جست‌وجوی استاد و پژوهشگر

Jochen Rethmannمشاهده پروفایل

استاد

• Algorithms
• Discrete Optimization
• Industrial Stacking Systems
• +۳ مورد دیگر

Prof. Dr. Jochen Rethmann is a Professor in the Department of Engineering and Computer Science at Niederrhein University of Applied Sciences in Krefeld, Germany. He teaches advanced computer science courses at the master's level and conducts research in algorithm development. Institution: Niederrhein University of Applied Sciences Department: Engineering and Computer Science Office: Room F 202 Contact: +49 (0)2151 822-4633 Professor Rethmann specializes in algorithm design and optimization, with particular focus on industrial applications. His research bridges theoretical computer science with practical logistics systems. He teaches core algorithm courses including Efficient Algorithms and Knowledge-Based Systems for master's students, along with project-based courses that emphasize practical implementation of algorithmic solutions. His current research focuses on developing efficient algorithms for discrete optimization problems, particularly for controlling industrial stacking systems where computer-controlled gripper arms manage container placement according to customer assignments. This work incorporates years of logistics experience while maintaining compatibility with existing system architectures. His research has been validated using real-world data provided by Bertelsmann Distribution GmbH in Gütersloh. Professor Rethmann teaches multiple courses for the winter semester 2025/26 including Efficient Algorithms, Knowledge-Based Systems, and Practical Application of Algorithms and Parallel Computing. His teaching spans both bachelor and master level programs with courses covering algorithms, data structures, programming, and specialized topics in computer science. Consultation hours are available during lecture periods on Mondays 13:00-14:00 and Wednesdays 10:00-11:00 on a first-come-first-served basis, with additional appointments available by email during lecture-free periods.

Anna Rohlfing-Bastianمشاهده پروفایل

استاد

• (Social) Sustainability
• Incentive Contracts
• Performance Measurement
• +۳ مورد دیگر

Prof. Dr. Anna Rohlfing-Bastian is a Professor of Managerial Accounting at the Faculty of Business Administration, Goethe University Frankfurt. She holds a PhD from the University of Mannheim and has held academic positions at institutions such as the University of Tübingen and WHU – Otto Beisheim School of Management. Her research focuses on incentive contracts, organizational design, sustainability, and the impact of transparency on investment decisions. She is a principal investigator at the TRR 266 - Accounting for Transparency and leads the DFG-funded project on 'Personality Traits and Incentives'. As the current president of the German Economic Association of Business Administration (GEABA), she actively contributes to academic governance and policy. Education and Career: 2002-2006: International Business Administration at Eberhard Karls University Tübingen (with study abroad at Università Commerciale Luigi Bocconi, Milan) 2010: PhD (summa cum laude) from University of Mannheim 2011: Visiting Scholar at Stanford University 2011-2013: Junior Professor at WHU – Otto Beisheim School of Management 2013-2016: Professor at University of Tübingen Since 2016: Full Professor at Goethe University Frankfurt Research Interests: Her work bridges accounting, economics, and organizational behavior. Key areas include: Design of incentive systems and performance measurement Task delegation and organizational structures Relevant costs in decision-making Social and environmental sustainability reporting Impact of personality traits on economic decisions Publications and Impact: Her research has been published in top-tier journals like The Accounting Review , Review of Accounting Studies , and Journal of Management Accounting Research . Recent work emphasizes sustainability standards and transfer pricing, reflecting her commitment to addressing contemporary business challenges. Grants and Leadership: As a PI in major research projects and GEABA chair, she drives interdisciplinary collaboration. Her editorial roles (e.g., Journal of Management Accounting Research ) highlight her influence in academic discourse. Labs and Teams: Central to her work is the TRR 266 consortium, which examines transparency in accounting systems. Her projects often involve cross-disciplinary teams, integrating insights from law, economics, and environmental science.

• Network Management
• Software-Defined Networking
• Network Function Virtualization
• +۶ مورد دیگر

Steven Latré is a Professor in the Department of Computer Science at the University of Antwerp, specializing in network management, software-defined networking, and network function virtualization. His research spans wireless communications, Internet of Things, machine learning for networking, and quality of experience optimization. With over 246 publications from 2007 to 2025, he has established himself as a leading researcher in network intelligence and management. His research focuses on developing intelligent approaches for network management, with particular emphasis on applying machine learning techniques to solve complex networking challenges. His work covers adaptive video streaming, resource allocation in heterogeneous networks, wireless sensor networks, and vehicular communications. His research often bridges theoretical advances with practical implementations, as evidenced by numerous collaborations with industry partners and participation in European research projects. His recent publications demonstrate a growing interest in applying AI and machine learning to networking problems, with significant contributions in network function virtualization, software-defined radio access networks, and intelligent resource allocation. His work shows a clear trajectory from traditional network management toward more intelligent, self-optimizing network systems that leverage the latest advances in artificial intelligence. His scientific contributions have been recognized through numerous publications in top-tier networking venues including IEEE Communications Magazine, IEEE Transactions on Network and Service Management, and IEEE Internet of Things Journal. His research has consistently addressed real-world networking challenges while pushing theoretical boundaries in network management and orchestration. Professor Latré has actively supervised numerous PhD students and collaborated extensively with researchers worldwide, particularly with colleagues at the University of Antwerp including Jeroen Famaey, Filip De Turck, and Tom De Schepper. His collaborative network spans multiple continents, reflecting the international impact of his research.

Alexander Hübnerمشاهده پروفایل

استاد

• Supply Chain Management
• Sustainable Logistics
• Retail Operations
• +۳ مورد دیگر

Prof. Alexander Hübner is a full Professor of Business Administration at the Technical University of Munich (TUM), leading the Chair for Supply and Value Chain Management at TUM Campus Straubing. His research focuses on sustainable supply chain design, decision support systems in retail, healthcare logistics, and operations optimization. He holds a PhD from the Catholic University of Eichstätt-Ingolstadt and has held roles including Associate Professor at MIT's Luxembourg Centre for Logistics and Head of the Institute for Supply Chain Management at the European Business School. He has extensive industry experience, including six years as a project manager at McKinsey & Company. Research & Awards: Hübner’s work spans retail shelf space optimization, inventory management, and hospital logistics. Notable contributions include applying Markov Decision Processes to patient-bed allocation and exploring omnichannel retail fulfillment. He has received the Emerald Literati Award (2019) and ranks among WirtschaftsWoche's Top 50 Economists (2020). He chairs the EURO Working Group on Retail Operations and serves on editorial boards of leading journals. Education & Career: After graduating in Business Administration from Eichstätt-Ingolstadt, he earned his PhD there and became a junior professor. His career includes roles at MIT, European Business School, and McKinsey. He currently advises on logistics for the German Logistics Association (BVL) and leads interdisciplinary research on sustainable supply chain innovation.

Bogdan Savchynskyyمشاهده پروفایل

پژوهشگر

• Combinatorial Optimization
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Dr. Bogdan Savchynskyy is a Senior Researcher and Group Leader at the Computer Vision and Learning Lab, Heidelberg University. His academic journey includes roles at TU Dresden and the Heidelberg Collaboratory for Image Processing. He holds a Ph.D. in Computer Science from National Technical University of Ukraine (Kiev Polytechnic Institute). Savchynskyy's research focuses on combinatorial optimization, graphical models, and their applications in computer vision and machine learning. Education: PhD in Computer Science, National Technical University of Ukraine (2009) Postdoc, Heidelberg Collaboratory for Image Processing (2009–2014) His research interests include large-scale combinatorial optimization, multi-graph matching, and unsupervised learning. Notable achievements include developing state-of-the-art graph matching solvers and securing DFG grants for projects like OPTEMA and UMDISTO. He has published extensively in top venues such as CVPR, ICCV, and AAAI. Dr. Savchynskyy supervises students in projects involving optimization techniques and teaches courses like Applied Combinatorial Optimization . His lab hosts regular seminars on convex and combinatorial optimization. Awards: DFG Grants (2016, 2022, 2024) Outstanding Reviewer Awards (ICML 2022, CVPR 2016/2015) Best Student Paper Award at CVPR 2014 Key projects include the Graph Matching Benchmark and Tracking-by-Assignment , advancing bioimaging and computer vision applications. His lab fosters collaboration in optimization and interdisciplinary research.

Clemens Thielenمشاهده پروفایل

استاد

• Discrete Mathematical Optimization
• Network Optimization
• Approximation Algorithms
• +۳ مورد دیگر

Prof. Clemens Thielen holds the Professorship for Optimization and Sustainable Decision Making at TUM Campus Straubing, Technical University of Munich. He previously served as Junior Professor at TU Kaiserslautern (2013–2019) and was appointed to the Professorship for Complex Networks at TUM Campus Straubing in 2019. His research focuses on discrete mathematical optimization, including network optimization, approximation algorithms for multiobjective problems, and practical applications like healthcare scheduling and infrastructure planning. He earned his PhD in Mathematical Optimization from TU Kaiserslautern in 2010, with studies at the University of Cambridge. Notable awards include the 2024 EURO Prize for OR for the Common Good and a 2018 teaching nomination. His work bridges theoretical advancements and real-world applications such as flood mitigation, traffic emission reduction, and crane logistics optimization. Education: PhD in Mathematical Optimization, Technical University of Kaiserslautern (2010) Studies in Mathematics at Technical University of Kaiserslautern and University of Cambridge Research Interests: Network optimization and approximation algorithms Multiobjective decision-making and sustainable resource allocation Applications in healthcare, transportation, and infrastructure Awards: EURO Prize for OR for the Common Good (2024) Nomination for Teaching Award of Rhineland-Palatinate (2018) Labs/Teams: Active in the Optimization and Sustainable Decision Making research group at TUM Campus Straubing, collaborating on projects such as municipal flood mitigation and healthcare scheduling.

Ivan Žuljمشاهده پروفایل

پژوهشگر

• Operations Research
• Combinatorial Optimization
• Logistics and Supply Chain Management
• +۵ مورد دیگر

Dr. Ivan Žulj is a scientific staff member at the University of Hohenheim, affiliated with the Institute of Business Administration within the Faculty of Business, Economics and Social Sciences. He works under the Chair of Operations Management led by Prof. Dr. Katja Schimmelpfeng, where he contributes to teaching and research in logistics and operations management. His responsibilities include leading exercises and seminars in Operations Management. Doctorate in Political Science, Technical University of Darmstadt M.Sc. in Management, University of Hohenheim B.Sc. in Economics, University of Hohenheim Dr. Žulj's research centers on quantitative methods for solving planning problems in logistics and healthcare, with a strong emphasis on combinatorial optimization. His work develops efficient heuristic, metaheuristic, exact, and hybrid algorithms to improve warehouse operations, particularly in order picking systems. Applications extend to both corporate logistics and healthcare logistics, aiming to enhance efficiency and safety through algorithmic solutions. The recent publications show a consistent trend in optimizing picker-to-parts systems using advanced algorithmic approaches. His work integrates robotics (AMRs), infection risk reduction, batch sequencing, and storage assignment, demonstrating interdisciplinary innovation in warehouse logistics. The use of hybrid metaheuristics like adaptive large neighborhood search and tabu search highlights his technical depth in solving NP-hard problems. Dr. Žulj has not been publicly recognized with any scientific awards based on the available information. He is actively involved in academic supervision, having contributed to final theses at the bachelor’s and master’s levels, though specific student names are not listed. There is no mention of external research grants, but his involvement in DFG projects and completed research initiatives suggests potential grant participation. His role includes developing optimization and simulation software for practical application in logistics planning. His research is conducted within the research focus of the Chair of Operations Management, which includes DFG-funded projects and completed studies on combinatorial optimization in logistics. The team includes research assistants and doctoral candidates working on related topics in operations management and supply chain optimization.

Franziska Eberleمشاهده پروفایل

پژوهشگر

• Approximation Algorithms
• Online Optimization
• Stochastic Scheduling
• +۳ مورد دیگر

Dr. Franziska Eberle is the Head of the MATH+ Junior Research Group in the Institute of Mathematics at Technische Universität Berlin. She leads research in approximation algorithms, focusing on uncertain environments such as online and stochastic models. Her work addresses scheduling, resource allocation, and combinatorial optimization under uncertainty. Education: PhD in Computer Science, Universität Bremen (2020) M.Sc. in Mathematics for Operations Research, TU München (2016) B.Sc. in Mathematics, TU München (2014) Research Interests: Franziska’s research spans approximation algorithms for stochastic and online scheduling, robust optimization, and algorithmic frameworks for commitment models. She has contributed to load balancing, matroid optimization, and learning-augmented algorithms. Her work bridges theoretical foundations and practical applications in scheduling and resource management. Recent Contributions: Developed algorithms for configuration balancing under stochastic requests (Mathematical Programming, 2024) Optimal online throughput maximization for unrelated machines (ACM Transactions on Algorithms, 2023) Robust scheduling frameworks for speed-uncertain machines (Mathematical Programming, 2023) Teaching: Franziska has taught courses on approximation algorithms, discrete optimization, and practical optimization modeling. Recent offerings include advanced topics in online optimization (Summer 2024). Labs/Teams: Her research group includes PhD student Sebastian Bruchhold, focusing on cutting-edge problems in optimization under uncertainty.

Stefan Weltgeمشاهده پروفایل

استاد

• Combinatorial Optimization
• Integer Programming
• Polyhedral Combinatorics
• +۳ مورد دیگر

Prof. Dr. Stefan Weltge is a Professor of Discrete Mathematics at the Department of Mathematics, Technical University of Munich (TUM). He holds a PhD in Mathematics from Otto von Guericke University Magdeburg (2016) and was a postdoctoral researcher at ETH Zurich. His research focuses on combinatorial optimization, integer programming, and polyhedral combinatorics, with notable contributions to extension complexity and mixed-integer programming. He has received multiple teaching awards at TUM, including the TUM Supervisory Award (2022) and Best Lecturer recognitions in 2019 and 2021/22. His work has been published in leading journals such as the Journal of the ACM and Journal of Combinatorial Theory B. Prof. Weltge’s academic contributions include groundbreaking research on the complexity of mixed-integer programs, polyhedral representations, and combinatorial optimization problems. He has organized conferences like OR 2024 and the Cargese Workshops on Combinatorial Optimization, and serves on program committees for IPCO, MIP, and ISCO. His research is supported by DFG grants, including the Individual Grant (NextGen) and the AdONE PhD Program. He advises PhD students working on topics such as integer programming, algorithm design, and optimization theory. His publications span theoretical advancements in convex optimization, linear programming relaxations, and applications in logistics and operations research. Notable articles include work on bounded subdeterminants in integer programs and the complexity of stable set problems. His research bridges discrete mathematics with practical algorithmic solutions, influencing both theoretical and applied domains.

Michael Krappمشاهده پروفایل

دانشیار

• Quantitative Methods
• Mathematical Economics
• Statistics
• +۴ مورد دیگر

Prof. Dr. Michael Krapp holds the Extraordinariat for Quantitative Methods in Economics at the University of Augsburg's Faculty of Business and Economics. His position is assigned to the Business Analytics & Operations cluster within the Institute for Statistics and Mathematical Economics. His research focuses on applying mathematical and statistical methods to solve economic decision problems. His primary areas include: Quantitative Methods in Economics Mathematical Economics Statistics Decision Theory Game Theory Business Analytics Operations Research Prof. Krapp teaches mathematics, statistics, decision theory, and game theory courses. He offers seminars on Selected Topics in Quantitative Methods for both semesters and supervises bachelor's and master's theses. He leads project studies like 'Decision Science and Artificial Intelligence' for master's students, emphasizing practical application of quantitative methods in data-driven environments. Students in his courses learn to engage with scientific literature, develop presentation topics, and apply quantitative modeling methods to research questions. His teaching approach prepares students for data-driven workplace challenges through realistic team projects.

Pallavi Jainمشاهده پروفایل

استادیار

• Parameterized Complexity
• Kernelization
• Computational Social Choice Theory
• +۷ مورد دیگر

Pallavi Jain is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Jodhpur, a position she has held since 2020. Previously, she was a Postdoctoral Fellow at Ben-Gurion University of the Negev, Israel (2019–2020) and the Institute of Mathematical Sciences, Chennai (2017–2019). Ph.D., Dayalbagh Educational Institute, Agra (2012–2017) Postdoctoral Fellow, Ben-Gurion University of the Negev, Israel (2019–2020) Postdoctoral Fellow, Institute of Mathematical Sciences, Chennai (2017–2019) Her research focuses on theoretical computer science, particularly in Parameterized Complexity , Kernelization , Computational Social Choice Theory , and Graph Algorithms . She explores algorithmic aspects of voting, fair division, and combinatorial optimization under structural and parameterized paradigms. Her work often bridges theoretical foundations with real-world applications in multiagent systems and participatory decision-making. Her recent publications span top-tier journals and conferences including Algorithmica , ACM Transactions on Computation Theory , AAAI , AAMAS , ICALP , and IJCAI . The publications reflect a strong trend in parameterized algorithms, fairness in allocation, committee selection, and voting under complex constraints. She has also contributed to heuristic methods in graph optimization problems. Best Paper Runner-Up Award at EUMAS 2022 SERB National Postdoctoral Fellowship (2017–2019) Maulana Azad National Fellowship (2014–2016) Institute Seed Grant (2022–2025) Indo-German Project Grant (2023–2025) Pallavi Jain actively advises BTech and MTech students and has mentored numerous interns from institutions like CMI, University of Calcutta, and Aligarh Muslim University. She has secured research funding from SERB and other national and international bodies. She serves on the program committees of major conferences including IJCAI, AAAI, AAMAS, and ECAI, and has co-organized workshops such as the Winter School on Algorithms for Graphs and Games and COSCOE 2023. She teaches courses such as Advanced Data Structures and Algorithms , Graph Theoretic Algorithms , and Computational Microeconomics . She leads a vibrant research group focused on algorithms and computational social choice, collaborating with leading researchers like Saket Saurabh, Nimrod Talmon, and Sushmita Gupta. Her lab emphasizes theoretical rigor and practical relevance in solving complex computational problems in social systems.

Viktor Kunčakمشاهده پروفایل

دانشیار

• Program Synthesis
• Program Verification
• Automated Reasoning
• +۳ مورد دیگر

Viktor Kunčak is an Associate Professor with tenure at the École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences. He leads the Laboratory for Automated Reasoning and Analysis (LARA) and has been at EPFL since 2007 after completing his PhD at the Massachusetts Institute of Technology (MIT). His educational background includes: PhD from Massachusetts Institute of Technology (MIT), 2007 Professor Kunčak's research focuses on bridging the gap between human goals and computational realizations through program synthesis , verification , and automated reasoning . His work has significant applications in software development, formal methods, and programming languages. He is particularly known for developing practical tools like Leon and Stainless that implement theoretical advances in automated reasoning. His recent publications demonstrate a consistent focus on advancing program synthesis techniques, verification frameworks, and formal methods. The research trajectory shows progression from foundational theoretical work to practical applications and tools that can be used by developers. Many papers focus on making verification and synthesis more accessible and efficient for real-world programming tasks. His notable scientific achievements include: ACM SIGSOFT Distinguished Paper Award for work on automated testing European Research Council (ERC) Grant of 1.5M EUR (2012) Communications of the ACM Research Highlight for a PLDI paper Professor Kunčak has supervised 13 completed PhD theses and teaches courses on functional and parallel programming, compilers, and verification at EPFL. He has also co-taught a popular MOOC on Parallel Programming that reached over 100,000 learners worldwide. His research has been supported by significant funding including a 5-year ERC grant. He has served in leadership roles for major conferences including as program co-chair for FMCAD 2014 and VMCAI 2012. He leads the Laboratory for Automated Reasoning and Analysis (LARA) at EPFL, which develops tools like Stainless for program verification. The lab has established an international presence through collaborations including a European COST Action to establish standardized formats for verification and synthesis (Rich Model Toolkit).

Stefanie Seiz-Kupfererمشاهده پروفایل

پژوهشگر

• Artistic Aesthetic Education
• Early Childhood Education
• Primary School Art Education
• +۷ مورد دیگر

Stefanie Seiz-Kupferer is a researcher at the University of Education Schwäbisch Gmünd, Department of Art, Institute of Arts. Her work integrates artistic practice with pedagogy, focusing on early childhood and primary school education. She has held academic roles since 2002, including teaching assignments and research collaborations. Education: Staatlich anerkannte Grafik-Designerin (1984–1988), Kolping Berufskolleg Stuttgart Freie Kunstschule Stuttgart (1989–1991) Diplom in Kulturgestaltung (1996–1999), Freie Hochschule Metzingen (now Fachhochschule Schwäbisch Hall) Her research explores artistic-esthetic education through sensory pedagogy, interdisciplinary art forms, and public art projects. She emphasizes hands-on learning in spaces like the "Kunstwerkstatt" (Art Workshop), linking art to environmental awareness, cultural integration, and creative curriculum development. Her work often involves collaborations between universities, schools, and community organizations. Key trends in her publications include sensory environments in art education, eco-art practices in schools, and interdisciplinary approaches to light, color, and shadow. She has contributed to materials for primary art education and cultural policy frameworks. Projects and Grants: Atelierstipendium from Esslingen District (2004–2007) "KiKuLa – kreativ von Anfang an!" (2022), funded by Louis Leitz Foundation, Vector Foundation, LBBW Foundation, and Morpho Foundation International collaborations in Poland, Germany, and Israel She leads and co-designs academic programs like the "Kunstwerkstatt," integrating art into early childhood education and primary schools. Her teams include university students, schoolchildren, and cross-institutional partners like the Touristik- und Marketinggesellschaft mbH Schwäbisch Hall and PH Freiburg.

• Economics
• Game Theory
• Microeconomics
• +۴ مورد دیگر

Prof. Dr. Stephan Lauermann is a faculty member in the Department of Economics at the University of Bonn , affiliated with the Institute of Microeconomics , ECONtribute , Hausdorff Center for Mathematics , and CRC TR 224 . His research focuses on Bargaining, Auctions, Search Theory, and Matching Theory , with applications to market design and information aggregation. Research Trends: Recent articles (2022-2025) emphasize information aggregation in elections and frictions in matching and auction models . Older works (2012-2017) address adverse selection in auctions, price discovery in search markets, and foundational matching theory. Subfields span dynamic matching , strategic voting , common-value auctions , and equilibrium analysis . Contact: Email: s.lauermann@uni-bonn.de , Phone: +49 228 73-6327, Room 3.004, Adenauerallee 24-42, Bonn.

David Monniauxمشاهده پروفایل

پژوهشگر

• program verification
• abstract interpretation
• static analysis
• +۸ مورد دیگر

David Monniaux is a senior researcher (directeur de recherche) at CNRS and an adjunct professor at École polytechnique. He works at VERIMAG, a computer science laboratory jointly operated by CNRS and the University of Grenoble. Dr. Monniaux obtained his PhD in 2001 from Université Paris Dauphine under Professor Patrick Cousot, with a dissertation on the static analysis of probabilistic programs by abstract interpretation. He later earned his habilitation in computer science in 2009 from Université Joseph Fourier, Grenoble, and also holds an agrégation in mathematics. Monniaux's research focuses on program verification, with particular emphasis on proving software correctness. His work spans theoretical foundations in computability theory and practical applications in safety-critical systems. He has made significant contributions to abstract interpretation, static analysis, and the verification of numerical properties in programs. His research bridges computer science theory with practical engineering challenges, particularly in the context of critical embedded systems where software failures can have severe consequences. His work connects to diverse fields including game theory, algebra, and convex optimization. His recent publications demonstrate a strong focus on improving the precision and efficiency of static analysis techniques. Key themes include polyhedral approximation, program analysis with local policy iteration, abstraction of arrays and maps, synthesis of ranking functions, and computing worst-case execution times. These works collectively advance the field of program verification by addressing challenges in handling nonlinear constraints, branching, and complex data structures while maintaining computational feasibility. Monniaux has supervised several students including Julien Henry, Alexis Fouilhé, George (Egor) Karpenkov, and Alexandre Maréchal (now at LIP6), with current students Hang Yu and Valentin Touzeau. He has led significant research projects including VERASCO (2012-2015), which aimed at integrating a static analyzer into the CompCert certified compiler, and STATOR (2012-2017), an ERC starting investigator grant exploring advanced techniques for automatic inference of program invariants. At VERIMAG, Monniaux is part of a vibrant research community focused on critical systems. His work connects with broader efforts in formal methods, with applications in aviation, automotive systems, and other safety-critical domains where software reliability is paramount.