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Eric PinsonView profile

Professor

• Combinatorial Optimization
• Scheduling Theory
• Transport Logistics
• +3 more

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.

Zoé EjebuView profile

Academic

• Applied Economics
• Nursing
• Health Workforce Retention
• +3 more

Zoé Ejebu is a Senior Research Fellow at the University of Southampton, affiliated with the Health Workforce and Systems research group. She joined the university in 2020 and focuses on applied economics methods to study nurse retention, workforce performance, and healthcare resource allocation. Her work emphasizes analyzing large datasets and conducting discrete choice experiments to understand job preferences. Education: PGCAP (2024), University of Southampton FHEA (2023), Higher Education Academy PhD in Economics (2010–2014), University of Aberdeen MSc in Financial Economics (2009–2010), University of Glasgow MA in Economics (2008–2009), University of Aberdeen Licence Économique, Monnaie et Finance (2007–2008), Université Paris II, France Research Interests: Zoé’s work centers on applied economics in healthcare, including nurse retention strategies, workforce performance metrics, and the impact of working conditions. She explores topics such as shift patterns, burnout prevention, and cost-effectiveness of nurse staffing. Her recent studies address NHS nurse retention through discrete choice experiments and policy analysis. Articles Trends: Her publications focus on nurse staffing, shift work impacts, and healthcare workforce dynamics. Recent work highlights cost-benefit analysis of nurse deployment, frailty in adult populations, and frameworks for evidence-based staffing decisions. Awards: Dean’s List Award (2024) Dean’s List Award (2024) Teaching & Grants: She teaches 'Developing Research Skills: Practice-Based Learning' and 'Applied Quantitative Research Methods.' She leads the Evaluation of the N50k Programme and collaborates on projects like understanding NHS nurse retention factors. She accepts PhD students and has no listed grant details. Labs/Teams: Active in the Health Workforce and Systems research group, contributing to interdisciplinary projects on healthcare labor economics and policy.

Jian-Bo YangView profile

Professor

• Evidential Reasoning
• Probabilistic Inference
• Multiple Criteria Decision Analysis
• +10 more

Jian-Bo Yang is Professor and Chair of Decision and System Sciences at the University of Manchester. With over £3.78m in secured research funding from 49 projects (including 17 EPSRC/ESRC grants), he leads research in decision sciences and analytics. He coordinates multiple courses including Quantitative Methods for Management and Decision Analysis for Business, while supervising PhD, MPhil, and MSc students. His research integrates evidential reasoning , probabilistic inference , and multi-criteria decision analysis to address complex problems in risk assessment, resource optimization, and intelligent systems. Recent publications demonstrate focus on: Theoretical advances in evidence-based decision frameworks Evolutionary algorithms for industrial optimization Uncertainty quantification in multi-source data fusion Yang has developed software systems like the Intelligent Decision System (IDS) and collaborates through the Data Science Institute and Decision and Cognitive Sciences Research Centre . His work supports UN Sustainable Development Goals through improved decision methodologies.

Yonah WilamowskyView profile

Professor

• Statistics
• Operations Research
• Quantitative Methods in Law
• +3 more

Dr. Yonah Wilamowsky is a Professor of Computing and Decision Sciences at Seton Hall University, specializing in Statistics and Operations Management. He holds a PhD in Operations Research from New York University (1975), an MS in Operations Research (1970), and a BA in Mathematics (1968) from Brooklyn College. Dr. Wilamowsky teaches courses such as Business Statistics, Quantitative Methods in Business, and Database Management Systems. His research focuses on applying statistics and quantitative methods to law, business processes, biblical studies, and higher education. Notable contributions include work on pooled testing optimization, healthcare reimbursement auditing, and historical mathematical analysis. He has published in journals like European Journal of Business and Management Research , Naval Research Logistics , and Hakirah . Dr. Wilamowsky has received academic honors including Phi Beta Kappa, Pi Mu Epsilon, and Sigma Xi (all 1968). He has also contributed to professional development through consulting in statistics and operations research, and has presented at conferences like the Decision Sciences Institute Annual Meeting. His teaching spans both undergraduate and graduate levels, emphasizing practical applications of quantitative techniques. Current research interests include statistical methodologies for legal and biblical studies, as well as operational efficiency in higher education administration.

• Operations Management
• Management Science
• Supply Chain Management
• +5 more

Dr. Omprakash Gupta is a Professor of Management at the University of Houston-Downtown's Marilyn Davies College of Business, where he has been teaching since 2011. His academic career spans over three decades with previous appointments at Prairie View A&M University, Nirma Institute of Management, and Purdue University. Education: Ph D in Operations Research from Purdue University MS in Mathematics from Purdue University MS in Mathematics from Gujarat University BS in Mathematics from Gujarat University with Supporting Areas of Emphasis in Physics Professor Gupta's research interests focus on operations management, management science, and the application of mathematical models to business and management. His scholarly work demonstrates a unique integration of quantitative methods with cultural and philosophical perspectives, particularly exploring Vedic principles in management. His research spans diverse domains including supply chain management, inventory modeling, quantitative decision-making, linguistic relativity in marketing, and Ramayana-based management principles. His recent publications (2015-2024) reveal a fascinating evolution from traditional operations research topics toward interdisciplinary studies connecting Eastern philosophy with business practices. While maintaining his expertise in quantitative methods and supply chain optimization, Gupta has increasingly explored the intersection of cultural values, linguistic frameworks, and business decision-making. His work on Ramayana-based management principles and linguistic relativity represents a distinctive contribution to management scholarship. Awards and Recognition: MDCOB Excellence in Research Award (September 2024) Marilyn Davies College of Business Excellence Award (September 2022) Professor Gupta has served in numerous leadership roles including Editor-in-Chief of AIMS International Journal of Management and President of AIMS International. His professional service extends to editorial boards, conference organization, and thesis evaluation. He has presented his research at international conferences worldwide and has made significant contributions to management education through case method teaching and faculty development initiatives. His current academic activities include teaching Operations & Supply Chain Management (MGT 3332) and Quantitative Methods in Business (GBA 5210) courses for both undergraduate and graduate students at the University of Houston-Downtown, with scheduled courses through Fall 2025.

Dong DaiView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• High-Performance Computing
• +5 more

Dong Dai is an Associate Professor at the University of Delaware in the Department of Computer and Information Sciences under the College of Engineering. He directs the Data Intelligence Research Lab (DIRLab) , focusing on optimizing intelligent infrastructure for high-performance, data-intensive systems using machine learning techniques. Research Interests : Artificial Intelligence, Machine Learning, High-Performance Computing, Storage Systems, Metadata Management, Graph Storage, Job Scheduling Education : PhD and BSc from the University of Science and Technology of China Grants : CCF-EAGER, CNS, CCF-Hybrid NVM, CCF-Parallel Graph-Based Paradigm, OAC-Provenance Collection Teaching : Courses include CISC 361 Operating Systems , CISC 360 Computer Architecture , ITCS 5145 Parallel Computing , and ITSC 3050 Undergraduate Research .

• Operations Research
• Discrete Event Simulation
• Deterministic Scheduling
• +4 more

John Fowler is a Professor in the Department of Supply Chain Management at Arizona State University's W. P. Carey School of Business, holding the Motorola Professorship in International Management. He previously served as Department Chair (2011-2016) and Avnet Professor of Industrial Engineering at ASU. Education: Ph.D. in Industrial Engineering, Texas A&M University (1990) M.S. in Industrial Engineering, Texas A&M University (1986) B.S. in Industrial Engineering, Texas A&M University (1982) Research Interests focus on discrete event simulation , deterministic scheduling , and multi-criteria decision making , particularly in semiconductor manufacturing systems and healthcare operations. His work bridges operations research with applications in pandemic preparedness, supply chain design, and energy-efficient scheduling. Recent Publications demonstrate expertise in simulation modeling for pandemic response, semiconductor supply chain optimization, and healthcare systems analysis. He has developed decision support frameworks for push-pull supply chains and hybrid scheduling approaches for batch processing in semiconductor manufacturing. Scientific Awards Fellow of the Institute of Industrial and Systems Engineers Outstanding Paper Award, International Journal of Lean Six Sigma (2013) Editorial Service includes Editor-in-Chief of IIE Transactions on Healthcare Systems Engineering (2011-2016) and ongoing roles at Journal of Simulation and IEEE Transactions on Semiconductor Manufacturing . He has held leadership positions in academic societies and served on editorial boards for multiple journals. Grants and Industry Collaboration include NSF funding for healthcare delivery systems, Intel-sponsored semiconductor research, and Mayo Foundation partnerships. His work has addressed pandemic influenza preparedness through simulation models and developed capacity allocation solvers for high-tech industries. Laboratory Leadership encompassed directing the Modeling and Analysis of Semiconductor Manufacturing Laboratory at ASU from 1996 to 2009, where he pioneered simulation frameworks and scheduling methodologies for complex manufacturing systems.

• Global Optimization
• Operations Research
• Computational Mathematics
• +3 more

Marco Locatelli is a Full Professor in the Department of Computer Engineering at the University of Parma, Italy. His research focuses on Global Optimization , Operations Research , and Computational Mathematics , with applications in Robotics and Optimization Algorithms . Education: Ph.D. in Computational Mathematics and Operations Research (University of Milano/Napoli, 1997); Laurea in Computer Science (University of Milano, 1992). Positions: Post-Doc (University of Trier, Firenze); Assistant/Associate Professor (University of Torino); Full Professor (University of Parma since 2010). His research spans Global Optimization over intervals, multistart algorithms, concave optimization, packing problems, and convex underestimators. Recent work includes Multi-Agent Pathfinding and Speed Planning with energy/time optimization, leveraging Machine Learning and Dynamic Programming . He has received distinguished accolades, including the Europt Fellow (2018), Best Paper in the Journal of Global Optimization (2016), and co-authored a SIAM-published book on Global Optimization (2013). He serves on editorial boards of top-tier journals like Computational Optimization and Applications and Operations Research Letters . Scientific Awards: Al Zimmermann's Programming Contest Winner (Circle Packing) AIRO Award for Daniele Depetrini's Master Thesis (2007) Chairman's Recognition of Outstanding Paper (2009 IEEE Congress) Europt Fellow (2018) His teaching includes Operations Research and Algorithms for Decision Support across multiple Italian universities (Torino, Parma, Firenze). He has contributed to Research Projects like MoSPRAS, MOST, and COSO, addressing real-world optimization challenges in healthcare, robotics, and transportation.

Rafael DiazView profile

Professor

• Supply Chain Management
• Cybersecurity
• Modeling and Simulation
• +5 more

Rafael Diaz serves as Director of the Maritime Research Cluster and Interim Graduate Program Director for Cybersecurity at Old Dominion University. Holding a Ph.D. in Modeling and Simulation along with an MBA, his academic work spans supply chain optimization, maritime logistics, cybersecurity, and public health applications through simulation modeling. Ph.D. in Modeling and Simulation (Old Dominion University, 2007) MBA in Business Administration (Old Dominion University, 2002) His research focuses on applying simulation and optimization techniques to complex systems, including: Supply chain decision analysis Inventory management optimization Emergency healthcare utilization patterns Climate-related risk assessment Energy portfolio modeling Lean manufacturing systems Recent publications demonstrate interdisciplinary expertise in operations research, environmental risk assessment, and healthcare analytics. Key article themes include stochastic inventory modeling, hurricane evacuation behavior, and JIT production systems analysis, reflecting his core interest in system performance optimization through simulation.

Purushothaman DamodaranView profile

Professor

• Industrial Engineering
• Systems Engineering
• Operations Research
• +7 more

Purushothaman Damodaran is a Presidential Teaching Professor at the Department of Industrial and Systems Engineering at Northern Illinois University . With expertise in large-scale optimization , logistics , simulation , scheduling , Lean Manufacturing , and Six Sigma , he develops mixed-integer linear formulations and novel algorithms for real-world applications in electronics manufacturing, healthcare, and logistics. Ph.D. , Industrial Engineering, Texas A&M University (2002) M.S. , Industrial Engineering, Northern Illinois University (1997) B.E. , Mechanical Engineering, University of Madras (1994) His research focuses on optimization models for batch processing machines , parallel machine scheduling , and simulation-based decision support systems . He has collaborated with industries like 3M , Caterpillar , Royal Caribbean Cruise Lines , and IBM , addressing challenges in manufacturing systems , warehouse design , and service operations . Recent publications highlight heuristic approaches (e.g., GRASP , Simulated Annealing , Particle Swarm Optimization ) for flow shop scheduling , job shop optimization , and material slitting problems . His work often integrates Lean Six Sigma principles and simulation-optimization for real-time manufacturing improvements . Scientific Awards : Best Paper Award, IISE Annual Conference (2021) National Science Foundation Grant (2008-2009) for server manufacturing research As a faculty teaching mentor at NIU, he teaches undergraduate and graduate courses in Six Sigma , Warehousing , and Advanced Lean Manufacturing , emphasizing real-life projects and student engagement .

• Sequencing and Scheduling
• Combinatorial Optimization
• Computational Complexity
• +6 more

Dr. Yumei Huo is a Professor in the Department of Computer Science at the College of Staten Island, City University of New York (CUNY). Her work spans theoretical and applied domains, including combinatorial optimization, sequencing and scheduling, high performance computing, and medical imaging. She has developed and taught multiple HPC-focused courses and actively supervises undergraduate and graduate research. Education : BS, University of Science and Technology (China) MS, University of Science and Technology (China) PhD, New Jersey Institute of Technology Dr. Huo's research focuses on Sequencing and Scheduling , Combinatorial Optimization , Computational Complexity , Operations Research , High Performance Computing (HPC) , and more recently, Medical Imaging and Big Data . Her recent publications apply deep learning and CNN models to lung nodule detection, polyp classification, and CT image analysis, demonstrating a shift toward biomedical data science. Her recent publications (2018–2021) show a strong trend in applying machine learning to medical imaging, particularly in CT scans for lung and colon analysis. Earlier works focus on theoretical scheduling problems with constraints like machine availability, processing sets, and completion time optimization, indicating a foundation in algorithmic design and complexity theory. Scientific Awards and Recognition : Extensive peer reviewer for over 40 journals and conference proceedings Reviewed more than 50 PSC-CUNY research grant proposals and Chancellor’s Research Fellowship applications Contributed to NSF/IEEE TCPP curriculum initiatives in parallel computing education Dr. Huo has supervised numerous students on research projects and co-authored publications with them. She has also led curriculum development, including launching four HPC courses. She has no known active grants mentioned, but her sustained publication and educational contributions reflect ongoing research support. She is affiliated with research teams in algorithm design and medical imaging AI, particularly collaborating with researchers like H. Zhao, J. Y-T. Leung, and J. Tan.

Leonardo MACCARIView profile

Associate Professor

• Network Security
• Wireless Mesh Networks
• Community Networks
• +5 more

Leonardo Maccari is an Associate Professor at Ca' Foscari University of Venice in the Department of Environmental Sciences, Computer Science and Statistics. His research focuses on network security, wireless mesh networks, community networks, and next-generation wireless backhaul systems. He leads projects like netCommons (EU Horizon2020) and OR2AN2G, advancing scalable and resilient network infrastructures. Notable contributions include centrality-based routing protocols (pop-routing) and analysis of digital contact tracing during the pandemic. Teaching includes courses on Network Security, Computer Networks, and Lab of Computer Security across Computer Science and Data Management programs. Awards include the 2024 Best Paper Award at CNMS for optimizing BGP convergence. Research spans 20+ years with 50+ peer-reviewed publications. Collaborations include Northeastern University, BarcelonaTech, and CNRS. Active in open-source projects like Augustus (programmable CCN router) and NePA TesT (network testing toolchain). Key projects: netCommons (transdisciplinary community networks), OR2AN2G (5G/6G backhaul), and PAF-FPE (Marie Curie security research). Consultancies with Alcatel-Lucent and Telecom Italia Lab produced patents in network security and programmable systems.

Zongli LinView profile

Professor

• Nonlinear Control
• Robust Control
• Control Applications
• +6 more

Zongli Lin is the Ferman W. Perry Professor and Associate Chair for Graduate Studies in the Department of Electrical and Computer Engineering at the University of Virginia's School of Engineering and Applied Science. His research focuses on nonlinear control, robust control, and control applications, with recent work spanning reinforcement learning, microgrid resilience, and HVAC system optimization. He has held editorial roles at journals like Automatica and serves as series editor for Springer/Birkhauser's Control Engineering series. Lin's academic leadership includes board memberships with the IEEE Control Systems Society and chairing its Technical Committee on Nonlinear Systems and Control. He is General Chair of the 2028 American Control Conference. His honors include IEEE, IFAC, and AAAS Fellowships. Research interests emphasize control theory applied to energy systems (e.g., battery storage, DC microgrids) and multi-agent systems. Over 150 publications reflect contributions to anti-windup compensation, distributed control algorithms, and adaptive control methodologies. Lin advises graduate students focusing on control systems theory and applications. His work integrates theoretical advancements with practical implementations, such as CO₂ controller design for cell culturing systems and HVAC energy optimization frameworks.

• Wind Energy
• Hybrid Renewable Energy Systems
• Energy Transition
• +13 more

Professor Alireza Maheri is a Personal Chair in the School of Engineering at the University of Aberdeen, where he has been a faculty member since 2016. He previously served as a Senior Lecturer at Northumbria University and held a research position at the University of Bristol. His academic journey includes a BSc from Shiraz University, an MSc from Amirkabir University of Technology, and a PhD from UWE Bristol, all in Mechanical Engineering. BSc in Mechanical Engineering, Shiraz University MSc in Mechanical Engineering - Energy Conversion, Amirkabir University of Technology PhD in Mechanical Engineering - Design and Simulation of Adaptive Aero-structures, UWE Bristol His research focuses on renewable and sustainable energy systems, with key interests in wind energy, hybrid renewable energy systems (HRES), multidisciplinary design optimization, offshore wind farm decommissioning, and smart energy systems. He leads several high-impact research projects funded by EU-InterReg, Net Zero Technology Centre, and Innovate UK, among others. His work integrates advanced computational methods with real-world energy challenges, particularly in off-grid and island communities. The 15 most recent publications reflect a strong trend in optimization of hybrid energy systems, decommissioning cost modeling, decision support platforms, and algorithmic development for renewable integration. His research spans both technical innovation—such as ant colony algorithms and metaheuristic assessments—and practical implementation, including hydrogen production and load planning for machinery. Professor Maheri has received recognition through research grants, including a project funded by the Royal Aeronautical Society. He has also secured substantial funding from national and international bodies, demonstrating sustained excellence and impact. Net Zero Technology Centre: 'Data for Net Zero (D4NZ)', £992k, 2022–2025, CoI EU-InterReg: 'DecomTools', £240k, 2018–2023, PI National Decommissioning Centre PhD Studentship: 'DSS for Oil & Gas Decommissioning', £72k, 2019–2022, PI Scottish Funding Council SPRe-Industrial Collaboration: £78k, 2019–2023, PI Carnegie Trust PhD Scholarship: 'Wind Turbine Smart Blades', £60k, 2019–2022, Principal Supervisor He supervises a wide range of PhD students on topics including smart blades, hydrogen systems, energy management, and decommissioning. He is also actively involved in teaching, particularly as Course Coordinator for Energy Systems Integration (EG554T and EG554U). His leadership extends to editorial roles in journals such as Energies and Renewable Energy , and he has chaired multiple international conferences. He serves on research proposal review panels for EPSRC, Royal Society, and DAAD, and has acted as an external examiner for MSc programs at Cranfield University. Professor Maheri leads the Applied Dynamics and Structures Research Group and is affiliated with the Centre for Energy Transition. He collaborates with institutions and industries across the UK, Europe, China, Mauritius, and Jordan, fostering international research partnerships in sustainable energy and engineering design.

• Operations Research
• Healthcare Logistics
• Transportation Systems
• +4 more

Onur Ozturk is an Associate Professor at the Telfer School of Management, University of Ottawa. He holds a PhD in Industrial Engineering from Grenoble Institute of Technology (2012), followed by a postdoctoral fellowship at Ivey Business School (2012–2014). Prior to his current position, he worked as an Assistant Professor at ESIEE Paris (2014–2017). His research focuses on large-scale optimization in healthcare and transport sectors, leveraging scheduling theory, simulation modeling, and stochastic processes. He has contributed to projects such as the Efficacity Institute’s urban freight transport optimization in Île-de-France. Research interests include: Integer linear programming and operations research applications Scheduling and simulation modeling for healthcare logistics and transportation Optimization of pandemic-related operations (e.g., staff scheduling in hospitals, patient admissions) Bi-criteria optimization in medical sterilization and manufacturing systems Recent funded research includes a NSERC grant (2019–2026; $169,000) for batch scheduling methods, and multiple internal grants addressing healthcare routing (2021), medical sterilization (2021), and pandemic staffing (2020–2021). His work emphasizes practical solutions for urban logistics, healthcare capacity planning, and crisis management. No scientific awards are explicitly mentioned in the text. His teaching focuses on business analytics, operations management, and stochastic modeling.