جست‌وجوی استاد و پژوهشگر

• Operations Research
• Mathematical Programming
• Transportation Planning
• +۷ مورد دیگر

Eva Barrena Algara is a Professor at the Department of Economics, Quantitative Methods, and Economic History at the University Pablo de Olavide. Her work bridges operations research, transportation planning, and mathematical optimization, with a focus on urban rail systems and network design. Her research interests include: Railway timetabling and scheduling under dynamic passenger demand Mixed-integer programming for transportation network optimization Multiplex network analysis in collective transportation systems Heuristic and metaheuristic algorithms for coordinated vehicle routing Waste logistics and humanitarian relief routing applications Her publications since 2013 demonstrate expertise in train unit scheduling, demand-adapted timetables, and network transferability analysis, often using Gröbner bases and adaptive algorithms. She collaborates with researchers like Gilbert Laporte and David Canca, with papers appearing in journals such as Computers & Operations Research and European Journal of Operational Research . Key application areas include metro systems, disaster response logistics, and waste collection optimization. She serves on the editorial board or as reviewer for transportation and operations research journals, and her work has been cited over 45 times. Her methodological contributions span exact formulations, biased-randomized heuristics, and stochastic modeling for time-dependent problems.

Marcel Mongeauمشاهده پروفایل

استاد

• Operations Research
• Global Optimization
• Numerical Optimization
• +۵ مورد دیگر

Marcel Mongeau is a Professor in Operations Research at the École Nationale de l'Aviation Civile (ENAC) in Toulouse, France, affiliated with the OPTIM team under the MORO axis . His research focuses on operational research, global optimization, numerical optimization, and mixed-integer programming, with applications in aeronautics, chemical engineering, life sciences, and other industries. Education PhD in Combinatorics & Optimization (1991), University of Waterloo, Canada MSc in Mathematics (1987), University of Montreal, Canada BSc in Mathematics (1985), University of Montreal, Canada Habilitation to Direct Research (2003), Paul Sabatier University, France Research Interests : Mongeau's work addresses complex optimization problems through mathematical modeling and algorithm development. Key areas include aircraft trajectory planning, contrail avoidance, stochastic programming, and multi-modal transportation optimization. His methodologies integrate exact optimization, heuristic approaches, and computational modeling. Publications Trends : Recent publications emphasize air traffic flow management , contrail-safe trajectories , stochastic aircraft scheduling , and multi-modal transportation synchronization . Applications span environmental impact minimization, machining efficiency, and climate-aware aviation planning. Scientific Recognition : He is a Member of the Academy of Technologies , reflecting his contributions to applied mathematical sciences. Advising & Grants : Mongeau has supervised PhD students and postdoctoral fellows, particularly in optimization and operational research. His research has been supported through collaborations with institutions like IBM, INRIA, and CNRS. Labs & Teams : He is associated with the OPTIM team at ENAC and previously worked with the MOGISA group at LAAS-CNRS and the Optimisation & Interactions group at Paul Sabatier University.

• Ecology
• Environmental Science
• Plant Biology
• +۳ مورد دیگر

Dr. Susanne Walford is a Lecturer in the Department of Biology at Lakehead University. She has been employed since September 1997, initially working in Dr. Peter Lee's Environmental Lab (LUEL) until 2007 and transitioning to teaching roles as a Contract Lecturer. Academic Qualifications: B.Sc. in Chemistry from Lakehead University (1994) Ph.D. in Biotechnology from Lakehead University (2011) Her teaching focuses on foundational and specialized biology courses, including Plant Biology, Wetland Ecology, and Limnology. She has been involved in laboratory instruction and curriculum development within the Department of Biology. Her research interests align with environmental and ecological studies, particularly through her work at the Lakehead University Environmental Lab (LUEL) and its role within the Lakehead University Centre for Analytical Services (LUCAS). Dr. Walford contributes to departmental activities such as timetable scheduling, lab room booking, and curriculum committee work. She is also engaged in outreach initiatives and recruitment efforts at Lakehead University.

• Biomedical Image Processing
• Image Processing
• Medical Imaging
• +۱ مورد دیگر

Zhu Chen is a Researcher at RWTH Aachen University within the Faculty of Electrical Engineering and Information Technology, holding dual affiliations with the Chair of Imaging and Image Processing (led by Prof. Volkmar Schulz) and the Junior Professorship for Biomedical Image Processing (under Prof. Johannes Stegmaier). She operates from offices in ICT Cube 1 (Room 111) and ICT Cube 2 (Room 138), contributing to advanced research in medical and biological image analysis while holding an M.Sc. degree. Research Interests Chen's primary focus spans biomedical image processing, medical imaging, and computer vision with specialized applications in animal behavior tracking and embryonic development analysis. Her methodology integrates unsupervised learning for 3D temporal alignment of biological structures and foundation models for annotation streamlining, targeting efficiency improvements in developmental biology research through computational innovation. Publication Trends Analysis reveals a strategic pivot from energy management systems for hybrid transportation (2021-2022 publications on fuel cell trains/buses) to biomedical imaging (2023-2025). Current work emphasizes AI-driven solutions for biological image analysis, particularly in zebrafish embryo studies and automated animal tracking, demonstrating applied machine learning expertise across divergent scientific domains. Scientific Awards No documented scientific awards, fellowships, or honors were identified in available institutional records. Advising and Grants Public sources contain no verifiable information regarding student supervision, grant acquisitions, or funded research projects under Chen's direct leadership. Laboratory and Team Affiliations Chen actively collaborates within the Chair of Imaging and Image Processing's scientific team alongside researchers including Ankit Amrutkar and Henning Konermann. She utilizes specialized facilities such as optical systems research areas and MRI laboratories, contributing to the institute's mission in medical image processing and computational biology.

• Algorithm design and analysis
• Combinatorial optimization
• Exact algorithms
• +۶ مورد دیگر

Fabio Guido Mario Salassa serves as an Associate Professor in the Department of Management and Production Engineering (DIGEP) at the Polytechnic University of Turin. He is a member of the Interdepartmental Center Ec-L - Energy Center Lab and actively participates in the College of Management and Production Engineering as well as the College of Computer, Film, and Mechatronics Engineering as an invited member. His research focuses on algorithm design, combinatorial optimization, exact algorithms, metaheuristics, and scheduling problems. His work bridges theoretical computer science with industrial applications, particularly in operations research and mathematical optimization. He specializes in developing optimization models for real-world industrial challenges including production scheduling, transportation logistics, and resource allocation. His recent publications demonstrate a strong focus on scheduling theory with applications to manufacturing systems, parallel machine environments, and workforce management. The research shows consistent contributions to solving complex optimization problems through innovative algorithmic approaches and mathematical formulations. Professor Salassa has supervised PhD student Elena Rener, whose thesis focused on Single Machine Rescheduling for New Orders. He has secured multiple commercial research contracts with companies including Protea S.r.l. and Sandeza S.r.l., focusing on optimization algorithms for waste calculation, production scheduling, and transportation problems. He teaches Operations Research and Optimization for Problem Solving courses across multiple academic programs including Management Engineering and Computer Science Engineering. His teaching spans from Bachelor to PhD levels, with recent courses scheduled through the 2025/2026 academic year.

• Psychopharmacology
• Perinatal Psychiatry
• Child Neurodevelopment
• +۴ مورد دیگر

Lisanne Schrijver is an active Researcher in the Department of Psychiatry at Erasmus University Medical Center's Faculty of Medicine. Her work focuses on the intersection of psychopharmacology and perinatal mental health, with particular expertise in how psychiatric medications affect pregnancy outcomes and child development. Dr. Schrijver's research interests center on psychopharmacology during pregnancy, specifically examining the effects of lithium and antipsychotics on fetal development and long-term neurocognitive outcomes. Her work bridges clinical psychiatry with developmental neuroscience, addressing critical questions about medication safety during pregnancy for women with bipolar disorder and other serious mental illnesses. She employs rigorous methodologies including cohort studies, systematic reviews, and meta-analyses to generate evidence that informs clinical practice guidelines. Her publication record reveals a clear trajectory of increasingly sophisticated research on perinatal psychopharmacology, with recent work focusing on dose-response relationships and long-term developmental outcomes. The 2024 publication on lithium serum levels during pregnancy represents the cutting edge of her current research program, building upon her foundational 2018 systematic review that has been highly influential (50+ citations). Dr. Schrijver collaborates extensively with leading researchers in the field including Bergink, Kamperman, Hoogendijk, and Poels, forming a prominent research group at Erasmus MC focused on reproductive psychiatry. Her work has garnered significant attention, with multiple publications receiving news mentions and substantial readership on academic platforms.

• Artificial Intelligence
• Explainable AI
• Human-Computer Interaction
• +۵ مورد دیگر

Yunfeng Zhang is a Professor at Shandong University of Finance and Economics specializing in Artificial Intelligence with significant contributions to Explainable AI, Human-Computer Interaction, and Machine Learning. His research spans computer vision, fairness in AI, and robotics applications across diverse domains including transportation, agriculture, and cybersecurity. Zhang has established strong international collaborations with IBM Research (notably with Kush Varshney and Q. Vera Liao) and publishes extensively in top venues like CHI, KDD, and IEEE Transactions. His research interests focus on making AI systems transparent and trustworthy through the AI Explainability 360 toolkit development since 2020, human-AI collaboration frameworks, and fairness optimization in machine learning. Recent work shows a strategic pivot toward applied AI problems including urban rail transit optimization, agricultural robotics for citrus detection, and VR-enhanced education systems in China. Zhang's publications demonstrate exceptional breadth across both theoretical foundations and real-world implementations of AI technologies. Zhang's recent publications (2023-2025) reveal strong trends in multimodal AI applications, with significant work in computer vision for remote sensing and industrial automation, reinforcement learning for transportation systems, and educational technology innovations. His work consistently bridges technical AI development with human-centered design principles, particularly evident in his CHI publications on human-AI collaboration interfaces. Co-developer of the influential AI Explainability 360 open-source toolkit (JMLR 2020) Key contributor to Uncertainty Quantification 360 framework Active participant in ACM FAccT conferences on AI fairness Principal investigator on multiple Chinese national research grants for AI applications Zhang leads research teams developing practical AI solutions for Chinese industry challenges, particularly in transportation optimization and agricultural technology. His lab maintains strong industry partnerships with Chinese railway authorities and agricultural technology firms, focusing on implementing AI systems that address specific local infrastructure and productivity challenges while maintaining rigorous academic standards.

• Graph Theory
• Combinatorial Optimization
• Logistics
• +۴ مورد دیگر

David Schindl is a Lecturer in the Department of Informatics at the University of Fribourg's Faculty of Management, Economics and Social Sciences, with his primary appointment at Haute Ecole de Gestion (HEG) Geneva since 2008. His research bridges graph theory and combinatorial optimization with practical applications in logistics, vehicle routing, and academic timetabling systems. Education: PhD in Mathematics, EPFL, 2004 Research Interests: Dr. Schindl specializes in theoretical graph structures—including k-community detection, clique-width parameterization, and EPG graphs—with direct applications to transportation logistics, waste management, and educational scheduling. His work on course/exam timetabling at HEG since 2012 demonstrates his commitment to solving real-world operational challenges through mathematical optimization. Research Trends: Analysis of his 2020-2025 publications reveals sustained focus on community structures in graph classes and width-parameterized algorithms, alongside growing emphasis on sustainable logistics. His waste collection project exemplifies the environmental application of combinatorial optimization to reduce municipal fuel consumption and emissions. Grants and Projects: Efficient and sustainable waste collection (2019-2022): Funded by Innovation, this project developed optimization algorithms for waste collection routing in Swiss municipalities using electric vehicles and intermediate depots to minimize environmental impact. Teaching: At the University of Fribourg, he teaches decision support and graph theory courses. At HEG Geneva, he delivers instruction in statistics and mathematics for economics students, emphasizing practical applications of quantitative methods.

Anders Petersonمشاهده پروفایل

دانشیار

• Transportation Planning
• Railway Systems Engineering
• Operations Research
• +۳ مورد دیگر

Anders Peterson is a Senior Associate Professor and Head of Unit at the Department of Science and Technology (ITN) within Linköping University's Communications and Transport Systems (KTS) program. His research focuses on railway and public transport planning, optimization, and simulation, with particular emphasis on decision support systems for strategic investments, scheduling, and operational planning. He leads the national research program Capacity in the Railway Traffic System (KAJT), collaborating with institutions like RISE and VTI, and participates in international networks such as IAROR. He teaches courses in traffic infrastructure and planning, including TNK061 and TNK098, and supervises doctoral, master's, and bachelor's thesis projects. His work is funded by the Swedish Transport Administration (Trafikverket), emphasizing practical solutions for railway capacity and reliability. His research addresses challenges in timetable robustness, infrastructure modeling, and intermodal transport efficiency. Collaboration with industry partners ensures his work bridges academic and applied contexts, contributing to both theoretical advancements and real-world transportation systems improvements.

Rolf van Lieshoutمشاهده پروفایل

استادیار

• Transportation Logistics
• Operations Research
• Public Transport Optimization
• +۳ مورد دیگر

Rolf van Lieshout is an Assistant Professor in the Department of Operations Planning Accounting & Control at Eindhoven University of Technology (TU/e), within the School of Industrial Engineering and Innovation Sciences. His research focuses on applying advanced analytical techniques to improve decision-making in transportation and logistics, particularly in public transport systems. He holds a PhD (cum laude) and degrees in Econometrics from Erasmus University Rotterdam. His work addresses strategic planning through real-time rescheduling, with a recent emphasis on evaluating public transport service quality and integrating freight and passenger rail systems. Education: Bachelor’s in Econometrics and Operations Research, Erasmus University Rotterdam Master’s in Econometrics and Management Science (Operations Research/Quantitative Logistics), Erasmus University Rotterdam PhD in Operations Research (cum laude), Erasmus University Rotterdam Research Interests: Transportation logistics, operations research, railway engineering, sustainable transportation, and public transit optimization. He explores topics like electric vehicle routing, infrastructure scheduling, and disruption management using computational methods. Teaching: Courses include Decision-making in Transport & Mobility, Large-scale Optimization for Transport & Logistics, and Microeconomics. He has supervised 25 student projects (names not specified). Awards: Best Teacher Master Operations Management and Logistics (2025) Grants & Projects: His research has been published in top journals like Transportation Science, addressing challenges in vehicle scheduling, infrastructure optimization, and self-organizing transport systems. Collaborations focus on railway systems and sustainable urban logistics.

Zahra Ansarilariمشاهده پروفایل

مدرس

• Transportation Systems
• Transit Optimization
• Public Transit Networks
• +۲ مورد دیگر

Zahra Ansarilari is a Lecturer in the Department of Civil, Environmental and Geomatic Engineering at ETH Zurich. She holds a PhD in Transportation Engineering from the University of Toronto and professional experience includes roles as Data Scientist at NeshanMaps and Transport Planner at AAVAND-e Tarh-o Andishe. Her research develops optimization models for public transit systems. Key research areas include synchronized timetabling, transfer coordination, and capacity-aware scheduling for multimodal networks. Methodological approaches integrate mixed-integer programming, Lagrangian relaxation, and stochastic optimization to improve passenger experience and operational efficiency. Recent publications focus on reducing transfer waiting times through novel optimization frameworks that account for vehicle capacities, dwell times, and network uncertainties. Applied work includes collaborations with transit agencies to implement scheduling improvements.

• Transportation Engineering
• Intelligent Transport Systems (ITS)
• Autonomous Vehicles
• +۵ مورد دیگر

Dr. Tang Li is a Researcher in the Urban Systems Laboratory (USL) and Centre for Transport Studies (CTS) at Imperial College London, affiliated with the Department of Civil and Environmental Engineering under the Faculty of Engineering. He holds a BEng from Beijing Jiao Tong University, an MSc from Imperial College London and University College London, and a PhD from Imperial College London. His research focuses on modeling autonomous and human-driven vehicle interactions, intelligent transport systems (ITS), connected autonomous vehicles (CAVs), and urban mobility optimization. He has contributed to projects like E-FLEX (Innovate UK-funded £3.6 million initiative) exploring electric vehicle energy trading. His work spans transport policy, energy systems, and sustainable development in emerging economies, with a strong emphasis on data-driven methodologies such as stated preference experiments and discrete choice modeling. Dr. Li’s research integrates technical and socio-economic dimensions, addressing challenges in Sub-Saharan Africa’s transport-energy nexus and urban rail systems optimization. He collaborates on open-source tools like OSeMobility for mobility modeling and advocates for equitable climate-compatible transport pathways. His technical expertise includes urban systems analysis, traffic signal coordination, and cooperative control strategies for energy efficiency in rail networks. Grants: E-FLEX Project (£3.64M, Innovate UK, 2018-2021) focused on real-world energy flexibility through electric vehicle-to-grid integration. His projects highlight interdisciplinary approaches to urban mobility challenges, blending engineering solutions with policy analysis. Labs/Teams: Active contributor to Imperial College’s Urban Systems Laboratory (USL) and Centre for Transport Studies (CTS), advancing innovative transport solutions through computational modeling and empirical research.

Esraa Abdelhalimمشاهده پروفایل

استادیار

• Artificial Intelligence
• Human-AI Collaboration
• Machine Learning Algorithms
• +۵ مورد دیگر

Esraa Abdelhalim is an Assistant Professor in Management Science at the Odette School of Business, University of Windsor. With a Ph.D. in Data Analytics from McMaster University (2023), she specializes in Human-AI collaboration and algorithmic systems. She previously served as a Research and Teaching Assistant at McMaster University and held academic positions at Alexandria University. Education: Ph.D. in Data Analytics (McMaster University, 2023), M.Sc. in Management Information Systems (Alexandria University, 2015), B.Sc. in Management Information Systems (Alexandria University, 2009) Her research focuses on Artificial Intelligence and Machine Learning applications in organizational contexts, particularly examining Human-AI collaboration and Generative AI systems. She has developed algorithmic frameworks for university timetabling optimization and information visibility systems. Recent publications highlight her work on ethical AI frameworks for chatbots and educational infrastructure optimization. Her 2024 paper in Business Horizons introduces diversity and inclusion safeguards in conversational AI systems. Scientific Awards: Professor of the Year (Odette Commerce Society, 2024) Doctoral Consortium (ICIS, 2020) TechWomen Emerging Leader Award (2014) Professional certifications include Data Science and Big Data Analytics (Dell EMC, 2017) and Certified Mentor (Mentoring Standard Foundation, 2015). She has presented at international conferences including INFORMS M&SOM and WASET.

Stefan Guerickeمشاهده پروفایل

استاد

• Data Science
• Business Intelligence
• Operations Research
• +۳ مورد دیگر

Stefan Guericke is a Professor of Business Informatics at the University of Applied Sciences Osnabrück since 2022, specializing in Data Science and Business Intelligence. He holds a PhD in Decision Support & Operations Research from the University of Paderborn (2014) and a degree in Business Informatics from the University of Paderborn and Beijing Institute of Technology. His professional experience includes roles at A.P. Møller-Mærsk, where he served as Senior Engineering Manager and Senior Data Scientist, focusing on logistics optimization and data-driven solutions. Research interests span logistics network design, mathematical optimization, containerization problems, and the application of advanced analytics in microservices architectures. He has contributed to solving complex problems in liner shipping, cargo allocation, and fleet deployment through both heuristic and exact methods. His work bridges academic research and industrial applications, emphasizing practical solutions for supply chain challenges. Teaching responsibilities include courses on Data Science fundamentals, Deep Learning, Operations Research, and Statistics. He is affiliated with the Faculty of Management, Culture, and Technology at HSO, contributing to interdisciplinary projects and student mentoring.

Jeffrey L. Lehmanمشاهده پروفایل

استاد

• Computer Science
• XML Applications
• Scheduling Algorithms
• +۳ مورد دیگر

Jeffrey L. Lehman serves as Associate Dean of the Sciences, Professor of Computer Science, and Department Chair at Huntington University. He joined the faculty in 1998 after teaching at William Penn College from 1993 to 1998. Dr. Lehman's educational background includes: BA in Computer Science from Bluffton College (1991) MS in Applied Computer Science from Illinois State University (1993) PhD in Computer Science from Nova Southeastern University (2004) His research focuses on computer science applications in educational settings, particularly XML applications for university course timetabling systems as evidenced by his dissertation titled "An XML Application for the University Course Timetabling Problem." His expertise spans scheduling algorithms, educational technology, and XML-based solutions for academic administrative challenges. Dr. Lehman is an active member of the professional community, belonging to the Association of Computing Machinery (ACM) and the Consortium for Computing Sciences in Colleges (CCSC). He has also contributed internationally, having taught a summer course at the Russian American Christian University in Moscow in 1999. His professional affiliations include: Association of Computing Machinery (ACM) Consortium for Computing Sciences in Colleges (CCSC)