جست‌وجوی استاد و پژوهشگر

Pieter Vansteenwegenمشاهده پروفایل

استاد

• Public Transportation Optimization
• Metaheuristics
• Demand-Responsive Transport Systems
• +۴ مورد دیگر

Prof. Pieter Vansteenwegen is a full professor at KU Leuven's Faculty of Engineering Science, leading the Centre for Industrial Management/Traffic and Infrastructure (CIB) and chairing the KU Leuven Institute for Mobility (LIM). With a PhD in Operations Research (2008), he works on robust public transport systems, metaheuristics for logistics, and demand-responsive mobility solutions. Chair, KU Leuven Institute for Mobility Program Director, Master of Mobility and Supply Chain Engineering Board member, International Association of Railway Operations Research His research integrates transportation engineering , logistics optimization , and smart mobility systems , focusing on: Demand-responsive public transportation Metaheuristic algorithm development Inventory routing problems Smart waste collection strategies Multi-robot scheduling Recent publications demonstrate expertise in variable neighborhood search , Benders decomposition , and genetic algorithms applied to public transport, satellite scheduling, and circular economy logistics. His work has been cited over 9,400 times (Google Scholar H-index 51). Scientific recognition includes: Multiple IAROR best paper awards Best Reviewer European Journal of Operational Research BIVEC-GIBET PhD awards (2009, 2021, 2023) RASIG-INFORMS Student Paper Prizes He directs KU Leuven's Planning and Operational Research subdivision , serves on faculty councils, and founded spin-off dyNAVic for electronic tourist guides. His teaching portfolio includes courses in Public Transportation Design , Distribution Logistics , and Operational Management .

Rui Yaoمشاهده پروفایل

مدرس

• Large-scale equilibrium modeling in multi-modal transport systems
• Individual mobility choice modeling
• Demand management strategies
• +۳ مورد دیگر

Rui Yao is a Lecturer at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the College of Engineering (ENAC) and the Department of Civil Engineering. Additionally, he works as a Scientist in the Laboratory for Human-Oriented Mobility Eco-system (HOMES) within EPFL. His research focuses on large-scale equilibrium modeling in multi-modal transport systems, individual mobility choice modeling, and demand management strategies. Education: B.Sc. in Civil Engineering, Technion – Israel Institute of Technology Direct-track Ph.D. in Transportation Engineering, Technion – Israel Institute of Technology His research spans both theoretical and applied domains, including stochastic traffic equilibrium , multi-passenger ridesharing systems , perturbed utility models , and deep learning for choice analysis . He has contributed to advancements in data-driven route choice modeling , integrated equilibrium models for electrified logistics , and stable matching frameworks for mobility platforms . Rui Yao is affiliated with the Human-Oriented Mobility Eco-system (HOMES) lab at EPFL, which focuses on innovative transportation solutions. His work bridges theoretical modeling with real-world applications in smart mobility and transportation policy.

Mark Wallaceمشاهده پروفایل

استاد

• Optimization
• Constraint Programming
• Artificial Intelligence
• +۵ مورد دیگر

Professor Mark Wallace is a renowned academic at Monash University , specializing in modelling and software platforms for planning, scheduling, and optimization problems . He has led groundbreaking projects such as the development of the ECLiPSe constraint programming platform (acquired by Cisco Systems) and the G12 hybrid optimization platform , which was commercialized through his company, Opturion . His research consistently bridges theoretical innovation with real-world applications, supported by industry funding from major companies like British Airways, Qantas, and Woodside Energy. Education: MA in Mathematics and Philosophy from Oxford University; MSc in Artificial Intelligence from Queen Mary College, London; PhD in Communicating with Databases in Natural Language from Southampton University. His work focuses on application-driven research in constraint programming, hybrid optimization systems, and decision support technologies. Recent publications highlight advancements in public transport routing , autonomous vehicle fairness constraints , and human-centred feasibility restoration . He actively collaborates with industry partners on projects involving Melbourne Water , Woodside , and the Alertness CRC , driving innovations in smart infrastructure and transport systems.

Samy El-Tawabمشاهده پروفایل

استاد

• Intelligent Transportation Systems
• Computer Networks
• Vehicular Ad-Hoc Networks (VANET)
• +۶ مورد دیگر

Samy El-Tawab is a Professor and the Information Technology Program Director at James Madison University (JMU) within the College of Integrated Science and Engineering 's Department of Computer Science . He has been at JMU since 2012, progressing from Assistant to Associate to Full Professor in 2024. Education: Ph.D. in Computer Science (2012), Old Dominion University M.Sc. in Computer Science (2006), Alexandria University B.Sc. in Computer Science (2002), Alexandria University Research Interests span Intelligent Transportation, Vehicular Ad-Hoc Networks (VANET), Wireless Sensor Networks (WSN), Network Security, Internet of Things (IoT), Cloud Computing, and Autonomous Vehicles. His work focuses on creating passenger-aware autonomous systems and improving transportation efficiency through low-cost IoT solutions. Selected Projects include: Independent Mobility for the Elderly (2019): $120,000 Jeffress Trust Award 4-VA Transit Bus Optimization (2015): $37,700 Madison Trust Smart Parking (2016): Cloud-based parking app STEM Outreach (2015): Mobile tech integration for K-12 education Scientific Awards : 2020 Madison Scholar 2018 Virginia Governor's Technology Award 2017 Outstanding Junior Faculty 2017 CFI Engaged Teacher Scholar 2014 IEEE MASS Travel Award Teaching includes courses like Autonomous Vehicles, Wireless Networking, Security & Forensics, and TCP/IP Networks. He emphasizes project-based learning, with students working on real-world problems like parking solutions and transit monitoring systems.

Shivam Guptaمشاهده پروفایل

دانشیار

• Procurement
• Supplier Management
• Innovation Management
• +۱ مورد دیگر

Shivam Gupta is an Associate Professor of Supply Chain Management and Analytics at the University of Nebraska-Lincoln's College of Business. He joined the university in 2018 as an Assistant Professor and was promoted to his current rank in 2024. His office is located in HLH 511K, Lincoln, NE. Education: Ph.D. in Management Science, The University of Texas at Dallas (2011-2016) M.Tech. in Civil Engineering, Indian Institute of Technology Kanpur (2009-2011) B.Tech. in Civil Engineering, Indian Institute of Technology Kanpur (2003-2007) His research expertise spans procurement systems, supplier relationship management, agricultural operations optimization, and incentive mechanism design. He develops analytical models to address challenges in supply chains, focusing on both theoretical frameworks and practical applications in agricultural markets. His work integrates game theory, optimization techniques, and economic analysis to solve complex operational problems. Gupta's publications demonstrate consistent focus on mechanism design and operational challenges, with recent work emphasizing dynamic incentive structures, procurement optimization, and agricultural policy impacts. His articles appear in premier journals including Management Science, Operations Research, and Production and Operations Management. Honors: First Place, INFORMS Public Sector OR Best Paper Competition (2015) Finalist, POMS SCM Student Paper Competition (2016) He teaches undergraduate and graduate courses in business analytics, including SCMA 350: Business Analytics/Information Analysis and SCMA 855: Prescriptive Analytics.

• Telecommunications
• Wireless Communication
• Terahertz Technology
• +۷ مورد دیگر

Kazuhiko Tamesue is an Associate Professor at the Faculty of Science and Engineering , Waseda University , with a focus on Terahertz Communication , Artificial Intelligence , and IoT Network Security . His academic journey spans academia and industry, including long-term roles at Panasonic Corporation (1991–2009) and current leadership in advanced wireless systems since 2022. Research Areas : Telecommunications, Wireless Hardware, Data Science, Machine Learning, Atmospheric Sensing Key Contributions : Pioneering 300GHz OFDM transceivers, AI-driven GNSS spoofing detection, and dual-frequency THz radar for cloud physics Projects : NICT-funded terahertz networks (2023–2024), ultra-low-latency systems (2022–2024), and security-enhancing radar technologies His 15 most recent publications (2024–2008) demonstrate expertise in (1) terahertz propagation for NTN/HAPS platforms, (2) machine learning for security (LSTM, GANs), and (3) next-generation IoT protocols (LPWAN, distributed ledger). He holds 20+ patents in antenna design, direct-conversion receivers, and power line communication. As an IEEE and IEICE member, he contributes to standards in 5G/6G and EMC.

Dirk Müllerمشاهده پروفایل

استاد

• Real-time systems
• Scheduling
• Software Engineering
• +۵ مورد دیگر

Dirk Müller is a Professor of Software Technology/Operating Systems at the Faculty of Computer Science/Mathematics, Dresden University of Applied Sciences (HTW Dresden). He has been in this position since 2016 and is an active member of the Faculty Council since June 2021. He was awarded IEEE Senior Member status in April 2023. His academic journey includes a doctorate in Engineering from the University of Kassel in 2006, habilitation at Chemnitz University of Technology in 2014, and prior research positions at Philipps University of Marburg and Florida State University. 1995-2002: Studies in Medical Informatics at University of Leipzig 2003-2006: Research Assistant/Doctoral Student at University of Kassel 2006-2008: Research Associate at Philipps University of Marburg 2008-2014: Academic Councillor at Chemnitz University of Technology 2014-2016: Private Lecturer at TU Chemnitz 2016-present: Professor at HTW Dresden Professor Müller's research focuses on real-time systems and scheduling, model-driven software development, digitalization in companies and administration, and the concept of information. His work particularly emphasizes Rust language applications in software engineering. He has published extensively on real-time scheduling algorithms, mixed-criticality systems, and embedded systems. His teaching responsibilities include Operating Systems I, Software Engineering I & II, Model-Driven Software Development, and Programming in Rust. His publication record shows a consistent focus on real-time systems, with a clear progression from theoretical scheduling algorithms to practical implementations. His recent work has expanded into public administration digitization and biometric conference systems, while maintaining his core expertise in scheduling theory. The publications demonstrate strong international collaboration, particularly with researchers like Matthias Werner, Alejandro Masrur, and Robert Baumgartl. IEEE Senior Member (2023) Erdős number: max. 4 Strict Erdős number: max. 5 Professor Müller actively supervises student theses, with over a dozen bachelor's and diploma theses completed between 2023-2025. His students work on diverse topics including Rust programming, workflow automation, user experience optimization, and real-time event processing. He serves as a reviewer for multiple prestigious journals including IEEE Transactions on Parallel and Distributed Systems, Real-Time Systems, and The Computer Journal. He also acts as Senior Editor for Computer Science Books at Versita. His laboratory work focuses on practical implementations of real-time systems, often using Raspberry Pi as a platform for traffic analysis and other embedded applications. His research group maintains strong connections with industry, as evidenced by the applied nature of student projects at companies like IntraConnect GmbH.

Ariane Fazenyمشاهده پروفایل

پژوهشگر

• Mixed Integer Optimization
• Game Theory
• Cryptography
• +۵ مورد دیگر

Ariane Fazeny is a Doctoral Researcher at SFB Transregio 154 since 2022, focusing on mathematical modeling, simulation, and optimization using Wasserstein metrics for gas networks. She also works as a Software Engineer for Siemens Mobility in Erlangen, contributing to powertrain technology and brake control systems validation. Educational Background Bachelor of Science (2017-2020) : Mathematics and Economics at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), with a thesis on mixed integer programs for air traffic fleet and crew assignment. Master of Science (2020-2022) : Mathematics and Economics at FAU, introducing generalized definitions for gradient, adjoint, and p-Laplacian operators on hypergraphs. Research Interests Mixed Integer Optimization Game Theory Cryptography Space Travel Fusion Power Mathematical Modeling Gas Network Optimization Hypergraph Theory Contact Email: ariane.fazeny@desy.de Affiliations Helmholtz Imaging at DESY (Notkestrasse 85, D-22607 Hamburg) SFB Transregio 154 subproject C06 LinkedIn profile

• Distributed Systems and Algorithms
• Decentralized search algorithms
• P2P systems and applications
• +۱۴ مورد دیگر

Angelo Furno is an Associate Professor at ENTPE (National School of Public Works) within Université Gustave Eiffel in Lyon, France. He serves as a researcher at the LICIT laboratory and collaborates with INRIA AGORA and the CITI-Lab of INSA-Lyon. His academic journey began at the University of Sannio in Italy where he earned his degree in Computer Engineering in 2010, followed by a PhD in Information Engineering completed in 2014 with a thesis titled "Scalable Service Composition in Autonomic Computing." After his PhD, he conducted post-doctoral research at both the University of Sannio and INRIA in Lyon. Furno's research spans multiple domains with a strong focus on transportation systems and network analysis. His work integrates distributed systems, mobile networking, and data science to address urban mobility challenges. He specializes in analyzing multi-source traffic data to support urban planning and transportation infrastructure management. His research interests include mobility pattern recognition, travel demand estimation, road-network modeling, land use detection, and social network analysis. He has developed expertise in graph analysis, clustering algorithms, and recommendation techniques applied to transportation contexts. His technical skills encompass Python, Scala, Java, and various web technologies. His publication record demonstrates consistent contributions to transportation research, with recent work focusing on park-and-ride systems optimization, traffic demand prediction using deep learning, privacy-preserving analysis of origin-destination data, and geometric classification of urban road networks. His research often addresses practical urban challenges, including pandemic-related transportation adaptations and accessibility analysis of transit networks in cities like Lyon. Best Paper Award (2012) Furno teaches courses on Intelligent Transportation Systems, Data Science and Machine Learning, and Big Data at ENTPE. His reviewing activities span numerous prestigious journals including IEEE Transactions on Mobile Computing, Transportation Research Part C, and Sensors. His collaborative work extends to multiple institutions across Europe, with particular emphasis on French research networks.

• real-time decision-making
• dynamic optimization under uncertainty
• online markets
• +۴ مورد دیگر

Vahideh Hosseinikhah Manshadi serves as the Michael H. Jordan Professor of Operations at Yale University's School of Management, with a secondary appointment as Assistant Professor in the Department of Statistics. Her academic profile reflects interdisciplinary expertise spanning operations research, statistics, and public health modeling. Professor Manshadi's research focuses on real-time decision-making and dynamic optimization under uncertainty , with significant applications across multiple domains. Her work addresses critical challenges in online markets , health-care operations , maritime port logistics , and matching markets . She has developed sophisticated optimization frameworks that account for network structures, user behavior in crowdsourcing platforms, and fair resource allocation in constrained environments. Analysis of her recent publications reveals a strong trend toward addressing complex matching problems in dynamic environments. Her research bridges theoretical optimization with practical applications in humanitarian contexts (refugee resettlement), platform economics, and social services. The interdisciplinary nature of her work is evident in publications spanning top journals in operations research, management science, and computer science. Professor Manshadi maintains an active research agenda as evidenced by consistent high-impact publications in premier journals including Management Science , Operations Research , and Manufacturing & Service Operations Management . Her work demonstrates significant methodological innovation while addressing real-world operational challenges across multiple sectors. Her academic leadership extends to the Public Health Modeling initiative at Yale, where her optimization expertise contributes to addressing complex public health challenges through quantitative approaches. While specific information about research grants and advising is not detailed in the provided text, her publication record indicates active collaboration with numerous researchers across different institutions.

Maryam Hamidiمشاهده پروفایل

دانشیار

• Reliability Engineering
• Statistical Data Analysis
• Maintenance Optimization
• +۹ مورد دیگر

Dr. Maryam Hamidi serves as Associate Professor in the Department of Industrial and Systems Engineering at Lamar University, where she leads research at the intersection of reliability engineering, data analytics, and transportation systems. Her work bridges theoretical frameworks with practical applications in maritime logistics and railway infrastructure, supported by active collaborations with government agencies and industry partners including Texas Department of Transportation and Buckeye Partners. Dr. Hamidi's academic foundation includes: Ph.D. in Systems and Industrial Engineering from the University of Arizona MBA from Sharif University of Technology B.S. in Electrical Engineering from Amir-Kabir University of Technology Her research program focuses on Reliability Engineering, Statistical Data Analysis, and Maintenance Optimization, with recent emphasis on applying machine learning to maritime transportation challenges. Current projects analyze Automatic Identification System (AIS) data to model vessel traffic patterns, predict congestion in narrow waterways like Houston Ship Channel, and assess port resiliency. She also develops game-theoretic models for warranty contracts and maintenance scheduling in railway systems, addressing critical infrastructure challenges through data-driven methodologies. Dr. Hamidi's publication trajectory shows increasing focus on AI-driven transportation analytics since 2020, with 80% of her recent work centered on maritime applications and machine learning. Her research consistently incorporates student collaboration, with doctoral candidates contributing to 90% of recent publications in transportation engineering journals. Dr. Hamidi's recognition includes: Certified Reliability Professional designation (2016) from ReliaSoft Society Hans Reiche Scholarship (2016) University of Arizona Student-Faculty Interaction Award (2015) Professional Opportunities Development Grant (2015) She currently mentors three doctoral students on projects involving port management resiliency, vessel traffic optimization, and industrial data science applications, while maintaining active industry partnerships that provide students with real-world research opportunities and career pathways. Her funded projects total over $500K, with current focus on AIS applications for Gulf Coast waterways and anomaly detection in energy infrastructure.