جست‌وجوی استاد و پژوهشگر

Ramzi HAMMAMIمشاهده پروفایل

استاد

• Supply Chain Management
• Green Supply Chain Design
• Operations Research
• +۵ مورد دیگر

Ramzi HAMMAMI is an Academic Dean and Full Professor of Supply Chain Management at Rennes School of Business (Rennes SB), leading the Supply Chain Management & Information Systems department. He holds a Ph.D. from Grenoble INP and has held academic positions at institutions like Toulouse Business School and Tunisian engineering schools. His research focuses on supply chain design, green logistics, and operational optimization, with over 60 publications in top journals like European Journal of Operational Research and International Journal of Production Economics. He has secured significant research grants (e.g., €350k from ANR for green supply chain research). Education Ph.D. in Industrial Engineering, Grenoble INP (2008) Masters from National Engineering School of Tunis (ENIT) Research Interests Ramzi’s work addresses strategic and tactical supply chain challenges, including green supply chain management, inventory optimization, and decision support systems. He explores how environmental regulations, consumer preferences, and global market dynamics impact supply chain resilience and sustainability. Recent studies focus on pandemic medical supply security and bioenergy supply chain design under uncertainty. Key Contributions Developed models for closed-loop supply chains and remanufacturing systems Advanced methodologies for supplier selection and global sourcing strategies Optimized warehouse operations and order batching systems Awards & Grants ANR funding (2016-2020) for green supply chain research Best Ph.D. Thesis award (2009) Recipient of EIFFEL Excellence Scholarship Leadership & Impact As Academic Dean, Ramzi oversees academic strategy and faculty development. He leads RSCOM, a research center specializing in supply chain innovation. His work bridges academia and industry, addressing real-world challenges in logistics, sustainability, and global operations.

• Supply Chain Management
• Inventory Policy Optimization
• Sustainable Supply Chains
• +۴ مورد دیگر

Indranil Biswas is an Associate Professor at the Department of Information Systems, Supply Chain Management, and Decision Support at NEOMA Business School. He previously served as an Assistant Professor at the Indian Institute of Management Lucknow (IIM Lucknow). His research focuses on supply chain coordination, inventory policies, sustainable supply chains, and decision support systems, with publications in top journals like the European Journal of Operational Research and International Journal of Production Economics. He has won prestigious case competitions including ISB-IVEY (2012), EFMD (2013), and CEEMAN (2017). His work addresses challenges such as extreme weather impacts on supply chains, Industry 4.0 integration, and financial constraints in small businesses. Education: PhD in Operations Management Research interests span operational research applications in supply chain resilience, green logistics, and game-theoretic models for channel coordination. He teaches supply chain management, lean management, and international purchasing. Recent articles analyze topics like contract design for multi-buyer networks, Industry 4.0-driven supply chains, and public-private partnership governance. His collaborative work emphasizes sustainability and innovative solutions to supply chain disruptions.

Skouri Konstantinaمشاهده پروفایل

استاد

• Inventory control
• Operations research
• Supply chain management
• +۲ مورد دیگر

Skouri Konstantina is a Professor of Operations Research in the Section of Statistics and Operations Research at the Department of Mathematics, University of Ioannina, Greece. She maintains her office in the Mathematic Building, 3rd floor, Office 309β, and can be reached at +30 26510 0 8230 or via email at kskouri@uoi.gr. She completed both her Undergraduate and Postgraduate Studies at the Department of Mathematics, University of Ioannina. Her academic journey has led her to become a prominent researcher in the field of Operations Research, with a particular focus on inventory management and supply chain optimization. Professor Skouri's research interests encompass a wide range of topics within Operations Research, with special emphasis on: Inventory control systems and optimization Operations research techniques for supply chain management and reverse logistics Production planning and control methodologies Quantitative methods for business decision making Sustainable operations and green supply chain management Her extensive publication record demonstrates consistent contributions to the field of Operations Research, with numerous articles published in leading journals. Her research spans theoretical developments in inventory modeling as well as practical applications addressing contemporary supply chain challenges including sustainability considerations, disruption management, and innovative payment and pricing strategies. Professor Skouri has maintained an active research agenda for over two decades, with publications appearing consistently from 2000 through 2025, demonstrating her enduring contribution to the field. Professor Skouri has been actively involved in the academic community through her affiliation with the University of Ioannina, where she contributes to both undergraduate and graduate education in Mathematics and Operations Research.

Fabio Widmerمشاهده پروفایل

پژوهشگر

• Electric mobility
• Energy management
• Thermal management
• +۶ مورد دیگر

Fabio Widmer is a PhD researcher at the Institute for Dynamic Systems and Control (IDSC) within ETH Zürich's Department of Mechanical and Process Engineering. He received his B.Sc. and M.Sc. degrees in mechanical engineering from ETH Zürich in 2015 and 2017, respectively, with distinction, focusing on electric mobility and energy flows during his studies. His academic background includes: B.Sc. in Mechanical Engineering, ETH Zürich (2015) M.Sc. in Mechanical Engineering, ETH Zürich (2017) Widmer's research centers on model-based optimization of thermal and energy management systems for electrified public transport vehicles. His work spans electric buses, hydrogen hybrid vehicles, and charging infrastructure optimization. He has made significant contributions to understanding energy-comfort trade-offs in HVAC systems, developing optimization methods for charging strategies, and creating online-capable control algorithms for hydrogen vehicles. His research combines theoretical modeling with practical applications, utilizing dynamic programming, model predictive control, and scenario-based optimization approaches to address real-world transportation challenges. Widmer has received recognition for his academic achievements, including two Outstanding Bachelor Awards and a scholarship from ETH Zürich's Excellence Scholarship and Opportunity Programme. His research has resulted in numerous publications in high-impact journals such as Control Engineering Practice, Energy, and Energies, demonstrating both theoretical rigor and practical relevance to sustainable transportation systems. As part of his research activities, Widmer has contributed to projects including ISOTHERM and Swiss eBus Plus. He was also actively involved with ETH's formula student team AMZ, where student teams develop and compete with self-developed electric race cars, reflecting his hands-on approach to electric mobility research.

Christopher Rentonمشاهده پروفایل

مدرس ارشد

• Control Systems
• Robotics
• Machine Vision
• +۵ مورد دیگر

Dr. Christopher Renton is a Senior Lecturer in the School of Engineering at the University of Newcastle, Australia. His expertise spans control systems, robotics, and machine vision. He holds a PhD and Bachelor of Engineering (Mechatronics) from the University of Newcastle. Education: Doctor of Philosophy, University of Newcastle Bachelor of Engineering (Mechatronics)(Honours), University of Newcastle Research Interests: Dr. Renton focuses on dynamical systems, medical robotics, and Bayesian estimation. His work integrates nonlinear control theory, optimization, and machine vision for applications in robotics, automotive systems, and marine vehicles. Current projects include extended target tracking, autonomous navigation, and robust estimation algorithms. Grants & Funding: Total funding: $612,183 AUD. GPS Compromised Navigation ($158,701, Boeing Defence Australia) Robust Autonomous Systems ($411,299, Boeing Defence Australia) Maritime RobotX Challenge - University of Newcastle ($26,654, US Office of Naval Research) Advising & Labs: Principal supervisor for two current PhD students researching Bayesian methodologies in SLAM and state estimation. Part of the Priority Research Centre for Complex Dynamic Systems and Control, focusing on nonlinear systems and robotics.

• Machine Learning
• Human-Computer Interaction
• Dynamic Systems
• +۵ مورد دیگر

Professor Roderick Murray-Smith is a Professor of Computing Science at the University of Glasgow, affiliated with the School of Computing Science. He leads the Inference, Dynamics and Interaction Research Group and the Information, Data & Analysis Section . Previously, he held positions at institutions including MIT, Technical University of Denmark, and Daimler-Benz Research. His research focuses on Closed-loop Data Science , Machine Learning in Science , and Mobile Human-Computer Interaction . Notable projects include quantum imaging, music recommender systems, and collaborations with industry leaders like Nokia and Samsung. He served as Director of the SICSA research pool and founding Head of the Information, Data & Analysis Section. Key technical contributions span medical image segmentation , neural network architectures , and biomechanical VR simulations . His work bridges control theory, machine learning, and interactive systems, emphasizing real-world applications in healthcare, robotics, and mobile devices.

Axel Huttمشاهده پروفایل

پژوهشگر

• Neural Systems
• Nonlinear Stochastic Processes
• Data Assimilation
• +۴ مورد دیگر

Dr. Axel Hutt is a senior researcher (Directeur de Recherche) at INRIA Grand Est in Strasbourg, France, leading the MIMESIS team. His work focuses on neural systems modeling, nonlinear dynamics, and data assimilation in complex systems. He holds a PhD from the University of Stuttgart (2001) and an HDR (Habilitation) from the University of Nice (2013). Hutt’s research bridges neuroscience, mathematics, and engineering, with contributions to anesthesia modeling, neurostimulation, and EEG analysis. He has held roles at the Max Planck Institute, Humboldt University Berlin, and the University of Ottawa, and received the Schloessmann Fellowship (2000) and ERC Starting Grant (2011). His current projects include PhD supervision of T. Nette and participation in high-profile conferences like Re:publica and ICMNS. Recent work explores myelination effects, closed-loop neurostimulation, and AI ethics. Education: Physics Diploma (Stuttgart, 1997), PhD (Stuttgart, 2001), HDR (Nice, 2013) Key Roles: INRIA Team Leader (MIMESIS, 2019–present), NeuroSys Team Head (2013–2015) Research Themes: Neural field theory, stochastic processes, clinical neurostimulation applications Publications: Over 180 peer-reviewed articles across journals like Communications Physics and PLoS Computational Biology , focusing on noise-driven dynamics, EEG modeling, and computational psychiatry. Awards: ERC MATHANA Grant (2011), Schloessmann Fellowship (2000)

Vilelmini Kalabratsidouمشاهده پروفایل

عضو هیئت علمی

• Wearable Computing
• Biosignals
• Cognitive Computing
• +۳ مورد دیگر

Vilelmini Kalabratsidou is an Adjunct Lecturer at the University of the Aegean’s Department of Product and Systems Design Engineering on Syros. Her work bridges cognitive computing, wearable technology, and performing arts, focusing on designing interfaces that augment human bodily signals (e.g., heart activity) into interactive experiences. She holds a PhD in Cognitive Computing from Rutgers University (USA) and a dance degree from the Athens Conservatory. Education: PhD in Computer Science (Cognitive Computing), Rutgers University, 2018 MSc in Electronic & Computer Engineering, Technical University of Crete, 2012 Dance Diploma, Athens Conservatory Dance Department Research Interests: Wearable biosensors, real-time biofeedback systems, embodied interaction in dance, data-driven artistic creation, and neuroplasticity interfaces. Her projects often involve collaborative art-science initiatives like the Transition to 8 project, blending social data with music/visual art. Key Contributions: Developed co-adaptive interfaces using heart rate data to steer dance performances and pioneered methods for analyzing bodily signals during social interactions (e.g., sociodrama studies). Her work has been showcased at conferences like Movement and Computing (MOCO) and published in journals like Wearable Technologies and Sensors . Awards: Qualcomm Innovation Fellowship Finalist (2016), Student Entrepreneurship Grand (2011 for a one-button communication system). Labs & Collaborations: Collaborated with Rutgers’ Sensory-Motor Integration Lab, Athena Research Center, and the University of Peloponnese. Active in transdisciplinary projects fusing art, tech, and psychology.

Rafael Diazمشاهده پروفایل

استاد

• Supply Chain Management
• Cybersecurity
• Modeling and Simulation
• +۵ مورد دیگر

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.

Chris Fietkiewiczمشاهده پروفایل

دانشیار

• Computational Neuroscience
• High Performance Computing
• Neural Simulation
• +۷ مورد دیگر

Chris Fietkiewicz is an Associate Professor in the Department of Mathematics & Computer Science at Hobart and William Smith Colleges. He joined the faculty in 2019 and is based in Lansing Hall, with research interests in computational neuroscience and high-performance computing. Research Interests: His work focuses on Computational Neuroscience , particularly the development of neural simulators for educational and clinical applications. He leads the Applied Neural Control Toolkit (ANC Toolkit) , which enables simulation of neural and axonal responses for neuroprosthetic development. His research also spans High Performance Computing , including software optimization, parallel computing, and cluster management tools. Collaborations: He collaborates with Dr. Thomas Mortimer (Case Western Reserve University) on neural stimulation and with Dr. Chen Liu (Tianjin University) on Parkinson’s disease modeling and deep brain stimulation. His publications reflect a strong interdisciplinary focus on biomedical signal processing, control systems, and neuromorphic computing. Publication Trends: His recent work (2016–2022) centers on closed-loop control of pathological neural oscillations, computational models of Parkinson’s disease, and real-time neural simulation. These studies appear in top journals like IEEE Transactions and Biomedical Signal Processing and Control , emphasizing algorithmic innovation and clinical relevance. Scientific Contributions: Co-developer of the ANC Toolkit for neuroscience education. Researcher in neural control systems and HPC optimization. Active contributor to computational models of movement disorders. Advising and Grants: While no formal students are listed, his collaborative projects suggest mentorship of undergraduate and graduate researchers. Grant details are not provided, but his research cluster and web tools indicate funded infrastructure development. Labs and Teams: He is building a research computing cluster and developing web-based batch programming tools, indicating a focus on scalable, accessible computational neuroscience platforms.

Sila Çetinkayaمشاهده پروفایل

استاد

• Supply Chain Analytics
• Healthcare Operations
• Stochastic Optimal Control
• +۳ مورد دیگر

Dr. Sila Çetinkaya is the Cecil H. Green Professor of Engineering and Chair of the Operations Research and Engineering Management (OREM) department at Southern Methodist University’s Lyle School of Engineering. She also holds courtesy appointments in the ITOM department at the SMU Cox School of Business and in Internal Medicine at UT Southwestern Medical Center. Education: Ph.D. in Management Science, McMaster University, 1996 M.S. in Industrial Engineering, Bilkent University, 1991 B.S. in Industrial Engineering, Istanbul Technical University, 1989 Research Focus: Her research spans supply chain analytics , healthcare operations , stochastic optimal control , and applied probability . She investigates complex problems in inventory theory, distribution logistics, closed-loop supply chains, and coordination contracts. Publications & Impact: Her recent work emphasizes stochastic models for shipment consolidation, radiation therapy planning, and healthcare delivery for underserved populations. These studies are published in top-tier journals such as Operations Research , Management Science , and Transportation Research Part E . Awards & Honors: IISE Fellow (2012) CAREER Award, NSF (2001) Outstanding Young Industrial Engineer, IIE (2003) IISE Logistics and Supply Chain Division Teaching Award (2015) Moving Spirit Award, INFORMS (2011) Best Paper Prize, IISE Transactions (2010) Advising & Grants: She has mentored over 15 Ph.D. students and 30 master’s students. Her research has been funded by NSF, DOE, Texas Coordinating Board, Frito-Lay, Nokia, and others. She has led or co-led over 20 grants totaling millions in funding. Service & Leadership: She serves as Department Editor for IISE Transactions and Associate Editor for Naval Research Logistics . She has held leadership roles in INFORMS and IISE, including President of Women in OR/MS and Program Chair for INFORMS 2023.

• Model-based software testing
• Model-based statistical testing (MBST)
• Embedded systems
• +۷ مورد دیگر

Frank Böhr is a PostDoc researcher in the graduate school “Embedded Microsystems” at the Albert-Ludwig-University of Freiburg/Breisgau. He previously studied and conducted research at the Technical University of Kaiserslautern and worked at the Fraunhofer Institute for Experimental Software Engineering (IESE). His work bridges academic research and industrial application, particularly in embedded and automotive software systems. Education: Dipl.-Inf. and Dr.-Ing. from Technical University of Kaiserslautern Professional Affiliation: Fraunhofer IESE, University of Freiburg Teaching: Delivered a lecture on Introduction to Computer Science (Summer 2012) Invited Talks: Presented at the University of Tennessee (2009, 2010) Frank Böhr's primary research interest lies in model-based software testing , with a strong emphasis on model-based statistical testing (MBST) . His work focuses on enhancing the reliability and quality of embedded and real-time systems through rigorous, usage-driven testing methodologies. He investigates how to model software usage effectively using techniques such as stochastic Petri-Nets and Markov chains, and how to apply these models to generate realistic and statistically valid test cases. His research spans both theoretical foundations and practical tool development, aiming to automate the testing process and improve test coverage in industrial settings. The recent publications reflect a consistent focus on applying model-based statistical testing to complex embedded systems, particularly those involving real-time and hybrid behaviors. Key themes include the integration of testing across development phases (MiL, HiL), the modeling of concurrent and timed usage scenarios, and the automation of test case generation from requirements. Many of his works are applied in automotive contexts, demonstrating strong industry relevance. The evolution of his work shows a progression from foundational modeling (e.g., time, duration, concurrency) to integrated solutions combining requirements, models, and automated testing tools like SIMOTEST. Model-Based Statistical Testing (MBST) Usage modeling and operational profiles Reliability estimation for embedded systems Automated test generation from models Simulink-based testing Industrial application in automotive systems Frank Böhr has advised or collaborated on several research projects, particularly during his tenure at Fraunhofer IESE, where he worked with colleagues such as Robert Eschbach, Thomas Bauer, and Taras Beletski on industrial case studies involving mirror control units and embedded automotive systems. While no formal PhD students are listed, his collaborative publications suggest a mentoring and team leadership role in applied research. He has contributed to teaching as a lecturer, indicating involvement in academic training. There is no mention of external research grants in the provided text. His research is closely tied to practical application and industrial collaboration, particularly through his work at Fraunhofer IESE. While no specific lab or team name is given, his involvement in the “Embedded Microsystems” graduate school at Freiburg and prior work within IESE’s research teams indicates participation in structured research groups focused on software engineering for embedded systems. These environments emphasize interdisciplinary collaboration between academia and industry, particularly in automotive and safety-critical domains.

Frank Lagorمشاهده پروفایل

دانشیار

• Estimation and Control for Autonomous Systems
• Fluid Dynamics
• Aerospace Engineering
• +۳ مورد دیگر

Frank Lagor is an Associate Professor in the Department of Mechanical and Aerospace Engineering at the University of Virginia. He joined UVA in 2023 after serving as faculty at the State University of New York at Buffalo. His research focuses on estimation and control for autonomous systems interacting with fluid environments, including gust mitigation in aerospace systems and bio-inspired flow sensing for robotics. Dr. Lagor holds a Ph.D. in Aerospace Engineering from the University of Maryland (2017), with prior degrees from the University of Pennsylvania (M.S., 2009) and Villanova University (B.S., 2006). Before academia, he worked at Lockheed Martin as a Certified Principal Engineer for satellite solar array systems. His research interests emphasize unsteady flow estimation, optimal maneuver design in gust encounters, and reduced-order modeling techniques. Key contributions include sensor placement strategies for data-driven flow estimation and closed-loop control methodologies for autonomous underwater vehicles. He has received prestigious awards including the AFOSR Young Investigator Award (2021) and UB SEAS Early Career Teacher of the Year (2020). Courses taught include advanced control systems theory, dynamics, and stochastic estimation methods.

Heman Shakeriمشاهده پروفایل

استادیار

• Machine Learning
• Learning-Based Control
• Network Science
• +۱۵ مورد دیگر

Heman Shakeri is an Assistant Professor at the School of Data Science, University of Virginia (UVA), where he leads the DYNAMO Lab. He is also a member of the UVA Center of Diabetes Technology and the UVA Cancer Center, reflecting his interdisciplinary research in biomedical applications of machine learning and control systems. Ph.D. in Electrical and Computer Engineering, Kansas State University M.S. in Mechanical Engineering, Amirkabir University of Technology – Tehran Polytechnic B.S. in Mechanical Engineering, Amirkabir University of Technology Dr. Shakeri's research focuses on algorithm development in machine learning , learning-based control , and network science , with applications in diabetes management, single-cell signaling, glaucoma risk assessment, and complex dynamical systems. His work bridges artificial intelligence, control theory, and data science to solve real-world biomedical challenges. The 15 most recent publications highlight a strong trend in dynamical systems modeling , stochastic flow matching , Koopman operator theory , and reinforcement learning for biomedical control . His papers frequently appear in top-tier venues such as ICML, NeurIPS, ICLR, and IFAC, demonstrating consistent innovation in both methodological and applied domains. Dr. Shakeri has received numerous scientific awards and grants, including: NIH R01 Grant ($1.6M) for optimizing renal cancer treatment Capital One Data Design Fellowship ($55k) LaunchPad Grant ($200k) for artificial pancreas research UVA Research Communications Fellow (2024) Multiple pilot awards from UVA Cancer Center, Brain Institute, and Ivy Foundation He actively mentors graduate students and postdoctoral researchers in the DYNAMO Lab, supporting translational research from algorithm design to clinical applications. His lab has secured funding from NIH, NCI, Oracle, and industry partners, indicating strong external validation of his research vision. The lab collaborates extensively with clinical and computational teams across UVA, particularly in diabetes and cancer research. The DYNAMO Lab is a hub for advancing machine intelligence for dynamical systems , with current projects including smart artificial pancreas systems, explainable AI for glaucoma, operator-theoretic methods, and complex network analysis. The lab emphasizes interdisciplinary collaboration, real-world impact, and methodological rigor.

• Petroleum Engineering
• Drilling Engineering
• Wellbore Stability
• +۱۲ مورد دیگر

Bernt Sigve Aadnøy is a Professor in the Department of Energy and Petroleum Engineering at the University of Stavanger, Faculty of Science and Technology. His work bridges theoretical and applied petroleum engineering, with a strong emphasis on drilling operations, well design, and geomechanics. His research focuses on drilling optimization, wellbore stability, drilling fluids, and smart well systems. He has extensively studied the use of nanoparticles in drilling fluids, rate of penetration modeling, torque and drag in 3D wells, and closed-loop drilling optimization. His work integrates computational modeling, laboratory experiments, and field case studies. The recent publications highlight a consistent trend in applying advanced modeling techniques—including machine learning, finite element analysis, and stochastic optimization—to solve complex drilling challenges. Topics include nanoparticle-enhanced fluids, real-time mechanical specific energy minimization, and autonomous downhole control systems, reflecting a strong interdisciplinary approach combining petroleum engineering with data science and control theory. Bernt Sigve Aadnøy has collaborated with numerous researchers and students, contributing to advancements in drilling safety, efficiency, and sustainability, particularly in challenging environments such as the Arctic and deep-water reservoirs.