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• Blockchain Technologies
• Distributed Systems
• Federated Learning
• +3 more

Kaiwen Zhang is a prolific researcher affiliated with institutions including École de Technologie Supérieure (Montréal, Canada), Technical University of Munich, and McGill University. His work spans blockchain technologies, distributed systems, federated learning, and privacy-preserving protocols, with a focus on applications in electric vehicle infrastructure, smart grids, and online gaming. Research Interests: He specializes in blockchain-based solutions for supply chain traceability, IoT security, and federated learning monetization. His studies often integrate decentralized architectures, cryptographic protocols, and event-driven systems, addressing challenges in scalability, privacy, and resource allocation. Publication Trends: Over 17 years (2008–2025), Zhang’s 39 publications (323 citations) emphasize blockchain’s intersection with cybersecurity, transportation, and distributed computing. Key subtopics include smart contracts, privacy-preserving EV charging, and federated learning frameworks. Collaborations: He frequently collaborates with colleagues like Hans-Arno Jacobsen, Mohammad Sadoghi, and Syed Muhammad Danish, contributing to conferences such as Middleware, DEBS, and ACM/SIGAPP Symposium on Applied Computing.

Qing LiuView profile

Professor

• Maritime Economics
• Global Logistics
• Transportation Economics
• +6 more

Prof. Dr. Qing Liu is a Professor of Maritime Economics at the University of Hamburg's Business School, where she has led the Maritime Economics Research Center (MERC) since May 2016. Her work focuses on global maritime shipping, port dynamics, and logistics optimization, leveraging expertise in game theory, operations research, and geospatial analysis. She previously served as Director of Transportation Economics at the Nick J. Rahall Transportation Institute (2014–2016) and as a Research Assistant at the Upper Great Plains Transportation Institute (2012–2014). Education: Doctorate in Transportation & Logistics, North Dakota State University (supervised by Dr. William Wilson) Bachelor's in International Shipping Management, Dalian Maritime University Her research spans port competition, optimal routing for global logistics, inland waterway shipping, and green transportation strategies. She actively collaborates with public agencies, private practitioners, and international partners, aiming to position MERC as a global hub for maritime economics research and industry engagement. Professional Engagements: Committee member, Standing Committee on Transportation and Economics Development (ADD10), U.S. Transportation Research Board (TRB) (2012–2018) Europe Board of Directors, Chinese Overseas Transportation Association (COTA) Co-chair, Technology Committee for Port Competition and Collaboration, World Transportation Convention (2017–2019) She has led externally funded studies as Principal Investigator and contributes to policy discussions through presentations at forums like the GIGA Forum 2019 and IAME conferences.

Alf KimmsView profile

Professor

• Operations Research
• Logistics and Supply Chain Management
• Revenue Management
• +6 more

Prof. Alf Kimms is a full professor at the University of Duisburg-Essen, holding the chair of Logistics and Traffic Management. He previously served as a full professor at the Technical University of Freiberg (2001–2006). His research focuses on applying operations research methods to logistics, supply chain optimization, revenue management, and evacuation planning. He earned his Ph.D. in Business Administration from the University of Kiel (1996) and his postdoctoral lecturer qualification (2001), both focusing on project management and production scheduling. Kimms' academic career is marked by contributions to high-impact journals such as European Journal of Operational Research and Annals of Operations Research . He has led projects for companies like Bayer, Lufthansa, and DaimlerChrysler, emphasizing practical applications of optimization. A 2005 Handelsblatt ranking placed him among Germany’s top ten business administration professors. He actively participates in professional societies, including the German OR Society (GOR), where he founded the Revenue Management working group. His research spans network design, disaster response logistics, cooperative game theory, and airline alliance strategies. Notable projects include evacuation modeling for urban areas and revenue management frameworks for broadcasting industries. Kimms reviews for the German Research Foundation (DFG) and serves on international conference committees, balancing academic rigor with industry collaboration.

• Mixed-Integer Nonlinear Programming
• Network Optimization
• Polyhedral Combinatorics
• +5 more

Prof. Dr. Maximilian Merkert is a Junior Professor for Optimization and Uncertainty in Mobility at the Institute for Mathematical Optimization, Technische Universität Braunschweig, since October 2021. Previously, he was a Postdoc at Otto von Guericke University Magdeburg (2017-2021) and a PhD student/research assistant at Friedrich-Alexander-Universität Erlangen-Nürnberg (2012-2017). His research focuses on mixed-integer nonlinear programming, network optimization, polyhedral combinatorics, and bilevel optimization with applications in mobility, logistics, and medicine. Research Interests: Mixed-Integer Nonlinear Programming Network Optimization Polyhedral Combinatorics Bilevel Optimization Game Theory Mobility Systems Teaching: Lectures and seminars on discrete optimization, multi-level optimization, and mathematical optimization Supervised computer labs and advanced optimization courses Publications: Contributions to mathematical programming journals and conferences (e.g., ICLR, Operations Research Proceedings) Focus on control languages, neural networks, wind farm optimization, and medical applications

Sebastian StillerView profile

Professor

• Optimization
• Operations Research
• Algorithmic Game Theory
• +5 more

Prof. Dr. Sebastian Stiller is a Professor at the Institute for Mathematical Optimization within the Carl-Friedrich-Gauß-Fakultät at Technische Universität Braunschweig. His research focuses on optimization, operations research, algorithmic game theory, quantum computing, and transportation science. He leads projects funded by DFG and BMBF, including 'SOAP' for air transport optimization and 'HyNEAT' for hydrogen supply networks in aviation. He teaches courses such as Linear Algebra, Algorithmic Game Theory, and Quantum Algorithms in both German and English. His research spans robust optimization, vehicle routing, and quantum algorithm development. Notable projects include optimizing wind farm control systems and analyzing quantum computing's potential for solving linear programming challenges. He collaborates with industry partners like 4flow AG and GAMS Software GmbH, emphasizing practical applications of his theoretical work. Teaching responsibilities include foundational mathematics courses for data science and engineering students, as well as advanced seminars on optimization. His contributions to operations research have been published in top-tier journals like Operations Research and Transportation Science.

Anita SchöbelView profile

Professor

• Operations Research
• Mathematical Optimization
• Robust Optimization
• +12 more

Anita Schöbel is a Professor in the Department of Mathematics at the Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU) and serves as the Director of the Fraunhofer Institute for Industrial and Financial Mathematics (ITWM) in Kaiserslautern. She is a leading figure in operations research and mathematical optimization, with a strong focus on public transportation systems, robust optimization, and multi-objective decision-making. Her dual roles bridge academic research and industrial application, particularly in logistics, healthcare, and energy systems. Her research interests include: Robust and integer optimization Public transport planning (timetabling, line planning, delay management) Facility and hub location problems Multi-objective optimization under uncertainty Algorithmic methods in transportation networks The analysis of her recent publications reveals a consistent focus on integrating robustness into transportation planning, using machine learning to enhance schedule reliability, and advancing theoretical frameworks for multi-objective optimization. Her work often combines mathematical rigor with real-world applicability, especially in public transit and pandemic modeling. She has contributed significantly to the development of optimization models for public health during the COVID-19 crisis. Her scientific awards include leadership roles in major professional societies: President of the European Association of Operational Research Societies (EURO), 2022–2023 President of the German Society for Operations Research (GOR), 2019–2020 Anita Schöbel has been actively involved in grant-funded research and collaborative projects, including the DFG Research Group FOR2083 on integrated transportation planning, the EU project EASIER, and the BMBF project SynphOnie. She is currently co-spokesperson of the DFG Graduate College 2982 on 'Mathematics of Interdisciplinary Multiobjective Optimization'. She also serves on advisory boards such as the steering committee of HLRS and the Fraunhofer Strategic Research Field on Next Generation Computing. She leads the research group 'Optimization' at RPTU and is associated with initiatives like LinTim (software for transport planning), QuanTUK (quantum computing applications), and GRK 2982. Her leadership extends to academic governance, including membership in the RPTU University Council and the Departmental Council of Mathematics.

Stefan RöhlView profile

Professor

• Logistics
• Operations Research
• Mathematics
• +4 more

Prof. Stefan Röhl is a Professor of Mathematics and Logistics at the Technical University of Bingen since August 2008. He holds a PhD in Operations Research from Humboldt University Berlin (2001) and has extensive experience in academia and research, including roles at the Zuse Institute Berlin and Vorarlberg University of Applied Sciences. He currently serves on the Senate of the Technical University of Bingen (since 2014) and previously chaired the Examination Board for several engineering programs (2012–2021). His research focuses on logistics, optimization, stochastic processes, and game theory. His notable publications address inventory management, vehicle scheduling, and stochastic dynamic models. Röhl teaches courses in mathematics, logistics, and operations research at both bachelor’s and master’s levels. He has collaborated on industry projects with partners like Vorarlberger Kraftwerke AG, BASF AG, and Deutsche Telekom AG, focusing on optimization of logistics, production processes, and energy management.

Stefan Wolfgang PicklView profile

Professor

• Operations Research
• Risk Management
• Complex Systems Optimization
• +3 more

Prof. Dr. Stefan Pickl is a full Professor of Operations Research at Universität der Bundeswehr München, where he leads the Chair of Operations Research and the Core Competence Center COMTESSA. His research integrates operations research, risk management, and complex systems optimization, with applications in critical infrastructure resilience, disaster reduction, and network security. Education includes a diploma in Mathematics and Philosophy from TU Darmstadt (1993), a doctorate (1998), and habilitation (2005) from TU Darmstadt and Universität zu Köln. He was an ERASMUS scholar at EPFL Lausanne. Research focuses on: Optimization of stochastic systems and game-theoretic frameworks for decision support. Risk analysis in transportation security (e.g., BMBF projects RIKOV and REHSTRAIN). Resilience modeling for critical infrastructure against hybrid threats. His recent publications emphasize stochastic positional games, humanitarian logistics, and ethical infrastructure challenges, reflecting interdisciplinary collaboration across computer science, engineering, and social sciences. Awards include three Best Paper Awards (CASYS 2003, 2005, 2007) and the Acquisition Research Symposium Award (2013). He secured significant grants for projects like RIKOV (terrorism risk in rail transport) and REHSTRAIN (high-speed train resilience). Leads the COMTESSA research team with 15+ members, including junior professors, scientists, and engineers. Collaborates with international centers like MUNICH AEROSPACE, CENETIX-NPS, and CODE.

Andreas WieseView profile

Associate Professor

• Combinatorial optimization
• Approximation algorithms
• Operations research
• +3 more

Prof. Dr. Andreas Wiese is an Associate Professor at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology and the Department of Mathematics. He previously held academic positions at the Vrije Universiteit Amsterdam (2021-2022), Universidad de Chile (2016-2021), and the Max-Planck-Institut für Informatik (2012-2016). Andreas Wiese earned his PhD in Mathematics from TU Berlin (2008-2011) and studied Mathematics and Computer Science at TU Berlin (2002-2008). His research focuses on combinatorial optimization , approximation algorithms , and geometric problem-solving , particularly for NP-hard problems in packing, scheduling, and network flow. His recent work includes A 2024 SODA publication on outlier-aware minimum sum of radii approximation A 2023 STOC paper improving weighted flow time minimization Foundational contributions to unsplittable flow and geometric knapsack problems with consistent appearances at top-tier conferences like STOC, FOCS, and SODA. Andreas Wiese leads the Discrete Optimization research group at TUM, supervising PhD students Alexander Armbruster, Elisa Dell'Arriva, and Sandy Heydrich. He has organized major conferences including LATIN 2024 and ADFOCS 2015 , and served on program committees for STOC, FOCS, and SODA.

• Transportation Engineering
• Traffic Flow Analysis
• Urban Mobility
• +4 more

Mónica Menéndez is a Professor at New York University Abu Dhabi, UAE, specializing in transportation engineering and intelligent mobility systems. Her research focuses on urban traffic flow modeling, signal control optimization, and machine learning applications for transportation networks. Key Affiliations: New York University Abu Dhabi Coauthors: Alexander Genser, Saif Eddin Jabari, Kaidi Yang, Lukas Ambühl Her research interests include traffic flow analysis, connected vehicle technologies, and sensitivity analysis of transportation models. Recent work explores modular vehicle deployment for congestion mitigation, kinematic wave theory integration with deep learning, and network-level fundamental diagram modeling. Selected publications (2022-2025) demonstrate trends in applying supervised learning to traffic signal control, synthetic trip generation, and perimeter control strategies. She has contributed to journals like IEEE Transactions on Intelligent Transportation Systems and CoRR , with peer-reviewed conference papers at ITSC and VEHITS. As an advisor, she has mentored researchers working on autonomous vehicle impacts, traffic data imputation, and modular transit systems. Her lab collaborates on global multi-source traffic data analysis and sustainable urban mobility solutions.

• Zooarchaeology
• Stable Isotope Science
• Animal Domestication
• +12 more

Prof. Dr. Cheryl Makarewicz is a Professor of Protohistoric Archaeology and Social Archaeology at the Institute of Pre- and Protohistoric Archaeology , Christian-Albrechts-University, Kiel . She is actively involved in the CRC 1266 Scales of Transformation and the ROOTS Cluster of Excellence , focusing on human-animal-environment interactions in prehistoric societies. Her research expertise spans zooarchaeology , stable isotope science , and bioarchaeology , with fieldwork conducted in Jordan, Mongolia, South Africa, Italy, and Inner Asia. She investigates early animal domestication, pastoral economies, Neolithic subsistence, and methodological rigor in isotopic analysis. Her recent publications reveal a strong trend in isotopic methodologies applied to diverse contexts: from reconstructing Neolithic foddering practices and urban elite provisioning to understanding hominin habitat use and ancient climate dynamics. Her work integrates multi-proxy data, including n-alkanes, collagen, and enamel isotopes, to achieve high-resolution reconstructions of past lifeways. She has contributed to major journals such as Scientific Reports , Journal of Archaeological Science , PLoS One , Antiquity , and Quaternary International , often in collaborative, international teams. Scientific Leadership and Methodology: Develops best practices in isotope archaeology Pioneers high-resolution intra-tooth and biomarker analyses Integrates ethnoarchaeological and geoarchaeological methods As a principal investigator, she leads or contributes to projects such as the El-Hemmeh Project in Jordan and studies on Trypillia mega-sites, Xiongnu elites, and Afanasievo pastoralism. Her work bridges theoretical frameworks (e.g., Marxist value theory) with empirical data, advancing understanding of social complexity in early agricultural societies. Laboratories and Teams: Works within the Institute of Prehistoric and Protohistoric Archaeology at Kiel Collaborates with international teams across Europe, North America, and Asia Engages in multidisciplinary clusters including ROOTS and CRC 1266

Kapil AhujaView profile

Professor

• Machine Learning
• Network Science
• Computational Optimization
• +4 more

Prof. Kapil Ahuja is a Full Professor in the Department of Computer Science & Engineering at the Indian Institute of Technology Indore (IIT Indore), where he heads the Mathematics of Data Science and Simulation (MODSS) research lab. After completing dual Master's degrees and a Ph.D. from Virginia Tech (USA) followed by postdoctoral work at the Max Planck Institute in Germany, he has held visiting positions at UT Austin, IMT Atlantique, Sandia National Labs, TU Dresden, and TU Braunschweig. His administrative roles include founding Dean of International Affairs and former Head of Computer Science & Engineering at IIT Indore. Education: Ph.D. in Mathematics, Virginia Tech (2011) M.S. in Mathematics, Virginia Tech (2009) M.S. in Computer Science, Virginia Tech (2007) B.Tech. in Mechanical Engineering, IIT (BHU) Varanasi (2001) Research Focus: Prof. Ahuja's work bridges theoretical advances with real-world applications, emphasizing machine learning algorithms for plant/cancer studies, game-theoretic poverty reduction models, exascale climate modeling solvers, and drone trajectory optimization. His interdisciplinary approach integrates numerical linear algebra with network science to solve complex systems problems across healthcare, agriculture, and climate science, supported by 4.85 Crores INR in external funding. Publication Trends: Recent work demonstrates growing emphasis on AI-driven optimization for physical systems (drones, climate models) and biomedical applications (cancer classification). His publications increasingly feature cross-disciplinary collaborations between computer science, biology, and economics, with notable contributions in explainable AI for healthcare and resource allocation algorithms for social networks. Scientific Recognition: National Teacher's Award (2024) from the President of India Five-time recipient of IIT Indore's Best Teacher Award (2013-2023) Best Poster Award at International Workshop on Game Theory & Networks (2019) Steeneck Graduate Research Fellowship (Virginia Tech, 2011) Multiple SIAM travel awards for international conferences Mentorship & Service: Prof. Ahuja has graduated 5 Ph.D. and 4 M.S. (Research) students while mentoring 75 B.Tech. projects. He serves as Associate Editor for Applied Intelligence Journal (Springer Nature) and Knowledge and Information Systems, organizes international conferences, and reviews for 35+ academic sources. His administrative leadership significantly expanded IIT Indore's global partnerships through the Research Park initiative. Research Infrastructure: The MODSS lab maintains active collaborations with Oak Ridge National Lab, Sandia National Labs, and European institutions. Current projects include AI-optimized drone swarms for agricultural monitoring and game-theoretic models for poverty intervention, utilizing high-performance computing resources for large-scale simulations.