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Hongtao YangView profile

Associate Professor

• Numerical Analysis
• Computational Finance
• Partial Differential Equations
• +3 more

Hongtao Yang is an Associate Professor in the Department of Mathematical Sciences at the University of Nevada, Las Vegas (UNLV). His research focuses on numerical analysis and its applications, particularly in computational finance and numerical methods for partial differential equations. He is affiliated with the Center for Applied Math & Statistics at SEB Program Group. His expertise includes pricing financial derivatives, calibrating interest rate models, and developing numerical methods for complex financial and engineering problems. Key areas of application include option pricing under stochastic volatility models, supply chain optimization with environmental considerations, and tax policy modeling using stochastic differential equations. Recent work emphasizes regime-switching models in finance, low-carbon supply chain collaboration strategies, and advanced numerical techniques like finite volume and discontinuous Galerkin methods. His research bridges theoretical numerical analysis with practical applications in economics, environmental policy, and computational finance. Dr. Yang's articles highlight contributions to American option valuation, carbon emissions reduction strategies, and stochastic control in financial systems. He has developed innovative numerical algorithms addressing free boundary problems and multi-objective optimization challenges.

An Yu ChenView profile

Researcher

• Science of Science
• Technology Policy
• Green Technologies
• +6 more

An Yu Chen is a Researcher at Alliance Manchester Business School within the IMP Innovation, Strategy and Sustainability department. She holds a Doctor of Philosophy from the same institution. Her research focuses on analyzing linkages between science and technology, with a particular emphasis on green technologies and knowledge flows. This work contributes to UN Sustainable Development Goals, especially SDG 13 (Climate Action). Her expertise includes developing belief rule-based systems for decision-making, social network analysis, and complex systems modeling. Key research areas involve understanding how social networks influence decision-making processes, optimizing group consensus mechanisms, and applying evidential reasoning to risk assessment and fault diagnosis. Notable contributions include frameworks for Arctic navigation risk assessment, R&D project evaluation systems using belief rule bases, and models analyzing vaccine adoption behaviors in social networks. Her work bridges theoretical advancements in decision science with practical applications in sustainability, healthcare, and logistics. She has extensively published on topics like trust propagation in social networks, entropy-based vulnerability analysis of infrastructure systems, and hybrid algorithms for optimization problems. Her interdisciplinary approach integrates methods from computer science, statistics, and management science to address real-world challenges in innovation and sustainability.

David KutnerView profile

Research Fellow

• Graph Theory
• Computational Complexity
• Temporal Graphs

David Kutner is a Career Development Fellow (Research Fellow) in the Department of Computer Science at Durham University, where he concurrently pursues postgraduate studies. His research bridges theoretical computer science and real-world applications, focusing on dynamic network problems. Education Kutner earned his PhD (2021-2025) from Durham University with a thesis titled Eventful graphs: the computational complexity of recognizing and realizing properties in changing networks , supervised by Dr. George Mertzios, Dr. Tom Friedetzky, Prof. Iain Stewart, and Dr. Amitabh Trehan. He previously completed a first-class MEng in Computer Science (2017-2021) at Durham, receiving a Certificate of Exceptional Achievement. Research Focus His core interests include: Graph Theory : Modeling relational structures and network dynamics. Computational Complexity : Fundamental limits of algorithmic solvability. Temporal Graphs : Analyzing networks that evolve over time, with applications in transport, contagion spread, and data centers. Publication Trends Kutner's recent work demonstrates a strong emphasis on temporal graph algorithms (e.g., delay management in transport networks, contagion modeling) and network optimization (e.g., reconfigurable data center routing). His publications also explore algorithmic game theory in financial systems and accessibility technology. Awards Best Paper Award & Best Student Paper Award at ALGOWIN 2023 for Temporal Reachability Dominating Sets . Projects & Leadership EPSRC Project: "Multilayer Algorithmics to Leverage Graph Structure" (University of Glasgow, 2025). "Generating Socially Realistic Synthetic Networks" (Durham Sociology Department, 2024). Co-founded and presided over SIDur (SIAM-IMA Student Chapter), organizing academic events (2022-2024).

Qin HanzhangView profile

Assistant Professor

• Operations Research
• Supply Chain Analytics
• Inventory Control
• +3 more

Qin Hanzhang is an Assistant Professor in the Department of Industrial Systems Engineering and Management at the National University of Singapore (NUS). He is affiliated with the Institute of Operations Research and Analytics (IORA), part of NUS’s Smart Nation Research Cluster. His research focuses on advancing optimization and decision-making methodologies, particularly in supply chain analytics, inventory control, and machine learning applications. His work bridges theoretical foundations with practical challenges, addressing topics such as fairness in algorithms, adaptive resource allocation, and privacy-enhanced predictive frameworks. He has contributed to solving large-scale logistical problems, including vehicle routing and stochastic demand modeling. His recent publications emphasize data-driven approaches for inventory positioning, pricing strategies under shape-restricted demands, and sample-efficient reinforcement learning in inventory systems. Hanzhang’s research trends highlight a strong emphasis on operational efficiency, real-world applicability, and interdisciplinary solutions combining operations research with modern machine learning techniques.

Dimitri BertsekasView profile

Professor

• Optimization
• Game Theory
• Systems
• +3 more

Dimitri Bertsekas is the Jerry Mcafee (1940) Professor in Engineering at the Massachusetts Institute of Technology. His research focuses on optimization, game theory, systems, networking, control, and autonomy. He works within the Laboratory for Information and Systems Decisions. His recent publications demonstrate a strong emphasis on reinforcement learning, dynamic programming, and algorithmic solutions for complex systems. Work spans applications in robotics, transportation optimization, computer vision, game AI, and knowledge systems. Common themes include multi-agent coordination, real-time decision-making under uncertainty, and scalable computational methods. Bertsekas contributes to both theoretical frameworks and practical implementations, with innovations in auction algorithms, rollout methods, and model predictive control integration.

Hu ZhenyuView profile

Associate Professor

• Revenue management
• Dynamic pricing
• Supply chain management
• +3 more

Zhenyu Hu is an Associate Professor in the Department of Analytics & Operations (DAO) at NUS Business School. He is affiliated with the Institute of Operations Research and Analytics (IORA) and the Institute of Data Science (IDS) at NUS. His research focuses on revenue management, dynamic pricing, supply chain management, dynamic programming, and game theory. He currently serves as an Associate Editor for Manufacturing & Service Operations Management . Education: Ph.D., Industrial Engineering, University of Illinois at Urbana-Champaign (2015) B.Sc., Mathematics, Sun Yat-sen University (2011) His research explores optimization under uncertainty, strategic interactions in operations, and robust decision-making. Key themes include dynamic pricing strategies with customer reference effects, supply chain coordination mechanisms, and game-theoretic frameworks for resource allocation. Recent work addresses challenges in renewable resource management and vehicle-sharing systems under uncertainty. His articles examine topics such as offer optimization under delayed feedback, robust capacity planning, and multi-location inventory pooling. Research emphasizes both theoretical contributions (e.g., duality approaches in screening problems) and practical applications (e.g., vehicle pre-allocation algorithms). Affiliated labs/teams: IORA focuses on operations research applications for Singapore's Smart Nation initiatives. IDS leverages data science for interdisciplinary solutions.

• Multiple Criteria Decision Making
• Combinatorial Optimization
• Heuristic Search
• +3 more

Murat Köksalan is a Visiting Professor at the Department of Technology and Operations within the Ross School of Business, University of Michigan, Ann Arbor. He previously held roles such as Professor and Chair of the Department of Industrial Engineering at Middle East Technical University, and visiting positions at Georgetown University, Aalto University, Purdue University, and SUNY Buffalo. His academic journey includes a PhD from SUNY Buffalo (1984), an MSc (1980), and BSc (1979) from Middle East Technical University. Education: PhD in Technology and Operations, State University of New York at Buffalo (1984) MSc in Industrial Engineering, Middle East Technical University (1980) BSc in Industrial Engineering, Middle East Technical University (1979) His research focuses on multiple criteria decision making, combinatorial optimization, heuristic search, combinatorial auctions, and teaching case development . He has been recognized with prestigious awards including the MCDM Gold Medal and the Parlar Foundation Science Award, alongside four INFORMS Case Competition first prizes. Recent articles highlight advancements in multi-objective optimization for UAV routing, preference function modeling, and stochastic programming applications. His work bridges theoretical contributions with practical implementations in energy markets, portfolio optimization, and interactive decision support systems. Awards: Young Researcher Award (Scientific and Technological Research Council of Turkey) MCDM Gold Medal (International Society on Multiple Criteria Decision Making) Science Award (Parlar Foundation) His advising and grants reflect a commitment to multi-objective frameworks and their applications. He contributes to research teams exploring algorithmic efficiency, preference elicitation, and stochastic modeling, with ongoing efforts in UAV navigation and energy market dynamics.

Mengxuan ZhangView profile

Lecturer

• Database Systems
• Spatial Databases
• Graph Databases
• +3 more

Dr Mengxuan Zhang is a Lecturer at the School of Computing within the College of Systems & Society at the Australian National University. Prior to her current position, she worked as a postdoctoral researcher at Iowa State University and as a Research Associate at the Hong Kong University of Science and Technology. Her academic qualifications are: PhD in Engineering from the University of Queensland, Australia (2021) Master of Engineering from Dalian University of Technology, China (2017) Bachelor of Engineering from Wuhan University of Science and Technology, China (2014) Dr Zhang's research expertise lies in database management systems, with a focus on spatial and graph databases. She develops advanced techniques for query processing and optimization to enhance performance. Additionally, she designs efficient and scalable routing algorithms for real-world navigation problems, which find applications in intelligent transportation systems, logistics planning, carpooling, robot path planning, and social network analysis. She is currently seeking motivated PhD students to work on projects in data science, particularly in databases (spatial, graph, vector) and intelligent transportation systems. Prospective candidates should possess strong computer science fundamentals and programming skills. She supports students through various scholarship opportunities including the ANU Research Scholarships, Pioneering Women Program, and Elevate Program. No scientific awards were mentioned in the provided information.

Alexander LeeView profile

Associate Professor

• Environmental Ethics
• Climate Change
• Conservation
• +3 more

Alexander Lee is an Associate Professor of Philosophy and Director of Liberal Studies Programs at Alaska Pacific University. His research focuses on environmental ethics, climate change, and the intersection of science, policy, and values in environmental problem-solving. He holds a Ph.D. in Environmental Theory and Values from the University of Colorado, Boulder, alongside an M.S. in Environmental Studies and a B.A. in Philosophy and Environmental Earth Science from Dartmouth College. Education : Ph.D. Environmental Theory and Values, University of Colorado, Boulder M.S. Environmental Studies, University of Colorado, Boulder A.B. Philosophy and Environmental Earth Science, Dartmouth College Lee’s research explores moral obligations in conservation, climate policy, and technological interventions. He emphasizes ethical frameworks for ecosystem restoration, species reintroduction, and climate adaptation. His recent work addresses topics like unintentional geoengineering ethics and the moral status of abiotic nature. Lee actively engages in public discourse through his climate ethics podcast *A Hostile Climate*, contributions to media outlets like *High Country News*, and advocacy with Protect Our Winters. His articles reflect a focus on ethical dimensions of environmental challenges, including consumerist solutions to animal agriculture, carnivore reintroduction ethics, and policy constraints in conservation. His work bridges academic philosophy and practical environmental governance. Lee has no listed scientific awards but is affiliated with the Committee on Environmental Thought. He teaches courses in ethics, environmental philosophy, and science policy. His external activities include writing for *The High Route* and *Ski Journal*, reflecting his interests in outdoor pursuits and climate communication.

Mehdi SadeghilalimiView profile

Lecturer

• Artificial Intelligence
• Optimization
• Machine Learning
• +6 more

Mehdi Sadeghilalimi is a Lecturer in the Department of Computer Science at the University of Regina, Faculty of Science. He specializes in Artificial Intelligence, Machine Learning, Optimization, and Computer Networks, with expertise in applying metaheuristic algorithms to combinatorial problems. He holds a Ph.D. in Computer Science (Artificial Intelligence) from the University of Regina, an M.Sc. in Computer Networks from Islamic Azad University, and a B.Sc. in Information Technology Engineering. His research integrates nature-inspired computing with practical challenges in healthcare scheduling, resource allocation, and network optimization. Recent work focuses on evolutionary approaches for nurse rostering and technician dispatch systems. He teaches courses including Computer Networks, Operating Systems, Programming, and Algorithm Analysis.

Gustavo VejaranoView profile

Associate Professor

• Cyber-Physical Systems
• Wireless Networks
• Robotics
• +4 more

Dr. Gustavo Vejarano is an Associate Professor of Electrical and Computer Engineering at Loyola Marymount University's Frank R. Seaver College of Science and Engineering. His teaching and research focus on the intersection of mathematics and physical systems, particularly in cyber-physical systems, robotics, and wireless networks. He emphasizes hands-on, collaborative learning to help students design practical technological solutions. Education: B.S. in Electrical Engineering, Universidad del Valle, Colombia (2005) M.S. and Ph.D. in Electrical and Computer Engineering, University of Florida (2009, 2011) Research Interests: Dr. Vejarano leads the Intelligent and Embedded Networks and Systems Laboratory (Intemnets Lab) , where research explores autonomous systems like drones for wildfire monitoring, computer vision, and wireless communication networks. His work integrates mathematical modeling to optimize system performance in fields like robotics, surveillance, and medical devices. Lab & Projects: The Intemnets Lab develops solutions for intelligent networked systems, including drone-based surveillance using thermal imaging and computer vision. Collaborative student projects focus on fault-tolerant systems, target localization, and wireless body area networks for healthcare applications. Teaching Philosophy: Dr. Vejarano prioritizes student engagement through real-world problem-solving. He advises future engineers to leverage LMU’s resources for impactful innovation and emphasizes the societal applications of their work.

Robert H. StorerView profile

Professor

• Mathematical Optimization
• Stochastic Optimization
• Robust Scheduling
• +3 more

Robert H. Storer is a Professor and co-founder of the Integrated Business and Engineering (IBE) Honors Program at Lehigh University's Department of Industrial and Systems Engineering. His research focuses on robust, stochastic, and adaptive optimization in scheduling and sequencing, particularly in healthcare and manufacturing systems. He has expertise in heuristic algorithms, simulation, and stochastic modeling. Dr. Storer's affiliations include membership in IIE, INFORMS, ASA, and Tau Beta Pi. He received the Lindback Award (2009) and led a U.S. Army-funded grant for ISE research. His work addresses challenges like operating room scheduling and parallel machine optimization. He teaches courses in optimization, simulation, and applied statistics. Research trends in his articles emphasize stochastic and robust scheduling, decomposition methods, and algorithmic approaches to complex systems. His contributions span vehicle routing, CNC machining, and healthcare logistics, reflecting a blend of theoretical and applied engineering.

Sérgio dos Santos BarretoView profile

Researcher

• Optimization
• Operational Research
• Supply Chain Management
• +4 more

Sérgio dos Santos Barreto is an Associate Researcher at the University of Aveiro's Systems for Decision Support (SDS) group within the GOVCOPP research unit. He holds a PhD in Industrial Management (University of Aveiro), a Master's in Statistics and Operational Research (University of Lisbon), and a Mathematics degree (University of the Azores). His career includes teaching Mathematics at the University of the Azores (1988–2004) and the Higher Institute of Accounting and Administration in Aveiro since 2004. His research focuses on optimization, particularly location-routing problems, supply chain logistics, and decision support systems. He has coordinated major projects like the 'Impact and Efficiency of European Structural and Investment Funds (ESIF) in Sustainable Regional Development in Portugal.' He has also served on the University of Aveiro's Scientific Council and held deputy director roles in CIMAD (Marketing and Data Analysis Center) and the Marketing degree program. Key areas of expertise include mathematical modeling, operational research applications, and policy analysis. His work spans publications in international journals and conference proceedings, with a focus on clustering algorithms, route optimization, and sustainable development metrics. He actively reviews for peer journals and contributes to policy evaluation frameworks. Advising and grants include leading ESIF impact studies and collaborative projects on workforce development and graduate employability. His current affiliations include the DSS-Lab and participation in global research networks.

Dolores Rosa Santos PeñateView profile

Professor

• Optimization
• Location Theory
• Multicriteria Decision Making
• +3 more

Dolores Rosa Santos Peñate is a Full Professor at the Department of Quantitative Methods in Economics and Management at the University of Las Palmas de Gran Canaria. She is affiliated with the Bayesian Statistical and Decision-Making Techniques in Economics and Business research group. Her teaching responsibilities include courses such as Mathematics for Economics III and Business Mathematics . Research Interests: Her work focuses on optimization, location theory, multicriteria decision analysis, and input-output analysis. She has applied these methodologies to competitive facility location problems, GIS-based decision support systems, and spatial economic modeling. Her research often integrates mathematical programming, metaheuristics (e.g., GRASP, PSO), and geographic information systems (GIS). Publications: Her recent work explores topics like tourist trip design optimization (2023), generalized discrete centroid problems (2019), and bibliometric analyses of research impact (2014). These articles reflect her expertise in both theoretical and applied operations research. Grants & Projects: She has led or participated in over 20 research projects, including: Técnicas de optimización y modelos en redes complejas (2015–2018, funded by Spanish Ministry of Economy) Red temática 'Localización y problemas afines' (multiple cycles, funded by national research agencies) Consulting for the Chilean Ministry of Transport (2015, funded by IADB) Labs/Teams: She collaborates with interdisciplinary teams in the Bayesian Techniques research group and contributes to the Quantitative and Computational Finance initiatives. She has also participated in international conferences on operations research and location analysis.

• Religious Education
• Philosophy for Children
• Teacher Education
• +3 more

Rhiannon Love is a Senior Lecturer in the Institute of Education at the University of Winchester, serving as Route Leader for the PGCE Secondary Religious Education (RE) program and overseeing RE curriculum content across undergraduate and postgraduate teacher education. She has 17 years of school teaching experience in Primary and Secondary education, specializing in RE and Philosophy for Children (P4C). Her work includes embedding P4C accreditation into teacher training and co-founding a 'Reading and Research Group' for RE teachers with grant support from Culham St Gabriel’s Trust. Education: Holds a Doctor of Education (EdD) focused on teacher identity and neoliberalism in education, advocating Freire’s Problem-Posing Education as an alternative pedagogical approach. Research Interests: Primary Religious Education, P4C methodology, resisting neoliberal educational narratives, teacher agency, and well-being through philosophical inquiry. She has published widely on these topics, including works in International Journal of Qualitative Studies in Education and Routledge anthologies. Awards and Memberships: Fellow of the Higher Education Academy (FHEA), UCET Travel Scholarship recipient (2015), Co-opted member of Hampshire SACRE, and representative on Diocesan Education Boards. Active in professional networks such as the South Central RE Hub and Hampshire P4C Steering Group. Labs/Initiatives: Leads the RE-focused ‘Reading and Research Group’ at Winchester and collaborates with organizations like HIAS and SACRE to enhance teacher training and curriculum development.