جست‌وجوی استاد و پژوهشگر

• Design of Experiments (DoE)
• Statistical Computing
• Regression Analysis
• +۳ مورد دیگر

Ulrike Grömping is a Professor of Applied Statistics and Business Mathematics at Beuth University of Applied Sciences Berlin, Department of Mathematics, Physics, and Chemistry. She specializes in Design of Experiments (DoE), statistical computing with R, and variable importance in regression models. Her academic career includes roles at Dortmund University and Ford Motor Company. She is a Book Review Editor for the Journal of Statistical Software and contributes to R packages such as DoE.base , FrF2 , and relaimpo . She holds a PhD in Statistics from Dortmund University (1996) and has published extensively on factorial designs, algorithmic methods, and statistical methodology. Education: 1991: Diploma in Statistics, Dortmund University 1996: PhD in Statistics, Dortmund University Research Interests: Design of Experiments, statistical software development, regression analysis, biostatistics, and combinatorial optimization. Professional Roles: Book Review Editor, Journal of Statistical Software Editor of Departmental Report Series Freelance Statistical Consultant Software Contributions: Maintainer of R packages for DoE and statistical inference, including DoE.base , FrF2 , and ic.infer . Her work bridges theoretical statistics with practical applications, emphasizing reproducible research and open-source tools. She collaborates across disciplines, including biotechnology and transportation safety, and has advised on EU-funded projects like TRACE.

Regina Pohle-Fröhlichمشاهده پروفایل

استاد

• Image Processing
• Pattern Recognition
• Computer Vision
• +۵ مورد دیگر

Regina Pohle-Fröhlich is a Professor of Computer Science and Graphical Data Processing at the Department of Electrical Engineering and Computer Science, Niederrhein University of Applied Sciences. Her research focuses on image processing, pattern recognition, computer vision, and medical imaging applications. Education: Diplom-Ingenieurin in Materials Engineering (1989), PhD in Image Analysis of Welding Defects (1995), Habilitation in Medical Image Analysis (2004) Her work spans applications in neuromorphic event cameras for outdoor monitoring, 3D city modeling, and biomedical image analysis. She collaborates extensively with institutions like the University of Cologne, German Aerospace Center, and Charité Berlin. Recent research trends include deep learning for event stream segmentation, semantic scene filtering, and advanced 3D reconstruction techniques. She actively participates in the iPattern Institute for Pattern Recognition and the Promotionskolleg NRW graduate institute. Key Projects: MLPCO (Machine Learning for Crop Output), KIRaPol.5G (AI for Radar Surveillance), BeeVision (Bee Population Monitoring), and EU/DFG-funded agricultural sustainability initiatives.

Rolf H. Möhringمشاهده پروفایل

استاد

• Combinatorial Optimization
• Graph and Network Algorithms
• Operations Research
• +۶ مورد دیگر

Prof. Rolf H. Möhring is a Professor at the Department of Mathematics, Faculty II – Mathematics and Natural Sciences, Technical University of Berlin. He specializes in Combinatorial Optimization, Graph and Network Algorithms, and Operations Research with applications in industrial and transportation systems. His research bridges theoretical foundations and practical implementations, addressing challenges in scheduling, distributed computing, and algorithmic game theory. Key research interests include graph algorithms, project scheduling optimization, and robust optimization methodologies. Notable contributions span network flow analysis, traffic equilibrium design, and logistics optimization in container terminals and shipping routes. Awards: 2025 Research.com Mathematics in Germany Leader Award, 2010 EURO Gold Medal. Publications: Over 127 papers with 16,279 citations in Computer Science and 113 papers with 15,733 citations in Mathematics. His work frequently explores combinatorial structures, invariant theory, and practical applications in distributed systems. His advising focuses on PhD students in combinatorial optimization and algorithmic theory, with contributions to the Mathematics Genealogy Project. Collaborations include industrial projects like Kiel Canal ship traffic optimization and AGV routing in container terminals, emphasizing real-world problem-solving through mathematical frameworks.

Mahdi Homayouniمشاهده پروفایل

مدرس ارشد

• Scheduling Optimization
• Operations Research
• Logistics and Supply Chain Management
• +۴ مورد دیگر

Mahdi Homayouni is a Senior Lecturer in Industrial Engineering and Management at the School of Business, Social & Decision Sciences, Constructor University. His expertise lies in scheduling optimization, logistics, and operations research. He holds a PhD in Industrial and Systems Engineering from Universiti Putra Malaysia (2012), an MSc in the same field (2008), and a B.Eng. in Industrial Engineering (2003). His research focuses on advanced scheduling methodologies for manufacturing systems, maritime operations, and container terminals. He has developed algorithms such as hybrid genetic algorithms, particle swarm optimization, and biased random key genetic algorithms (BRKGA) to address complex problems like energy-efficient job shop scheduling, integrated production-transport systems, and port automation. His work emphasizes sustainability, resource optimization, and the application of metaheuristics to real-world logistical challenges. Dr. Homayouni has held academic positions at institutions including the University of Porto (FEP), Islamic Azad University, and served as a research assistant at INESC Technology and Science. His contributions span theoretical advancements in scheduling models and practical applications in supply chain management, with a strong emphasis on interdisciplinary solutions. His recent publications highlight innovations in digital twin technology for seaport sustainability, energy-efficient manufacturing systems, and multi-objective optimization in transportation logistics. He continues to explore cutting-edge applications of AI-driven algorithms to enhance operational efficiency in industrial and maritime sectors.

• Operations Research
• Combinatorial Optimization
• Algorithmic Graph Theory
• +۳ مورد دیگر

Prof. Dr. Marzena Fügenschuh is a Professor at the Berlin School of Economics and Law (BHT Berlin), affiliated with the Department of Mathematics - Physics - Chemistry. She has been actively involved in teaching since the summer semester of 2009, offering courses in applied mathematics, computer science, and media informatics. Her research focuses on operations research, combinatorial optimization, algorithmic graph theory, and network theory, particularly analyzing multiplex networks and their layered structures. Her work emphasizes synthetic model development for complex networks, including air transportation systems and layered network topologies. She has presented her research at major conferences such as Complex Networks and the European Conference on Operational Research. Supervising theses, she guides students in topics like multiplex network generation and optimization algorithms. Prof. Fügenschuh’s contributions span theoretical advancements in graph bisection and practical applications in magnetic measuring systems and industrial design. Her interdisciplinary approach bridges algorithmic theory with real-world engineering challenges.

Alex Blackمشاهده پروفایل

پژوهشگر

• Algebraic Combinatorics
• Geometric Combinatorics
• Optimization
• +۳ مورد دیگر

Alex Black is currently a Hermann Weyl Instructor at ETH Zurich, focusing on algebraic and geometric combinatorics and optimization. He will join Bowdoin College as a tenure-track assistant professor in the mathematics department starting Fall 2025. His research emphasizes the simplex method and its applications in optimization and polytope theory. Black’s research explores the interplay between algebraic and geometric combinatorics, with a particular focus on optimization and the simplex method. His work addresses topics such as polytopes, matroid theory, and pivot rules, aiming to advance understanding in discrete and computational geometry. He investigates issues like exponential lower bounds for pivot rules, monotone paths on polytopes, and the structure of flag polymatroids. INFORMS 2022 George Nicholson Paper Competition Finalist for Small Shadows of Lattice Polytopes No advising roles or grants are explicitly mentioned in the provided information.

Cornelia Schönمشاهده پروفایل

استاد

• Operations Research
• Service Operations Management
• Revenue Management
• +۳ مورد دیگر

Prof. Cornelia Schön serves as Professor and Chair of Service Operations Management at the University of Mannheim Business School, where she also directs the Mannheim Executive MBA Program. Her expertise bridges operations research with practical business applications, focusing on data-driven decision support for complex service environments. Her academic foundation includes: Ph.D. and Habilitation from Karlsruhe Institute of Technology (KIT) Diploma in Industrial Engineering MBA from UMass Boston Schön's research centers on quantitative methods for service operations management, with emphasis on revenue management (dynamic pricing, assortment optimization), service design (simultaneous product-process development), and sustainable operations (green product design, servicizing). She integrates operations research with cross-functional value creation, addressing real-world challenges in retail, transportation, and financial services through data-driven modeling. Recent publications reveal consistent focus on machine learning-enhanced assortment optimization, airline/railway scheduling under uncertainty, and sustainability integration in product design. Her work demonstrates strong industry applicability, particularly in transportation logistics and consumer-facing service sectors, with growing emphasis on ESG factors in operational decision-making. No scientific awards for Prof. Schön were documented in the source materials. Schön actively supervises doctoral researchers including Fabian Strohm (service process design), Marius Krömer (airline crew scheduling), Niloufar Sadeghi (assortment optimization), and Oliver Vetter (product pricing), while mentoring master's students like award-winning Jan-Hendrik Büscher (ESG in bank risk management). Her research receives industry collaboration funding and addresses practical implementation through application-driven projects. The Chair maintains an active research ecosystem with dedicated research assistants and administrative support, facilitating collaborative projects that translate theoretical models into operational solutions for partner organizations.

Lukas Pottmeyerمشاهده پروفایل

پژوهشگر

• Number Theory
• Diophantine Approximation
• Algebraic Number Theory
• +۲ مورد دیگر

Dr. Lukas Pottmeyer is a faculty member at the Faculty of Mathematics, University of Duisburg-Essen, with offices in both Essen (WSC-N-3.38) and Duisburg (BC 507). He serves as Student Advisory Service coordinator and teaches core mathematics courses for engineering and computer science students, including Mathematics for Engineering (WS 25/26), Stochastics I, Mathematical Modeling, and Discrete Mathematics across multiple semesters. His research focuses on Number Theory, particularly Diophantine Approximation, Arithmetic Dynamics, and Height Functions. Publications span from 2013-2022 with significant contributions to Mahler measure dynamics, $p$-adic numbers, and Bogomolov-type properties. His 2019 German-language textbook Discrete Mathematics (Springer-Spektrum) supports undergraduate instruction. Research trends show consistent specialization in algebraic number theory with increasing focus on dynamical systems applications. His Erdős number is 3, reflecting connections to prominent mathematicians. Teaching responsibilities include developing course structures with integrated lectures, exercises, and tutorials emphasizing solution-writing practice. Professional service includes student advising with structured consultation hours, mentoring for mathematics bachelor programs, and coordination of resources like STEP teams and mentoring groups. He actively supports students through the Academic Counseling Center and emphasizes foundational courses in Analysis and Linear Algebra.

• Operations Research
• Optimization
• Network Flows
• +۳ مورد دیگر

Prof. Horst W. Hamacher is a Professor in the Department of Optimization at the University of Kaiserslautern's Faculty of Mathematics. His research focuses on optimization, operations research, and their applications in logistics, healthcare, and disaster management. Key areas include network flow optimization, evacuation planning models, radiation therapy treatment design, and hub location problems. He leads the Optimization Group (AG Optimierung), developing algorithms for complex systems. His work integrates theoretical advancements with practical solutions, such as minimizing beam-on time in radiation therapy and optimizing urban evacuation routes. He has authored/co-authored over 100 journal papers and book chapters, including seminal contributions to facility location theory and dynamic network flows. Collaborations span academic and industrial partners, addressing challenges in public transportation, medical engineering, and sustainable urban planning. Notable projects include the 'OptionS' initiative for sustainable water management optimization and the 'FlowLoc' framework for evacuation dynamics. He actively contributes to interdisciplinary education, bridging mathematics with real-world applications like robotic assembly and infrastructure design.

• Computer Science Education
• Culturally Responsive Computing
• Augmented Reality for Education
• +۴ مورد دیگر

Dr. Wei Yan is an Associate Professor in the Department of Computer & Information Science & Engineering at the University of Florida's Herbert Wertheim College of Engineering. With an extensive publication record spanning computer science education, augmented reality applications, and culturally responsive computing, Dr. Yan has established a significant research presence with numerous publications in top-tier conferences and journals from 2023-2025. Dr. Yan's research interests focus on culturally responsive computing education, particularly with Indigenous communities including the Navajo Nation. Their work bridges the gap between technical computing concepts and culturally relevant pedagogy, with a special emphasis on spatial reasoning and mathematics education through augmented reality technologies. The research program has produced innovative AR classroom applications that help students understand complex spatial transformations and matrix algebra through interactive 3D visualizations. Through collaborations with researchers like Ashish Amresh, Paige Prescott, Maya Israel, and Heather Burte, Dr. Yan has developed several educational technology interventions that address inclusion in computer science education. Their publications reveal a strong commitment to broadening participation in computing, particularly among underrepresented groups, with a focus on teacher professional development and curriculum design that respects cultural contexts. Dr. Yan's technical expertise spans both educational technology development and core computer science topics, as evidenced by publications ranging from spatial reasoning in AR classrooms to advanced topics in integer coding and neural image compression. This interdisciplinary approach allows for the development of sophisticated educational tools grounded in solid computer science principles. Current research directions include AI-enhanced educational applications, culturally responsive computing curriculum development, and the integration of conversational AI with augmented reality for improved learning experiences. The work has significant implications for how computing education can be made more accessible and relevant to diverse student populations.

Dmytro Sytnykمشاهده پروفایل

پژوهشگر ارشد

• Fractional Calculus
• Mathematical Modeling
• Applied Mathematics
• +۳ مورد دیگر

Dmytro Sytnyk is a Research Fellow at the Technical University of Munich (TUM) under the Institute for Advanced Study (TUM-IAS), hosted by Prof. Barbara Wohlmuth. His appointment began in 2022 through the Fellowship for Ukrainian Scientists program. His research focuses on developing novel analytical and numerical tools for modeling fractional phenomena, particularly in areas such as diffusion in porous media, structural mechanics, and systems exhibiting memory effects. The project emphasizes fractional calculus—an extension of classical calculus to non-integer orders—which is critical for modeling transient systems with memory, such as shape-memory alloys and financial markets. As part of the TUM Department of Mathematics, his work addresses time-dependent fractional differential equations, requiring innovative analysis and numerical methods. His contributions aim to enhance accuracy in modeling complex systems across scientific and engineering domains.

• Electrical Engineering
• Robotics
• Biomedical Engineering
• +۶ مورد دیگر

Wilfrido Alejandro Moreno is a Professor in the Electrical Engineering Department at the University of South Florida. His research spans interdisciplinary domains including Electrical Engineering , Robotics , Biomedical Engineering , and Computer Science . Key areas of interest: Electrical Engineering Robotics Biomedical Engineering Computer Science Systems Engineering Applied Mathematics Renewable Energy Cryptography Signal Processing Research Trends: Moreno’s work focuses on fault-tolerant systems , context-aware mobile sensing , energy-efficient robotics , and biomedical signal processing . Recent publications highlight applications in neuromorphic computing , photovoltaic systems , and digital twins for health monitoring . Notable Contributions: He has pioneered glitch power consumption models for secure computing, variable stiffness control algorithms for humanoid robots, and adaptive sampling frameworks for smartphone sensors. Collaborations with experts like Ozgur Yurur and Kimon Valavanis underscore his interdisciplinary impact.

• Robotics
• Optimization Algorithms
• Machine Learning
• +۳ مورد دیگر

Victor Parque is an active researcher with a focus on robotics, optimization algorithms, and machine learning applications. His work spans robotics control, sensor network design, and algorithm development for engineering systems. He has collaborated with institutions globally, contributing to advancements in areas such as path planning for mobile robots, tactile sensor integration for food quality assessment, and prosthetic arm feedback systems. Key co-authors include Tomoyuki Miyashita and Satoshi Miura. His research emphasizes practical applications of computational methods in engineering and agriculture, with publications in venues like IEEE Access, Neurocomputing, and the International Conference on Neural Information Processing (ICONIP).

Martin Henkمشاهده پروفایل

استاد

• Convex Geometry
• Discrete Geometry
• Algebraic Combinatorics
• +۳ مورد دیگر

Martin Henk is a Professor at the Berlin Institute of Technology since October 2014. Previously, he held academic positions at Otto von Guericke University Magdeburg (2003–2014) and Technische Universität Wien (2001–2003). His research focuses on Convex and Discrete Geometry , with interdisciplinary applications in Algebraic Combinatorics, Integer Programming, and Differential Geometry. Editorial Roles : Managing Editor, Contributions to Algebra and Geometry (2022–) Journal of Algebraic Combinatorics (2018–) Discrete & Computational Geometry (2014–) Advisory Board, Journal of Nepal Mathematical Society (2017–) Research Themes explore the interplay between convex geometry, discrete mathematics, and computational methods. His projects include global analysis in differential and convex geometry, proximity of linear and integer programming solutions, and geometric properties of polytopes and Steiner polynomials. Scientific Awards : Johann Joseph Ritter von Prechtl Medal (Technische Universität Wien, 2008) Hlawka Prize of the Austrian Academy of Sciences (2002) Academic Leadership includes organizing workshops like the Conference on Convex, Discrete, and Integral Geometry (2019) and co-chairing sessions at the International Symposium on Mathematical Programming (2018). Labs/Teams : Affiliated with the Berlin Mathematical School and Berlin Mathematics Research Center Math+ , contributing to collaborative projects in discrete and computational geometry.

Ahmad Abdiمشاهده پروفایل

دانشیار

• Combinatorial Optimization
• Integer Programming
• Linear Programming
• +۳ مورد دیگر

Ahmad Abdi is an Associate Professor in the Department of Mathematics at the London School of Economics and Political Science (LSE). He joined LSE as a tenure-track Assistant Professor in 2018 and was promoted to Associate Professor in 2023. He holds a PhD in Mathematics from the University of Waterloo, supervised by Bertrand Guenin, and completed a postdoctoral fellowship at Carnegie Mellon University under Gérard Cornuéjols. His research focuses on Combinatorial Optimization, Integer and Linear Programming, Matroid Theory, and Graph Theory, particularly the study of Ideal Clutters and their applications to open conjectures like Woodall’s and the Generalized Berge-Fulkerson conjecture. Education: PhD in Mathematics, University of Waterloo (2018) Postdoctoral Fellow, Carnegie Mellon University (2018–2019) Research Interests: Combinatorial Optimization and its applications to conjectures in Graph Theory (e.g., Woodall’s conjecture) Ideal Clutters and their connections to Linear Programming Matroid Theory and structural graph properties Grants: EPSRC New Investigator Award (2023–2026) for research on Woodall’s conjecture and the Generalized Berge-Fulkerson conjecture Students and Postdocs: PhD Students: Ruilan Wang (since 2019), Mahsa Dalirrooyfard (since 2022) Postdoctoral Fellows: Meike Neuwohner (since 2024), Tamás Schwarz (since 2025) Teaching: MA431 Spectral Graph Theory (2021/22) Combinatorial Optimization: Packing, Partitioning, and Covering (2023) Workshops: Co-organized the Cargese Workshop on Combinatorial Optimization (2022, 2024) and ACO@CMU Workshop (2020).