his ongoing work on rationality frameworks and competitive market analysis.

Andreas ReuterView profile

Professor

• Wind Energy Systems
• Wind Turbine Design
• Rotor Blade Technology
• +3 more

Prof. Dr.-Ing. Andreas Reuter serves as Managing Director at both the Institute for Wind Energy Systems (LUH) and the Fraunhofer Institute for Wind Energy Systems IWES . Affiliated with the Faculty of Civil Engineering and Geodetic Science at Leibniz University Hannover, his work focuses on wind turbine design, structural reliability, and renewable energy systems. PhD in Wind Turbine Fatigue (Technical University Berlin) Executive Director positions since 2010 Co-founder roles in multiple wind energy companies His research explores innovative wind turbine concepts , smart rotor blade design , fatigue load analysis , and technology assessment in wind energy. Recent publications emphasize aerostructural optimization , active load management , and offshore wind turbine modeling . Publications trends include multi-megawatt turbine evaluation , swept blade aerodynamics , and sensor technology integration for energy systems. His work spans mechanical engineering , renewable energy , and structural dynamics sub-fields. Courses taught include Rotor Blade Design for Wind Turbines , Wind Energy Technology series, and supervision of student projects/theses.

Michael HintermüllerView profile

Professor

• Applied Mathematics
• Optimization and Control
• Partial Differential Equations
• +4 more

Prof. Michael Hintermüller is the Director of the Weierstrass Institute (WIAS) and holds a professorship in Applied Mathematics at Humboldt-Universität zu Berlin. He serves as Founding Coordinator of BR50, Spokesperson of the Mathematical Research Data Initiative (MaRDI), and Board Member of the MATH+ Cluster of Excellence. His research focuses on nonsmooth optimization, PDE-constrained control, mathematical image processing, and quasi-variational inequalities. Leadership Roles: Director of WIAS; Founding Coordinator of BR50; Spokesperson of MaRDI; Board Member of MATH+ Key Research Areas: Mathematical image processing, optimization under uncertainty, PDE-constrained optimization, shape/topology optimization, learning-informed constraints Recent Applications: Image deblurring/denoising/demodulation, energy network modeling, gas dynamics on pipeline networks, thermoforming simulations, strained photonic device design. His work combines analytical rigor with numerical methods for inverse problems, including adaptive regularization and physics-informed neural networks. Scientific Leadership: Active in mathematical modeling for biomedical imaging (e.g., quantitative MRI) and industrial applications (e.g., semiconductor design, gas flow optimization). Develops novel algorithms for nonsmooth PDE systems and contributes to the theoretical foundations of quasi-variational inequalities and generalized Nash equilibrium problems.

Hongjin LiangView profile

Associate Professor

• Programming Languages
• Formal Verification
• Concurrency Theory
• +3 more

Hongjin Liang is an Associate Professor at the School of Computer Science , Nanjing University , China. He is an active researcher and educator in the fields of programming languages and formal verification, with a strong focus on concurrency theory, mechanized proofs, and memory models. Education: PhD in Computer Science (May 2014), dissertation titled Refinement Verification of Concurrent Programs and Its Applications . Research Interests: His research spans formal verification , concurrent programming , memory models , and mechanized reasoning . He is particularly known for his work on verifying concurrent data structures, program logics for concurrency, and certified compilation. He is a member of the PLaX research group . Publications and Impact: Liang has published extensively in top-tier venues such as POPL, PLDI, ESOP, TOPLAS, and CSL-LICS. His work often involves formalizing and verifying complex concurrent systems using interactive theorem provers like Rocq/Coq. Notable contributions include verifying compiler optimizations under weak memory models and developing program logics for randomized concurrent programs. Scientific Awards: Distinguished Paper Award , PLDI 2019 for "Towards Certified Separate Compilation for Concurrent Programs" Teaching and Advising: He teaches undergraduate and graduate courses including Formal Semantics of Programming Languages , Concurrency: Algorithms and Theories , and Compiler Design . He has supervised graduate students and served on numerous program committees for international conferences. Affiliations: He is affiliated with the PLaX research group at Nanjing University and has collaborated with researchers such as Xinyu Feng, Zhong Shao, and Jan Hoffmann.

Benjamin C. PierceView profile

Professor

• Programming Languages
• Type Systems
• Language-based Security
• +5 more

Benjamin C. Pierce is the Henry Salvatori Professor of Computer and Information Science in the School of Engineering and Applied Science at the University of Pennsylvania. As a Fellow of the ACM, he has made significant contributions to programming language theory and formal methods. His academic leadership includes previous editorial roles as co-Editor in Chief of the Journal of Functional Programming and Managing Editor for Logical Methods in Computer Science. His research spans multiple interconnected domains in programming language theory, with particular emphasis on type systems and their applications to security and verification. Pierce's work bridges theoretical foundations with practical implementations, most notably through his development of the Unison file synchronization tool and contributions to the Clowdr virtual conference platform. His research interests form a cohesive trajectory from foundational type theory to applied security and verification techniques. Pierce's scholarly output shows consistent focus on property-based testing, type systems, and formal verification methods. His recent publications demonstrate evolving interests in differential privacy verification, synchronization technologies, and the practical challenges of implementing formal methods in real-world systems. The progression of his work reflects both theoretical depth and practical relevance to software development challenges. Fellow of the ACM Author of influential textbooks Types and Programming Languages and Software Foundations Lead designer of the Unison file synchronizer Co-developer of the Clowdr virtual conference platform Former editorial leadership for multiple prominent programming languages journals As an educator and mentor, Pierce has contributed to the Programming Languages Mentoring Workshop (PLMW) and has served on numerous conference program committees. His academic service extends to SIGPLAN leadership roles including SIGPLAN Vice Chair and Steering Committee membership. His textbook Software Foundations has become a standard resource for teaching formal methods and proof assistants.

Michael HarrView profile

Researcher

• Artificial Intelligence
• Recruiting
• Digitalization and digital Transformation of Human Resource Management
• +4 more

Michael Harr is a doctoral researcher and research assistant at the University of Duisburg-Essen, affiliated with the Faculty of Computer Science and the Chair of Business Informatics and Integrated Information Systems. His work focuses on artificial intelligence, digital transformation of HR management, enterprise systems, new work arrangements, and digital communication. He has published extensively on these topics in leading journals and conferences. Education: M.Sc. in Business Information Systems (2020-2023), University of Duisburg-Essen B.Sc. in Business Information Systems (2016-2020), University of Duisburg-Essen His research explores the intersection of AI and human-centric systems, including studies on retail service robots, intelligent HRIS, generative AI in MOOCs, and user annoyances in voice assistants. Recent publications analyze digital communication trends and digitalization challenges in the construction sector. Publications: Harr has contributed to key areas such as retail automation, HRIS optimization, and AI-driven e-learning, with a focus on practical applications and theoretical frameworks. Supervised Theses: Exploring ChatGPT for MOOCs AI in Knowledge Management Technostress and Quiet Quitting Taxonomy of AI Recruitment Tools Talent Recruitment on Social Networks Labs and Teams: Harr is involved in the Retail Artificial Intelligence Lab (retAIL) and SAP Innovation Lab, contributing to projects on digital transformation and enterprise systems.

• Ferrous Metallurgy
• Advanced High-Strength Steels
• Medium-Manganese Steels
• +6 more

Dr.-Ing. Alexander Gramlich is a scientific staff member at the Chair of Metal Materials Science and Institute of Ferrous Metallurgy, RWTH Aachen University, Germany. His work focuses on advanced steel development, particularly medium-manganese steels, sustainable manufacturing, and digitalization of metallurgical processes. His research spans multiple critical areas of modern steel metallurgy including: Development of third-generation advanced high-strength steels Phase transformation kinetics in medium-manganese steels Sustainable steel production through recycling and eco-efficient processes Digital material twins and physics-informed machine learning Fatigue and fracture mechanics of automotive and wind energy components Dr. Gramlich's recent publications demonstrate a strong focus on bridging fundamental materials science with industrial applications. His work on medium-manganese steels addresses critical challenges in automotive lightweight design, while his research on wind turbine components contributes to renewable energy infrastructure. The integration of digital technologies, including AI-driven material design and digital twins, represents a cutting-edge approach to modern metallurgy. Based at RWTH Aachen University, one of Europe's leading technical universities, Dr. Gramlich contributes to both fundamental research and technology transfer to industry. His address at Intzestr. 1, 52072 Aachen, places him at the heart of Germany's industrial region, facilitating collaboration with major steel producers and automotive manufacturers.

• Steel Construction
• Additive Manufacturing
• Fire Safety Engineering
• +3 more

Jakob Blankenhagen is a research assistant at the Chair of Metal Construction at the Technical University of Munich . He holds an M.Sc. in Civil Engineering from TUM and specializes in additive manufacturing , fire safety engineering , and hybrid steel-timber structures . B.Sc. in Civil Engineering (2015-2019) M.Sc. in Civil Engineering (2019-2022) International Welding Engineer (2021) His research focuses on optimizing fatigue-stressed hollow section structures using Laser Powder Bed Fusion (LPBF) and developing fire-safe hybrid steel-timber constructions. Current projects include TRR277 A06, which investigates LPBF fundamentals for structural steel elements. Key publications address material characterization , fire behavior of hybrid structures, and machine learning-based pore detection in additive manufacturing. He contributes to advancing 3D-printed steel components and sustainable construction methods . He teaches courses on steel construction, composite building, and computational design at TUM, with a focus on practical implementation of additive manufacturing in construction.

Dirk LowkeView profile

Professor

• Digital Construction
• 3D Printing
• Sustainable Materials
• +6 more

Prof. Dr.-Ing. Dirk Lowke is a Professor at the Department of Materials Engineering, Technical University of Munich. He specializes in materials and digital manufacturing in construction, focusing on 3D printing with concrete and clay, ecological material optimization, durability, circularity, and mobile robotics. Before joining TU Munich in 2023, he led the Building Materials Department at TU Braunschweig's Institute of Materials Science and Technology (iBMB) from 2017 to 2023 and was a board member of the Braunschweig Materials Testing Institute. He studied civil engineering at TU Cottbus and earned his doctorate from TU Munich. Academic Affiliation: Technical University of Munich Prior Employment: TU Braunschweig (2017-2023) His research emphasizes digital and sustainable construction, particularly through resource-efficient production and maintenance of mineral structures. He contributed to understanding the thixotropy of self-compacting concrete (SCC) and the zeta potential of cementitious suspensions. Recent work includes interlaboratory studies on 3D printed concrete properties and numerical modeling for particle bed 3D printing. He actively participates in RILEM conferences and co-edited proceedings on digital fabrication. Prof. Lowke's publications highlight advancements in selective cement activation, shotcrete 3D printing, and additive manufacturing applications for coastal biogenic structures. He investigates how process parameters affect material density, dimensional accuracy, and hardened state properties, aiming to enhance the practicality and sustainability of digital construction methods.