جست‌وجوی استاد و پژوهشگر

Qi Wuمشاهده پروفایل

دانشیار

• Empirical Research in Operations Management
• Finance and Operations Management Interface
• Risk Management
• +۶ مورد دیگر

Qi Wu is an Associate Professor in the Department of Operations at Weatherhead School of Management, Case Western Reserve University. Her research bridges empirical operations management with financial and risk analysis, focusing on procurement strategies amid globalized supply-demand uncertainties. PhD in Information, Risk and Operations Management (University of Texas at Austin, 2013) MS in Mathematics and Statistics (University of South Carolina) Bachelor’s in Operations Research (Huazhong University of Science and Technology, China) Her work explores the interplay between financial constraints and operational decisions, including inventory financing, healthcare service optimization, and supply chain sustainability. She employs stochastic control models and econometric frameworks to analyze risk-averse strategies and contractual design. Recent publications highlight trends in supply chain financing, waste reduction in retail promotions, and capital structure dynamics under operational flexibility. She has received accolades such as the Emerging Impact Research Award (2020) and Lewis-Progressive Fellowship (2020). 2020 Emerging Impact Research Award 2018 Meritorious Service Award 2020 Lewis-Progressive Fellow Dr. Wu teaches courses in probability, statistical analytics, and revenue management, and has contributed extensively to journals like Management Science and Production and Operations Management .

• Applied Probability
• Stochastic Processes
• Queueing Theory
• +۷ مورد دیگر

Bert Zwart is a Professor and Scientific Staff Member at Centrum Wiskunde & Informatica (CWI) in Amsterdam, where he leads the Stochastics group. He also holds a professorship by special appointment at Technische Universiteit Eindhoven (TU/e). His research spans applied probability, stochastic processes, queueing theory, and operations research, with applications in power systems, supply chains, and risk modeling. His research interests focus on extreme value theory , large deviations , asymptotic analysis of stochastic systems , and random graphs . He develops theoretical tools to analyze rare events and performance limits in complex systems such as fork-join queues, power grids, and stochastic networks. His work combines deep probabilistic insights with practical applications in engineering and operations management. Recent publications (2023–2025) reveal a strong focus on tail behavior in queueing systems, large deviations in heavy-tailed processes, and optimization in power networks. The articles span high-impact journals like Mathematics of Operations Research , Queueing Systems , and Random Structures & Algorithms , indicating sustained leadership in applied probability and stochastic modeling. His scientific awards include: Erlang Prize (2008) Dantzig Prize (2015) Best publication award, INFORMS Revenue Management & Pricing (2016) IBM Faculty Award (2008) ASML Prize (2002) Gijs de Leve Prize (2002) Applied Probability Trust Award (2001) Best paper, Performance conferentie, Namen, Belgium (2010) Zwart has secured significant research funding, including a Vici grant from NWO on rare events, multiple NWO TOP and STAR cluster grants, and funding for PhD positions and postdocs. He has advised numerous students (though not explicitly listed here) and collaborates widely with researchers such as Maria Vlasiou, Remco van der Hofstad, and Onno Boxma. He is actively involved in teaching, offering advanced courses like Stochastic Decision Theory and Asymptotic Methods in Queueing Theory . He leads the Stochastics group at CWI, a leading research unit in probability and operations research.

Dean Chatfieldمشاهده پروفایل

دانشیار

• Supply Chain Management
• Business Simulation
• Operations Management
• +۳ مورد دیگر

Dean Chatfield is an Associate Professor in the Department of Information Technology & Decision Sciences at Old Dominion University , where he teaches and conducts research in supply chain management and simulation modeling. Education: Ph.D. in Management Science and Information Systems, Pennsylvania State University (2001) M.S. in Management Information Systems, Pennsylvania State University (1993) M.B.A. in Finance, Pennsylvania State University (1991) B.S. in Management Systems, Rensselaer Polytechnic Institute (1989) Research Interests focus on supply chain dynamics and inventory system optimization , particularly examining phenomena like the Bullwhip Effect , stockout propagation , and risk amplification in multi-echelon systems. His work employs discrete-event simulation and agent-based modeling to develop decision support frameworks for complex supply chain scenarios, including cascading failures and stochastic lead times. Representative Publications include simulation studies on network characteristics affecting supply chain resilience (International Journal of Production Economics, 2020), crossover-aware inventory policies (Transportation Research Part E, 2018), and quantifying information-sharing impacts on demand amplification (Production and Operations Management, 2004). His research has secured over $834,238 in grants , including a $551,438 NSF CAREER award for simulation-based inventory modeling. Scientific Honors: 2005 Best Application Research Paper, Decision Sciences Institute Grants address technology gaps in transportation logistics and mathematical frameworks for service-driven systems. He has developed specialized simulation tools like SISCO and SCML to support industry applications.

Nezih Altayمشاهده پروفایل

استاد

• Humanitarian Supply Chains
• Disruption Management
• After-Sale Service Operations
• +۴ مورد دیگر

Nezih Altay serves as Professor and Director of the MS in Supply Chain Management Program within the Department of Management & Entrepreneurship at DePaul University's Driehaus College of Business. He maintains international research affiliations as a Resilience Research Fellow at Delft University of Technology and research partner at Kühne Logistics University's Research Institute on Leadership and Operations in Humanitarian Aid, while continuing his relationship with Hanken School of Economics as a HumLog Institute Research Affiliate. His academic credentials include: PhD in Operations Management, Texas A&M University (2001) MBA, University of Texas Pan American (1996) BS in Chemical Engineering, Bogazici University, Turkey (1993) Altay's research centers on humanitarian supply chains, disruption management, and after-sale service operations, addressing critical challenges in disaster response systems and vulnerable population support. His work bridges theoretical operations management with practical humanitarian applications, emphasizing resilience building and ethical considerations in crisis contexts through frameworks like coping strategies and ambidextrous organization design. Recent publications (2022-2025) show intensified focus on pandemic resilience, migrant flow logistics, and generative AI applications for social good, while maintaining core themes in disruption management and humanitarian innovation. His research increasingly integrates advanced analytics with field-based evidence from crises in Turkey, Greece, Kenya, and Ethiopia. Major recognitions include: Academic/Research Accomplishment Award from American Logistics Aid Network (ALAN) (2019) Fulbright-Hanken Chair in Business and Economics (2021) Altay has directed DePaul's MS in Supply Chain Management program while teaching executives, MBA, and undergraduate students since 1999. His Fulbright Grant enabled significant collaboration with HumLog Institute, and editorial leadership includes co-editor-in-chief of the Journal of Humanitarian Logistics & Supply Chain Management and senior editor of Production and Operations Management. International research partnerships drive his work through Delft University's resilience initiatives, Kühne Logistics University's leadership institute, and Hanken's HumLog Institute, creating a global network for humanitarian operations research with field studies across multiple continents.

• Forest Carbon Management
• Sustainable Forest Management
• Remote Sensing in Forestry
• +۵ مورد دیگر

Mathias Neumann is an Assistant Professor at the Institute of Forest Management within the Department of Ecosystem Management, Climate and Biodiversity at the University of Natural Resources and Life Sciences, Vienna (BOKU). His research focuses on Forest Ecosystem Management with a specific emphasis on sustainable Carbon management in forests. Dr. Neumann leads multiple research projects including 'Totholzzersetzung in Zentraleuropäischen Wäldern' (Deadwood decay in Central European forests) and 'OPTimising FORest management decisions for a low-carbon, climate resilient future in EUrope'. Dr. Neumann's research interests span forest carbon dynamics, sustainable forest management, remote sensing applications in forestry, climate change impacts on forest ecosystems, deadwood decay processes, and wildfire risk assessment. His work integrates field measurements with modeling approaches to understand carbon allocation in forest ecosystems, forest productivity under changing climate conditions, and the development of sustainable management practices that enhance forest resilience and carbon sequestration capacity. His recent publications demonstrate a clear focus on understanding forest carbon cycles, developing methods for assessing forest carbon sinks, modeling forest responses to climate change, and evaluating sustainable management practices. The research trends show increasing emphasis on integrating multiple data sources to create comprehensive forest ecosystem models that can inform climate-resilient forest management decisions across Europe. Förderpreis Fonds 120 Jahre Universität für Bodenkultur (2020) Thurn und Taxis Förderpreis (2018) Outstanding Reviewer Award of Forests (2017) Dr. Neumann has secured significant research funding from the Austrian Science Fund (FWF), European Commission, and national agencies. His current projects address critical challenges in forest management under climate change, including wildfire risk mapping, deadwood management, and optimizing forest carbon sequestration. He actively collaborates with international research teams and contributes to policy-relevant research that bridges science and forest management practice. His work with the Institute of Forest Management involves both fundamental research on forest ecosystem processes and applied research that directly informs sustainable forest management practices in Austria and Europe.

• Supply Chain Risk Management
• Supply Chain Resilience
• Technological Innovation
• +۳ مورد دیگر

Mahour Parast is a Research Associate Professor at Arizona State University's Del E. Webb School of Construction within the School of Sustainable Engineering and the Built Environment. His research focuses on supply chain disruption risk, resilience, and technological innovation, with funding from NSF, USDOT, VentureWell, and Qatar Foundation. He maintains active industry collaborations and serves on editorial boards for IEEE Transactions on Engineering Management and Operations Management Research. Education: Ph.D. in Engineering, University of Nebraska-Lincoln M.S., University of Science and Technology B.S., Sharif University of Technology Research Focus: Dr. Parast's work integrates data science and machine learning to analyze supply chain risk mitigation, emphasizing R&D investment impacts and dynamic capabilities. His publications in Journal of Operations Management and IEEE Transactions reveal how firm size, business strategy, and innovation orientation affect resilience. Recent studies examine bio-materials sustainability and healthcare quality systems through Baldrige Award frameworks. Publication Trends: His 2019-2020 output shows increasing use of machine learning for disruption prediction, with 60% of recent articles applying computational methods to supply chain risk. Cross-industry applications span airlines, healthcare, and construction, highlighting universal resilience principles through empirical US supply chain data. Scientific Recognition: Best Paper Award, European DSI (2024) Mentoring Award, TRB (2018) Multiple Best Paper Awards (DSI, ASEE) Faculty Research Award, UNC-Pembroke (2008) Mentoring & Grants: He has advised 19 graduate students to completion across Ph.D. and Master's programs. Current grants include NSF-funded studies on R&D innovation using BRDIS data and sustainable bio-materials development. His industrial experience in auto and energy sectors informs practical risk management frameworks. Professional Engagement: As a member of ISCRiM and DSI, he leads international research networks. His 24 invited presentations at institutions like Columbia University and Qatar University demonstrate global impact in technological innovation risk management.

Konstantinos A. Tsintotasمشاهده پروفایل

استادیار

• Artificial Intelligence
• Robotics
• Computer Vision
• +۹ مورد دیگر

Konstantinos A. Tsintotas is an Assistant Professor at the Department of Information and Electronic Engineering, International Hellenic University. His research focuses on artificial intelligence, robotics, computer vision, and their applications in smart cities, healthcare, and manufacturing. He is actively involved in advancing AI-driven systems for critical infrastructure management, robotic vision, and embedded device technologies. His work spans theoretical advancements and practical implementations, including projects like SLAM algorithms for autonomous navigation, deep learning models for medical diagnosis, and IoT-integrated smart supply chains. Tsintotas also explores ethical implications of AI in human action recognition and contributes to neuromorphic computing through spiking neural networks. Key technical contributions include ReJSHand (real-time hand pose estimation), fall detection systems for embedded devices, and visual place recognition frameworks. His interdisciplinary approach bridges computer science, electrical engineering, and biomedical applications, reflecting a strong commitment to innovation at the hardware-software interface. Notable trends in his publications emphasize AI ethics, multimodal perception for robotics, and low-power embedded solutions. Ongoing work includes advancing digital twin technologies for supply chains and refining bio-inspired neural architectures for robotics applications.

Marios Savvidesمشاهده پروفایل

استاد

• Biometric Identification
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Marios Savvides is the Bossa Nova Robotics Professor of Artificial Intelligence and a Full Tenured Professor in the Electrical and Computer Engineering Department at Carnegie Mellon University (CMU). He is also the Founder and Director of the CyLab Biometrics Center. His research focuses on AI algorithms for biometrics, facial recognition, iris scanning, and object detection under challenging conditions. He holds a BEng from the University of Manchester, an MS in Robotics from CMU, and a PhD in Electrical and Computer Engineering from CMU. Education: BEng, Microelectronics Systems Engineering, University of Manchester Institute of Science and Technology (1997) MS, Robotics, Carnegie Mellon University (2000) PhD, Electrical and Computer Engineering, Carnegie Mellon University (2004) Research Interests: Core AI and machine learning for robust biometric systems Long-range iris capture and matching Low-shot object detection and scene understanding Applications in retail automation, airport security, and medical imaging Key Achievements: Recipient of seven Best Paper Awards and the 2022 PIPLA Inventor of the Year Recipient of the 2015 Edison Gold Award, 2018 Immigrant Entrepreneur Award, and 2020 AI Excellence Award Developed AI algorithms deployed in over 3 million ADT security cameras and Bossa Nova robots Spun off startups including HawXeye and Oosto, serving as CTO/Chief AI Scientist Grants and Partnerships: Collaborations with Bossa Nova Robotics, Egen, UltronAI, and CMKL University Research on facial recognition for stock market prediction and medical imaging privacy risks Labs and Teams: Director of the CyLab Biometrics Center Member of IEEE Biometric Council and contributor to the IEEE Certified Biometrics Professional program

Giorgio Albertiمشاهده پروفایل

استاد

• Forest Ecology
• Carbon Sequestration
• Remote Sensing in Forestry
• +۵ مورد دیگر

Giorgio Alberti is a Full Professor at the University of Udine , Department of Agri-Food, Environmental and Animal Sciences. His research focuses on forest ecology, carbon sequestration, remote sensing applications, climate change impacts on tree species, and ecosystem services. He leads projects like CarboMark and contributes to Horizon Europe initiatives. Key Research Areas Forest carbon dynamics and biodiversity conservation Integration of field measurements with remote sensing Climate change adaptation in agricultural and forest systems Ecosystem service trade-offs in protected areas His recent work involves machine learning for forest carbon estimation, ecohydrological studies in vineyards, and global biodiversity assessments. He actively participates in international collaborations, including the LATEST Erasmus+ project and Dinaric Alps old-growth forest research. Project Involvement PRI. FOR. MAN Dashboard for wood resource mapping Horizon Europe Project 101081177 on carbon-biodiversity datasets Post-windstorm forest regeneration studies in the Alps Governance of Natura 2000 protected areas

Thomas Kirschsteinمشاهده پروفایل

استاد

• Logistics Management
• Supply Chain Sustainability
• Operations Research
• +۴ مورد دیگر

Introduction Prof. Dr. Thomas Kirschstein is a Professor at Martin Luther University Halle-Wittenberg (MLU), affiliated with the Faculty of Law, Economics and Business, and a researcher at the Center for Economics of Materials (CEM), Fraunhofer-Zentrum IMW. His work focuses on logistics, emission management, and robust statistical methods. He holds a PhD in Economics (2014) and a habilitation in eco-oriented logistics management (2020). Education 2002–2003: Diploma in Mathematics at MLU 2003–2008: Diploma in Economics at MLU 2014: PhD in Economics (thesis: 'Integrated Supply Chain Planning in Chemical Industry') 2020: Habilitation (thesis: 'Papers on the Eco-oriented Management of Logistics Operations') Research Interests Kirschstein's research integrates logistics and environmental sustainability, including emission reduction in freight transport, robust statistical methodologies, and supply chain optimization. His work combines simulation-based planning with empirical analysis, addressing challenges in complex production networks and intermodal transportation. Awards and Recognition Christian Wolff Award (2020) for habilitation thesis Werner Kern Award (2013/2014) for production management research Best Paper Award (2013) from the Faculty of Law and Business Administration Teaching and Academic Contributions He teaches courses in production management, logistics, and data science. Notable roles include: Lecturer: 'Production & Logistics' (2014–2019) Organized conferences like Logistics Management 2019 and Robust Statistics 2014 Labs and Collaborations Active collaborations with Dow Olefinverbund GmbH and Fraunhofer IMW, focusing on integrated logistics systems and robust estimator development.

• Healthcare Logistics
• Project Risk Management
• Warehouse Performance
• +۴ مورد دیگر

Sabrina Grimaldi is a Research Fellow at the Department of Management and Production Engineering (DIGEP) at the Polytechnic of Turin . She has been actively involved in teaching and research since 2010, serving as a Course Collaborator and Lecturer for courses such as Production Planning and Logistics and Industrial Plants and Occupational Safety . Current affiliation: College of Management and Production Engineering Former affiliation: College of Mechanical, Aerospace and Automotive Engineering Her research focuses on healthcare logistics , project risk management , and warehouse performance , with an emphasis on Lean warehousing , supply chain resilience , and Digital Twin integration in logistics networks. The analysis of her recent publications (2022-2025) reveals a trajectory centered on optimizing warehouse operations (e.g., Overall Warehouse Effectiveness), mitigating risks in blood supply chains, and integrating Industry 4.0 technologies like Digital Twins into Physical Internet networks. Subfields span from emergency logistics to smart warehouse automation . She has led research projects funded by commercial contracts, including Internal Logistics and Warehouses (2018-2019), and contributed to doctoral colleges in Production Systems & Industrial Design (2010-2013). Scientific disciplinary sector: IIND-05/A (Mechanical Industrial Systems) Academic area: Industrial and Information Engineering (Area 0009)

Nived Chebroluمشاهده پروفایل

پژوهشگر

• Robotics
• Autonomous Systems
• Simultaneous Localization and Mapping (SLAM)
• +۴ مورد دیگر

Nived Chebrolu is a Senior Research Associate at the Oxford Robotics Institute (ORI) , working with the Dynamic Robot Systems Group since 2021. His research focuses on robot navigation and mapping for field robots, particularly in forest and agricultural environments. University of Bonn – Ph.D. in Robotics Ecole Centrale de Nantes (France) & University of Genoa (Italy) – M.Sc. in Robotics (2015) Research Interests : Simultaneous Localization and Mapping (SLAM) with LiDAR and vision systems Robust registration techniques for long-term autonomy Perception systems for forest and agricultural robotics Autonomous aerial and terrestrial navigation Field robotics applications in precision agriculture Publications reflect expertise in: Forest point cloud co-registration Online tree reconstruction LiDAR-based place recognition Traversability estimation for wild environments Handheld LiDAR for real-time inventory Teaching Activities : Lecturer for M.Sc. course on Mobile Sensing and Robotics Instructor for Techniques for Self-Driving Cars course

Belen Martin-Barraganمشاهده پروفایل

پژوهشگر

• Machine Learning
• Mathematical Programming
• Operational Research
• +۶ مورد دیگر

Belen Martin-Barragan is a Reader in Management Science at the University of Edinburgh Business School , with a focus on the Department of Management Science and Business Economics . Her research bridges Machine Learning and Mathematical Programming , emphasizing Explainable Artificial Intelligence (XAI) and applications in Operational Research , including classification , clustering , inventory management , and routing optimization . Her work includes developing interpretable machine learning models for credit scoring, healthcare data, and sustainable logistics. She has led EPSRC-funded projects on Optimisation Models for Interpretable Analytics and contributed to journals like European Journal of Operational Research , Risk Analysis , and Computers and Operations Research . Key methodologies involve Mixed-Integer Linear Programming , Support Vector Machines , and stochastic dynamic programming . Her research fingerprint spans Machine Learning (97%), Mathematical Programming (75%), and Optimization Algorithms (20%). She has been a Research Champion and Deputy Director of Research (Ethics and Integrity) at the Business School, with affiliations to the Credit Research Centre and Edinburgh Strategic Resilience Initiative .

Ou Jihongمشاهده پروفایل

دانشیار

• Analytics for Managers
• Business Process Management
• Production/Inventory Systems
• +۴ مورد دیگر

Ou Jihong serves as Associate Professor of Operations Management at Cheung Kong Graduate School of Business (CKGSB), bringing extensive global academic experience from prior appointments at National University of Singapore Business School, University of Cambridge, University of California at Los Angeles, and University of Illinois. His research bridges theoretical operations research with practical applications in China's logistics industry. His educational background includes a PhD from Massachusetts Institute of Technology. Research interests span Analytics for Managers, Business Process Management, Production/Inventory Systems, Queuing Analysis and Control, Statistics, Stochastic Modeling and Analysis, and Supply Chain Management, with particular expertise in applied research on China's third-party logistics sector. Professor Ou's publication record demonstrates significant contributions to top-tier journals including Management Science and Operations Research , focusing on optimization of production systems, inventory control, queuing networks, and revenue management. His work consistently addresses real-world operational challenges through rigorous mathematical modeling. His scientific contributions include expertise in conducting industry surveys within China's logistics ecosystem and developing computational approaches for complex operational problems. Professor Ou maintains active engagement with industry through his research on supply chain dynamics and operational efficiency in emerging markets.

• Precision Agriculture
• Computer Vision
• Neural Networks
• +۳ مورد دیگر

Ameer Tamoor Khan serves as a Postdoctoral Researcher (Research Fellow) in the Section for Crop Sciences within the Department of Plant and Environmental Sciences at the University of Copenhagen's Faculty of Science. Based at the Taastrup campus (Højbakkegård Allé 13, 2630 Taastrup), his work bridges agricultural science and computational intelligence with direct contact via atk@plen.ku.dk and +4535327865. His research centers on AI-driven solutions for agricultural challenges, specializing in computer vision applications for precision farming. Key focus areas include pest and weed detection using YOLO architectures (v8/v11), leaf phenotyping analysis, neural network-based supply chain optimization, and evolutionary computation for model-free systems. This interdisciplinary work integrates deep learning, operational research, and agricultural engineering to enhance food security and farming efficiency through real-time computational approaches. Analysis of his 2025 publications reveals a dominant trend in applying computer vision to agricultural robotics, particularly in multi-crop monitoring systems. His work consistently connects neural dynamics with practical farming applications, spanning from cotton weed management to portfolio risk optimization, demonstrating cross-domain versatility in computational intelligence. No scientific awards were documented in the source material. Information regarding student supervision or research grant acquisition was not provided in the available records. While specific laboratory affiliations weren't detailed, his research output indicates active collaboration within computational agriculture networks, particularly with co-authors Jensen and Mirjalili across multiple institutions.