جست‌وجوی استاد و پژوهشگر

Marco Chiarandiniمشاهده پروفایل

دانشیار

• Operations Research
• Optimization Algorithms
• Integer Programming
• +۱۰ مورد دیگر

Marco Chiarandini is an Associate Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), with a secondary affiliation to the SDU Climate Cluster. His research focuses on Operations Research, Optimization Algorithms, and their applications in domains such as transportation, healthcare, and education. He has led or contributed to projects addressing dynamic traffic estimation, dementia care app design, and sustainable software development. Chiarandini has supervised students including P. Tampakis and C. McCarthy, and his work has been featured in interdisciplinary collaborations with institutions globally. His recent articles explore topics like goal-scoring prediction in football and urban traffic modeling, reflecting his expertise in data science and algorithmic design. His academic contributions span over 50 publications, emphasizing methodological advancements in optimization and heuristic algorithms. He actively participates in conferences and peer review, and has coordinated EU-funded projects like Data Science for University Management (2019–2023). Chiarandini’s teaching includes courses on linear programming and metaheuristics, integrating practical applications with theoretical foundations.

• Transportation Engineering
• Urban Rail Systems
• Timetable Optimization
• +۳ مورد دیگر

Res.Asst.Dr. Taha Yüksel is affiliated with the Civil Engineering Department at Istanbul Technical University. His work focuses on optimizing transportation systems, particularly in urban rail networks and energy-efficient solutions. Key research areas include timetable synchronization, passenger flow analysis, and applications of optimization algorithms like particle swarm optimization. Research interests span smart transportation systems, energy efficiency in railways, and advanced train control technologies. His contributions address challenges in transfer passenger management, regenerative braking utilization, and CBTC systems for safer, more efficient rail operations. No formal education details are provided in the profile. His publications (2017-2024) emphasize data-driven solutions for rail systems, with a focus on synchronization, energy optimization, and algorithmic approaches to operational efficiency.

Fatih Ibiliمشاهده پروفایل

استاد

• Family Law
• Private International Law
• International Child Abduction
• +۳ مورد دیگر

Prof. Fatih Ibili is a Professor of Family Law at the University of Groningen's Faculty of Law, holding the title of 'bijzonder Hoogleraar' in Personen-, Familie- en Jeugdrecht. He concurrently serves as a Judge at the Court of Appeal of The Hague and holds significant roles in legal governance, including membership in the Standing Government Commission on Private International Law and leadership of the Dutch Judiciary's Expert Group on Private International Law. His academic career includes a PhD from Vrije Universiteit Amsterdam (2006) on jurisdictional principles in private international law. Prior to his current roles, he contributed to the Supreme Court's Scientific Bureau (2006–2017), advising Advocates-General on civil litigation matters. Research focuses on private international law, family law, and comparative legal systems. Notable works include standard-setting publications like Nederlands internationaal personen- en familierecht (2017) and Internationale kinderontvoering (2019). His recent publications address EU legal frameworks (Brussels I-bis Regulation), marital property regimes, and Turkish civil law translations. Prof. Ibili has advised on critical legal reforms, including the Dutch government's 2016 review of parenthood laws, advocating for multi-parentage and surrogacy regulations. He actively participates in judicial training and lectures on family law, international child abduction, and civil procedure at Groningen. Recent professional milestones include his 2024 appointment as Advocate-General at the Supreme Court's Civil Division, marking a dual role in academia and high judicial office.

Banafsheh Khosraviمشاهده پروفایل

مدرس ارشد

• Operational Research
• Logistics
• Mathematical Modelling
• +۶ مورد دیگر

Dr Banafsheh Khosravi is a Senior Lecturer in Operational Research at the University of Portsmouth, affiliated with the School of Mathematics and Physics. She is a member of the Logistics, Operational Research and Analytics Research Group (LORA) and the Centre for Operational Research and Logistics (CORL). Her research focuses on mathematical modelling, combinatorial optimization, and applications in transportation and healthcare. She holds a PhD in Management Science from the University of Southampton, with earlier degrees in Industrial Engineering. Before joining Portsmouth, she worked at the University of Southampton's CORMSIS Centre and the University of Westminster's Health and Social Care Modelling Group. Dr Khosravi teaches Operational Research, Modern Computational Methods, and Supply Chain Management courses. She has supervised numerous academic projects and led industry-funded research with EPSRC, ESA, NHS, RSSB, and Arriva. Her work addresses challenges like railway scheduling, routing optimization, and healthcare capacity planning. She is a Fellow of the Higher Education Academy and contributes to professional organizations including The OR Society and IAROR. Her research trends span transportation logistics (railway rescheduling, electric vehicle routing) and healthcare systems (NHS patient activity forecasting). Recent work emphasizes risk-based surveillance and digital performance analysis in undersea infrastructure and insurance sectors. Collaborations with industry partners ensure practical impact across sectors like rail networks and space operations. Awards: Fellow of the Higher Education Academy (FHEA) Labs/Teams: LORA Group, CORL Centre, Intelligent Transport Research Cluster Grants: Funded by EPSRC, ESA, NHS, RSSB, Arriva

• Operations Research
• Combinatorial Optimization
• Operational Research
• +۳ مورد دیگر

Edmund Burke is a Professor and Vice Chancellor at Bangor University. His research focuses on operations research, combinatorial optimization, and algorithm development, with notable contributions to scheduling, hyper-heuristics, and airport ground movement optimization. He has published extensively on topics such as constraint propagation, routing algorithms, and multi-objective optimization. Research interests include algorithmic approaches for real-world problems, such as airport slot allocation, maintenance crew scheduling, and timetabling. His work often integrates heuristics and metaheuristics to tackle complex optimization challenges. Recent publications explore cutting-edge techniques like memetic algorithms for ground movement and hyper-heuristics for nurse rostering. Burke has contributed to interdisciplinary projects, including collaborations with Danish railways and airport logistics systems. He actively participates in university administration, organizing alumni events and engaging in outreach activities such as exhibitions and community days. His academic leadership roles underscore his commitment to both research excellence and institutional governance.

Luuk Veelenturfمشاهده پروفایل

دانشیار

• Real-time transport operations
• Mobility operations
• Public transport planning
• +۱۰ مورد دیگر

Luuk Veelenturf is an Associate Professor at the Department of Technology and Operations Management, Rotterdam School of Management, Erasmus University Rotterdam. His work bridges operations research and sustainable urban mobility, focusing on real-time decision systems in transport and logistics. His research interests include real-time transport operations , public transport planning , vehicle routing , and data-driven logistics . A significant portion of his work emphasizes sustainable transportation , aiming to reduce CO2 emissions and congestion through algorithmic improvements in scheduling and routing. The recent publications show a strong trend in solving complex logistics problems using advanced optimization techniques such as Mixed-Integer Programming and Adaptive Large Neighborhood Search . These works span domains including last-mile delivery , passenger-oriented timetabling , and robust train rescheduling , reflecting a consistent focus on resilience and efficiency in transportation systems. Scientific Awards: No scientific awards mentioned in the provided text. Advising and Grants: Luuk Veelenturf has co-supervised PhD research, including the thesis on vehicle routing with multiple service agreements. While specific grants are not listed, his collaboration with prominent researchers and publication in high-impact journals suggest active research funding. His work contributes to UN Sustainable Development Goals on sustainable cities and climate action. Labs and Teams: He is part of the research network within the Department of Technology and Operations Management at RSM, collaborating extensively on transport and logistics optimization. His work involves developing algorithms and models for real-world applications in public transport and city logistics, likely within a structured research group or lab focused on operations and analytics.

• Operational Research
• Combinatorial Optimisation
• Mathematical Programming
• +۷ مورد دیگر

Greet Vanden Berghe is a full professor at the Faculty of Engineering Technology of KU Leuven. She leads the Subdivision Combinatorial Optimisation and Decision Support at Ghent and Aalst Campuses, and contributes to research networks like Leuven.AI and LIM. Her work focuses on industrial combinatorial optimization problems through mathematical programming, heuristics, and decomposition approaches. Affiliations: Numerical Analysis and Applied Mathematics (NUMA), Leuven.AI, LIM Institute Research: Logistics optimization, personnel scheduling, vehicle routing, and algorithm development for industrial decision support Projects: MoVeRS (Modular Vehicle Routing Solver), Trustworthy Algorithms for Industrial Decisions, Fairness in Allocation Problems, and Electric Vehicle Charging Station Optimization Her research emphasizes bridging theoretical advancements with real-world industrial challenges, particularly in maritime logistics, healthcare scheduling, and production planning. She has developed scalable solvers and integrated legal constraints into routing algorithms.

• Artificial Intelligence
• Optimization and Learning
• Vehicle Routing Problems
• +۳ مورد دیگر

Dr. Neil Urquhart is a Lecturer at the School of Computing Engineering and the Built Environment , Edinburgh Napier University , specializing in computational intelligence and optimization. He actively contributes to research in quality-diversity algorithms, vehicle routing problems, and socio-technical systems. Education: PhD in Computing (Edinburgh Napier University) His research focuses on: Evolutionary algorithms for delivery optimization Domain-specific languages for traffic simulation Human-AI trust dynamics in socio-technical systems Multi-stakeholder decision support frameworks Recent publications highlight: Real-world applications of nature-inspired optimization Empirical evaluation of domain-specific languages Micro-depot routing for sustainable logistics MAP-Elites for workforce scheduling Scientific contributions: Elected member of SPECIES (Society for Evolutionary Computing in Europe) Collaborative grants: £7,495 (2025) - VanFill Innovation Voucher £5,000 (2021) - ChargeBreak EV Suitability Tool £5,000 (2018) - Netmedia AI/Optimization Voucher £4,920 (2017) - Bendifa Food Delivery Heuristics £19,807 (2016) - DataLab LarderLoad Food Analytics £5,000 (2015) - Food Services Analytics

• Database Systems
• Information Visualization
• Bioinformatics
• +۵ مورد دیگر

Andrew Cumming is a Researcher at the School of Computing Engineering and the Built Environment , Edinburgh Napier University. His work spans database systems, information visualization, and computational biology, with a focus on SQL education and microarray data analysis. Research Interests Database technologies and SQL optimization Animated visualization for biological time-course data Interactive graphics in virtual reality environments Automated educational assessment systems Genetic algorithms for timetabling Publications (sorted by year) highlight his contributions to: 2014: Polygonal voxel rendering techniques 2007: SQL best practices and data digging methodologies 2005: Dynamic scatter-plot visualization for gene activity 2004: Automated SQL marking systems 2000: Constraint-based timetabling algorithms Contact: A.Cumming@napier.ac.uk | a.cumming@napier.ac.uk

• Food Science and Technology
• Agricultural Sciences
• Environmental Sciences
• +۴ مورد دیگر

Massimo Mozzon is an Associate Professor at the Department of Agricultural, Food and Environmental Sciences (D3A), Faculty of Agriculture, Università Politecnica delle Marche (UNIVPM). His academic work is rooted in the scientific sector of Food Science and Technology (AGRI-07/A), reflecting a strong focus on food-related research and innovation. His research interests span Food Science and Technology , Food Safety , Food Chemistry , Food Processing , and Sustainable Agriculture . Given his departmental affiliation, his work likely integrates agricultural and environmental dimensions into food systems, contributing to sustainable and safe food production. While specific publications and research projects are accessible through the university's IRIS repository and research portals, the overarching themes emphasize technological and scientific advancements in food and agriculture. Prof. Mozzon is actively involved in teaching and academic supervision, with course materials, timetables, and announcements available through the university's educational platforms. He contributes to the academic life of UNIVPM through structured lessons and student guidance within the agricultural sciences domain. Professional Affiliations: Department of Agricultural, Food and Environmental Sciences (D3A), UNIVPM Faculty of Agriculture, Università Politecnica delle Marche Contact Information: Email: m.mozzon@staff.univpm.it Phone: 071-2204926 Address: Via Brecce Bianche, Ancona, Italy

Eric Pinsonمشاهده پروفایل

استاد

• Combinatorial Optimization
• Scheduling Theory
• Transport Logistics
• +۳ مورد دیگر

Eric Pinson is a Professor at the University of Angers (UCO) within the Faculty of Sciences. He holds an HDR (Accreditation to Supervise Research) from Université Pierre et Marie Curie (Paris VI) since 1994 and a PhD in Computer Science and Applied Mathematics from the same institution in 1988. He leads the LigéRO regional project (Loire Operational Research Group) and is an integrated member of LARIS (Angevin Research Laboratory in Systems Engineering), part of team EA-7315. Education: PhD in Computer Science and Applied Mathematics, Université Paris VI, 1988 HDR in Research Supervision, Université Paris VI, 1994 Research Interests: His work focuses on Combinatorial Optimization , particularly in scheduling theory and transport logistics. Key areas include algorithm development for scheduling problems (job-shop, flow-shop, maintenance planning), resource allocation in production systems, and optimization under constraints such as human resource limitations and energy considerations. His contributions span theoretical advancements and practical applications in renewable energy maintenance (e.g., wind turbines) and industrial logistics. Publications Trends: Recent work emphasizes algorithmic efficiency (O(n²) scheduling adjustments, energy function management) and industrial applications (wind farm maintenance, multi-skill project scheduling). Earlier publications established foundational scheduling algorithms and constraint-based optimization techniques. Scientific Awards: No specific awards listed, though his sustained contributions indicate significant recognition within the operations research community. Advising & Grants: Supervised at least one PhD student (Aurélien Froger, 2012–2016). Involved in collaborative projects including the DC-GNN program for real-world data clustering using graph neural networks. Labs & Teams: Primary affiliations include LARIS (Systems Engineering) and the LigéRO network, fostering regional operational research collaboration.

• Oral Cancer Diagnosis
• Medical Imaging
• Artificial Intelligence in Healthcare
• +۳ مورد دیگر

Dr. Pilana Hettiarachchi is a Casual Research Assistant and Casual Academic at the School of Dentistry, University of Queensland. They also serve as a Casual Examination Supervisor in Examinations and Timetable Services. Their work focuses on leveraging artificial intelligence and medical imaging for early detection of oral cancers and oral potentially malignant disorders. Research interests include the application of machine learning to medical diagnostics, development of annotated datasets for oral health, and multimodal neural network pipelines for disease detection. Recent contributions highlight advancements in AI-assisted early diagnosis through collaborative research with multiple institutions. No scientific awards or grants are explicitly listed. While no formal advisees are documented, their publications involve collaborative teams across disciplines. No specific lab affiliations are mentioned, though work is likely integrated with clinical and computational research groups.

• Mathematics
• Number Theory
• Analysis
• +۴ مورد دیگر

Dr. Joshua Friedman is a Professor in the Department of Math and Science at the United States Merchant Marine Academy (USMMA) since 2005. His research focuses on advanced mathematical analysis including Selberg trace formulas, automorphic forms, zeta functions, and Fuchsian/Kleinian groups. He has contributed to areas such as analytic number theory, spectral geometry, and combinatorial optimization through his publications. Teaching interests span all mathematics courses. Education: PhD and MA in Mathematics (Stony Brook University), BS in Math & Physics (Binghamton University) His work bridges pure mathematics with applied problems like automated timetabling using integer programming. Recent research emphasizes zeta functions, regularized determinants, and scattering theory applications. Notable contributions include studies on Bessel function integrals linked to Mahler measure (2022), deep learning approaches to graph theory problems (2021), and effective bounds in modular form analysis (2019). His 2016 papers address scattering determinants and hyperbolic manifold applications.

Stefan Andresمشاهده پروفایل

مدرس

• Urban Planning
• Spatial Analysis
• Geography
• +۳ مورد دیگر

Stefan Andres is a Lecturer at the Department of Urban and Spatial Planning within the School of Architecture and Urban Planning at the University of Applied Sciences Erfurt. He serves as Degree Program Coordinator, Chair of the Academic Committee, and Timetable Coordinator & Placement Officer. His office hours are held on Mondays from 1-2 p.m. in room N.208, Schlüterstraße 1, Erfurt. Position: Lecturer Institution: University of Applied Sciences Erfurt School: Architecture and Urban Planning Department: Urban and Spatial Planning Responsibilities: Degree Program Coordinator, Academic Committee Chair, Timetable Coordinator & Placement Officer His research focuses on urban planning and spatial analysis, with an emphasis on practical applications in regional development and city planning. His work intersects with broader disciplines including geography and environmental studies. Contact: stefan.andres@fh-erfurt.de

Björn Morénمشاهده پروفایل

استادیار

• Mathematical Optimization
• Brachytherapy Treatment Planning
• Radiotherapy
• +۷ مورد دیگر

Björn Morén is an Assistant Professor in the Department of Mathematics at Linköping University, Sweden. He is affiliated with the Division of Applied Mathematics (TIMA), where his research focuses on mathematical optimization applied to brachytherapy treatment planning in radiation oncology. His work aims to improve cancer treatment outcomes through advanced computational models that enhance precision and robustness in radiotherapy. Research Interests: His primary research lies at the intersection of applied mathematics and medical physics. He specializes in developing and analyzing mathematical optimization models for high-dose-rate (HDR) brachytherapy, particularly for prostate and cervical cancers. His work addresses critical challenges such as rotational and positional uncertainties, dwell time optimization, and automated plan validation. He seeks to bridge the gap between manual clinical planning and algorithm-driven optimization to improve dosimetric outcomes and reduce complications. Publication Trends: His recent publications (2021–2025) demonstrate a consistent focus on robust optimization techniques in brachytherapy. Themes include uncertainty mitigation, dosimetric evaluation, inverse planning, and automation in treatment workflows. His interdisciplinary work combines operations research, medical imaging, and clinical oncology, reflecting strong collaboration across physics and medicine. Scientific Awards: No awards or honors are mentioned in the provided text. Advising and Grants: There is no information available about students advised or research grants received. However, his active publication record suggests ongoing funded research and potential mentorship roles within his research group. Labs and Teams: Björn Morén is part of a multidisciplinary research group at Linköping University focused on brachytherapy treatment planning. This group collaborates on developing optimization models for clinical use, working closely with medical physicists and oncologists to translate mathematical innovations into practical healthcare solutions.