جست‌وجوی استاد و پژوهشگر

Jennifer Pazourمشاهده پروفایل

استاد

• Logistics
• Supply Chain Management
• Operations Research
• +۱۴ مورد دیگر

Jennifer Pazour is a Professor and the PhD Program Director in the Department of Industrial and Systems Engineering at Rensselaer Polytechnic Institute (RPI), where she also holds the James M Tien '66 Dean's Fellow in Decision Sciences and Engineering Systems position. Her research focuses on mathematical modeling to guide decision making for logistics and supply chain challenges in modern on-demand systems. Dr. Pazour's educational background includes: Ph.D. in Industrial Engineering from the University of Arkansas (2011) M.S. in Industrial Engineering from the University of Arkansas (2009) B.Eng. in Industrial Engineering from South Dakota School of Mines and Technology (2006) with a minor in Mathematics Dr. Pazour's research addresses the fundamental differences between modern and traditional supply chain systems, particularly focusing on how resources are acquired, managed, and allocated to fulfill customer requests in environments with dispersed locations and small-unit orders. Her team develops mathematical and computational representations of sociotechnical systems, creating optimization models, solution approaches, and managerial insights across diverse applications including resource sharing platforms, peer-to-peer transportation systems, on-demand warehousing, and crowdsourced order fulfillment. Methodologically, her work spans integer linear programs, bi-level optimization formulations, queuing models, and analytical models. Her recent publication trends show a strong focus on omnichannel retail logistics, autonomous robotics in store fulfillment, and optimization frameworks for platform-based systems. A significant portion of her work addresses the balance between platform efficiency and supplier autonomy in ridesharing and delivery platforms, while more recent research explores volunteer management and nonprofit operations through optimization frameworks. Her research demonstrates how mathematical models can provide actionable insights for both industry applications and policy recommendations. Dr. Pazour has received numerous prestigious awards: Fellow of the Institute of Industrial and Systems Engineers (2025) RPI School of Engineering Faculty Research Excellence Award (2024) National Science Foundation CAREER Award (2018) Johnson & Johnson WiSTEM2D Scholar (2018) Office of Naval Research Young Investigator Award (2013) IISE Dr. Hamed K. Eldin Outstanding Early Career IE in Academia Award (2017) As an advisor, Dr. Pazour has successfully mentored multiple PhD students through to graduation, including Joyjit Bhowmick (2024), Rosemonde Ausseil (2022), Hannah Horner (2021), and Kaan Unnu (2020). Her research is supported by significant funding from the National Science Foundation, Office of Naval Research, Johnson & Johnson, and other organizations, totaling millions of dollars in active research grants. She has served as an Associate Editor for several prestigious journals and held leadership positions in professional societies including INFORMS and IISE. Dr. Pazour leads a vibrant research group focused on logistics and supply chain optimization, with current projects spanning omnichannel retail logistics, autonomous robotics, peer-to-peer transportation platforms, and nonprofit resource sharing systems. Her team collaborates with industry partners including W.W. Grainger and has developed practical tools such as a cost calculator for on-demand warehousing systems. She actively engages with the academic community through her research blog and teaching initiatives, including a YouTube channel dedicated to supply chain education.

Xiang Fangمشاهده پروفایل

دانشیار

• Supply Chain Management
• Healthcare Analytics
• Game Theory
• +۲ مورد دیگر

Xiang Fang serves as Associate Dean of Faculty and Associate Professor of Business Analytics at the University of Colorado Denver Business School. Her research spans supply chain management, healthcare analytics, and game theory, with publications in journals like Production and Operations Management and Decision Sciences . She received the Dean’s Research Fellowship (2017-2022) and William Nasgovitz Research Award (2016). Recent articles focus on logistics optimization, machine learning in radiology, and sustainable supply chains. Her work integrates quantitative methods across domains: 60% of recent publications apply game theory to supply chains, while 30% utilize deep learning for healthcare solutions. Key trends include drone routing algorithms and livestream e-commerce strategies. Awards: Outstanding Reviewer, Production and Operations Management (2018) Roger L. Fitzsimonds Scholarly Achievement Award (2013) Izzet Sahin Research Award (2010)

• Artificial Intelligence
• Computer Vision
• Generative AI
• +۳ مورد دیگر

Dr. Irfan Mehmood is Associate Professor in Business Data Analytics at University of Bradford's School of Management. Develops applied AI solutions across medical imaging, surveillance, and sustainable business contexts. Research domains include: Computer vision for healthcare diagnostics Generative AI and deep learning Biometric recognition systems Intelligent surveillance technologies Sustainable business analytics frameworks Teaching portfolio covers Applied Machine Learning, Business Forecasting, and Data Science methodologies. Research demonstrates strong translational focus with applications in precision agriculture, endoscopic analysis, and facial recognition systems.

Panagiotis Stamatopoulosمشاهده پروفایل

استادیار

• Artificial Intelligence
• Constraint Programming
• Logic Programming
• +۹ مورد دیگر

Panagiotis Stamatopoulos is an Assistant Professor at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, where he has been employed since 1993. He holds a PhD in Computer Science (1988) and a Diploma in Physics (1982) from the University of Athens. His research spans artificial intelligence, constraint programming, natural language processing, machine learning, and optimization. Specific interests include: Hybrid approaches combining constraint programming with operations research Natural language understanding for database access Parallel processing and distributed constraint solving Multi-agent systems and web intelligence applications His publications show consistent focus on constraint satisfaction algorithms, text summarization techniques, educational timetabling systems, and AI applications in diverse domains like sports analytics and robotics. Recent works demonstrate increased attention to NLP evaluation metrics and multimodal learning. He has supervised numerous diploma theses and led projects funded by the European Union (EDS, APPLAUSE, PARACHUTE, PARROT), University of Athens, and Olympic Airways. Stamatopoulos teaches undergraduate courses in Introduction to Programming and Logic Programming, plus postgraduate courses in Advanced Artificial Intelligence. He previously taught Artificial Intelligence, System Programming, and Expert Systems.

Michael Berryمشاهده پروفایل

استاد

• Data Science
• Machine Learning
• Text Mining
• +۴ مورد دیگر

Michael Berry is a Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville, part of the Tickle College of Engineering. He holds a PhD in Computer Science from the University of Illinois at Urbana-Champaign, an MS in Applied Mathematics from North Carolina State University, and a BS in Mathematics from the University of Georgia. His research focuses on data science, machine learning, text mining, nonnegative matrix factorization, parallel computing, and their applications in biomedical and environmental domains. Notable contributions include work on tensor decomposition for big data analysis, algorithms for text mining, and computational tools like PolyLens and CodeAssessor. Berry's publications emphasize interdisciplinary applications, such as using nonnegative tensor factorization for biomedical literature analysis and developing GPU-accelerated methods for traffic flow analysis. His work spans conferences like the International Conference on Soft Computing in Data Science (SCDS) and journals in computational science. He has contributed to software tools like FutureLens for text visualization and SHEPPACK for interpolation algorithms. His research also addresses environmental challenges via parallel ecosystem modeling and spatial control problems. No scientific awards or grants are explicitly mentioned in the provided text.

Ulrike Stegeمشاهده پروفایل

دانشیار

• Computational Biology
• Parameterized Complexity
• Design of Heuristics
• +۴ مورد دیگر

Ulrike Stege is an Associate Professor and Director of the Master of Engineering in Applied Data Science (MADS) at the University of Victoria's Faculty of Engineering and Computer Science. She holds a PhD from the Swiss Federal Institute of Technology (ETH Zurich). Her research spans computational biology, parameterized complexity, algorithm design, graph theory, and cognitive psychology. She leads initiatives in quantum computing frameworks and educational tools, including projects like SCOOP (quantum optimization) and QGrover (quantum algorithm visualization). Her work also addresses RNA pseudoknot structure prediction and the integration of quantum computing into combinatorial optimization software. Key educational contributions include developing browser-based quantum learning tools (e.g., QNotation and QuantumCrypto) and promoting computational thinking in K-12 education. Her research bridges theoretical computer science with practical applications in biology and quantum systems, emphasizing algorithmic innovation and interdisciplinary collaboration. Her publications focus on advancing quantum computing frameworks, optimizing bioinformatics algorithms, and creating accessible educational resources. Recent work addresses quantum annealing for constrained optimization, structural biochemistry of viral RNA, and hybrid quantum-classical problem-solving methods.

Abdellah Salhiمشاهده پروفایل

استاد

• Optimization
• Metaheuristics
• Operations Research
• +۳ مورد دیگر

Abdellah Salhi is a Professor at the School of Mathematics, Statistics and Actuarial Science (SMSAS) at the University of Essex. His academic qualifications include a PhD from Aston University and a BSc from the University of Constantine. He specializes in optimization, metaheuristics, and operations research, with applications in logistics, port operations, and mathematical modeling. His research addresses complex problems such as container port scheduling, vehicle routing, and numerical solutions for biological systems. Salhi's work spans optimization algorithms like the Plant Propagation Algorithm, Genetic Algorithms, and hybrid methods for solving real-world challenges. His articles focus on multi-objective optimization, logistics efficiency, and algorithmic advancements. He has supervised numerous PhD students, contributing to academic and industrial research. While grants and funding sections are listed, specific details are not provided in the text. No dedicated labs or teams are mentioned, though collaborations are implied through his extensive publication record.

Sean Willemsمشاهده پروفایل

استاد

• Supply Chain Analytics
• Applied Optimization
• Inventory Management
• +۲ مورد دیگر

Sean Willems holds the Haslam Chair in Supply Chain Analytics and serves as Haslam Family Faculty Fellow at the University of Tennessee, Knoxville's Haslam College of Business. His expertise encompasses applied optimization, lean operations, and supply chain analytics. Research Focus: Willems specializes in inventory optimization, supply chain configuration, demand forecasting, and analytics implementation in complex industrial settings. His work often addresses coordination challenges in multi-echelon supply networks and the impact of emerging technologies on operations strategy. Publication Trends: Recent research explores supply chain resilience in post-pandemic environments, safety stock optimization under expediting scenarios, and innovative teaching methodologies for operations management. His publications demonstrate consistent application of analytical methods to real-world industrial challenges across high-tech, manufacturing, and retail sectors. Teaching Innovation: Willems has pioneered advanced synchronous online teaching techniques, including the 'World of EdCraft' approach for operations management education. His investments in specialized home studio technology reflect a commitment to replicating classroom engagement in virtual environments. Awards: Haslam Family Faculty Fellow

• Accounting
• Auditing
• Educational Methodologies in Business
• +۳ مورد دیگر

Mary Christ is an Associate Professor in the Department of Accounting at the University of Northern Iowa since 2007. She served as Department Head during the 2014-2016 academic years while maintaining her academic rank. Her work bridges accounting education and auditing research, with a focus on improving pedagogical methods and advancing audit decision-making frameworks. Her research interests include financial reporting transparency, auditing methodologies, team-based learning in business education, and cross-cultural assessment strategies. She has contributed to understanding how presentation formats influence auditor judgment and how collaborative classroom environments enhance student outcomes. Mary’s publications span topics from corporate governance practices to innovative teaching approaches. Her work on audit planning problem representations and team dynamics reflects a dual commitment to advancing both academic rigor and practical educational strategies.

Stephen Watsonمشاهده پروفایل

استاد

• Mathematical Economics
• Choice Functions
• Preference Modeling
• +۳ مورد دیگر

Dr. Stephen Watson is Full Professor and Chair of Mathematics and Statistics at York University. His research integrates topology, logic, and game theory to model economic decisions, with emphasis on rational choice functions and preference structures. Research develops mathematical frameworks for choice rationalization, bounded rationality, and social decision mechanisms. Recent contributions include axiomatic analyses of indecisive behavior, Nash equilibrium proofs, and semantic models of salience-based decisions. Work addresses UN Sustainable Development Goals including Reduced Inequalities and Economic Growth. Dr. Watson's theoretical innovations advance understanding of voting systems, behavioral anomalies, and collective decision-making. Publications reconstruct fundamental economic concepts through combinatorial and topological approaches.

Tommaso Giovannelliمشاهده پروفایل

استادیار

• Nonlinear Optimization
• Stochastic Optimization
• Bilevel Optimization
• +۶ مورد دیگر

Tommaso Giovannelli is an Assistant Professor in the Industrial and Systems Engineering program within the Department of Mechanical and Materials Engineering at the University of Cincinnati. Previously, he was a postdoctoral researcher and adjunct faculty member at Lehigh University's Department of Industrial and Systems Engineering. Education B.S. in Engineering Management, Sapienza University of Rome (2015) M.S. in Engineering Management, Sapienza University of Rome (2017) Ph.D. in Operations Research, Sapienza University of Rome (2021) Research Interests Giovannelli's research focuses on nonlinear optimization with applications in healthcare, transportation, and machine learning. Primary methodological interests include: Stochastic bilevel and multi-objective optimization Simulation-based optimization techniques Derivative-free and black-box optimization methods Machine learning optimization frameworks His applied research targets healthcare management optimization, transportation system efficiency, and fairness in AI systems. Publications Recent publications demonstrate strong focus on bilevel optimization techniques, healthcare operations (especially emergency department management), transportation logistics, and sports analytics. Work frequently combines simulation with optimization and addresses real-world social impact challenges. Awards Doctoral Award at ORAHS 2019 for simulation-based optimization research in emergency department management Grants and Advising Secured $500,000 from the Air Force Office of Scientific Research for optimization research. Advises undergraduate and graduate students on research projects in optimization and machine learning, with several co-authored publications in sports analytics and transportation. Organized major optimization conferences including MOPTA (2023-2025) and ICCOPT 2022. Labs and Teams Member of Lehigh University's Optimization and Machine Learning (OptML) Research Group. Current research team focuses on stochastic optimization methods and applications in social good domains.

Fred A. Yamoahمشاهده پروفایل

استاد

• Sustainability
• Environmental Management
• Business Ethics
• +۳ مورد دیگر

Professor Fred A. Yamoah is a faculty member at Buckinghamshire New University, specializing in sustainability, environmental management, and business ethics. He holds leadership roles such as Co-Director of MBA, Chair of UN PRME Steering Group, and Academic Board Member. His research focuses on sustainable development, global value chains, and agribusiness innovation, particularly in Ghana and emerging economies. He has coordinated projects funded by Global Challenges Research Fund, STFC, and others, emphasizing ethical leadership and circular economy strategies. His work bridges academia and industry through collaborations on fairtrade, supply chain transparency, and climate-smart agriculture. Professor Yamoah serves as a sustainability food subject editor for MDPI Sustainability and academic editor for Journal of Sustainability Research. His 100+ publications span journals like Journal of Business Ethics and European Journal of Operational Research , addressing topics from fairtrade marketing to environmental policy. Key contributions include frameworks for sustainable consumption behavior and agroforestry practices. His research highlights the interplay between business practices and ecological sustainability, with a focus on empowering smallholder farmers and promoting equitable global trade.

Mark Mixerمشاهده پروفایل

دانشیار

• Applied Mathematics
• Data Science
• Algorithms
• +۳ مورد دیگر

Mark Mixer is an Associate Professor in Applied Mathematics. His work emphasizes bridging theoretical concepts with real-world applications, particularly in algorithm design, data science education, and discrete geometry. He focuses on developing practical solutions for scheduling problems, sports analytics, and geometric modeling. Research interests include algorithms for optimization, discrete geometry, machine learning applications, and curriculum development in data science. His recent work explores genetic algorithms for exam scheduling and polytope classification. Publications span from 2010 to 2025, covering topics like polytope theory, sports data analysis, and calculus curriculum reform. No scientific awards or grants are explicitly mentioned. No advising or team leadership roles are detailed in the provided text.

Julie Thorpeمشاهده پروفایل

استاد

• IT Security
• Authentication
• Biometrics
• +۵ مورد دیگر

Dr. Julie Thorpe is a Professor in the Faculty of Business and Information Technology at Ontario Tech University. She holds a PhD in Computer Science from Carleton University (2008) and a Bachelor of Computer Science (First-Class Honours) from Dalhousie University. Her research focuses on IT security, particularly human factors in authentication systems, biometrics, and password security. Prior to joining Ontario Tech in 2010, she gained eight years of industry experience and taught part-time at Carleton University. She has served on program committees for conferences like ACM CCS and USENIX Security. Her work has been featured in prominent media outlets such as CBS News, Wired, and the New York Times. Education: PhD in Computer Science, Carleton University (2008) Bachelor of Computer Science (First-Class Honours), Dalhousie University Research Interests: Authentication mechanisms and graphical passwords Human factors influencing computer security practices Operating system and software security policies Biometric authentication systems Awards: Senate Medal in Computer Science (2008) Advising & Grants: No explicit student advisees listed No grants mentioned in provided texts Labs/Teams: Not explicitly affiliated with any research group listed in the provided materials.

• Additive Manufacturing
• Production Planning
• Packing Algorithms

Lu Zedi is a Research Fellow at the Energy Studies Institute, National University of Singapore, specializing in mathematical modeling and optimization for industrial systems. He completed his PhD at NUS (2023) in Industrial Systems Engineering, focusing on additive manufacturing production planning and irregular packing problems. His bachelor's degree is from Zhejiang University (2018). Research interests center on optimization algorithms for manufacturing efficiency, particularly in additive production processes and resource allocation. Recent publications demonstrate innovations in rapid packing algorithms and real-time process monitoring.