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Sajjad Fattaheian DehkordiView profile

Researcher

• Power Systems Engineering
• Smart Grids
• Renewable Energy Integration
• +3 more

Sajjad Fattaheian Dehkordi is a Postdoctoral Researcher in the Department of Electrical Engineering and Automation at Aalto University, Espoo, Finland. His research focuses on advanced energy management systems for modern power grids, with emphasis on distributed and transactive control approaches for resilient and efficient grid operations. His core research interests include: Power system resilience under high renewable penetration Microgrid and energy community optimization Distributed energy resource integration Electric vehicle-grid interaction and V2G systems Real-time congestion and ramping management Analysis of his 2022-2024 publications reveals a dominant trend toward multi-agent transactive frameworks addressing grid stability challenges. His work consistently targets voltage regulation, asymmetrical power flows, and ramping events in distribution systems, leveraging optimization techniques like MILP while incorporating flexibility concepts for renewable integration. Key innovations include distance-driven P2P/P2G transactions and incentive-based congestion management. No scientific awards are documented in the available records. Information regarding student advising, research grants, or leadership roles is not provided in current documentation.

• Control Systems Engineering
• Aeronautical Engineering
• Wind Turbine Dynamics
• +5 more

Maria Tomas Rodriguez is a Senior Lecturer in Mechanical and Aeronautical Engineering at City University London. She has been with the institution since 2007, initially as a Lecturer (2007-2014) and promoted to Senior Lecturer in 2014. Prior to her position at City University, she was a Postdoctoral Research Associate at Imperial College London and a Research Assistant at the University of Sheffield. Dr. Rodriguez earned her Licenciatura in Physics from Universidad Complutense de Madrid, followed by a Masters and PhD in Control Systems Engineering from the University of Sheffield. She further completed an MPhil in Aeronautical Engineering at Imperial College London, establishing her interdisciplinary expertise spanning physics, control systems, and aeronautics. Her research primarily focuses on nonlinear control systems applied to diverse platforms including floating offshore wind turbines, rotorcraft dynamics, marine vehicles, and motorcycle suspension systems. She has developed innovative methodologies for dynamic modeling, stability analysis, and control of complex mechanical systems, with particular emphasis on vibration reduction and oscillation damping in challenging environments. Her work bridges theoretical control approaches with practical engineering applications in renewable energy and vehicle dynamics. Her publication record shows consistent output across multiple domains, with recent work concentrating on floating offshore wind turbine technology, helicopter dynamics, and advanced control techniques for autonomous systems. The interdisciplinary nature of her research is evident in her collaborations across engineering disciplines and institutions. Dr. Rodriguez has extensive experience in supervising research and teaching across mechanical engineering and aeronautics disciplines. Her technical expertise spans nonlinear dynamics, system identification, control theory, and their applications to complex engineering systems in marine, aerospace, and automotive contexts. She maintains active research in structural dynamics and control for renewable energy systems, particularly focusing on floating wind turbine technology, where she has developed methodologies for stability analysis, vibration identification, and motion control of these complex marine structures.

Vassilios AngelidisView profile

Professor

• Power Electronics
• Renewable Energy Sources
• Electrical Power Systems
• +1 more

Professor Vassilios Angelidis is a distinguished academic in the field of Electrical Engineering, currently serving as a Professor at the Department of Electrical and Computer Engineering of Democritus University of Thrace. He joined the university in June 2024, bringing with him extensive international experience from prestigious institutions including the University of Glasgow, University of Sydney, University of New South Wales (UNSW), and the Technical University of Denmark. Professor Angelidis received his educational foundation with a degree in Electrical Engineering from Democritus University of Thrace, followed by a Master of Applied Science from Concordia University in Canada, and a PhD from Curtin University in Western Australia. He further enhanced his expertise with an MBA from Curtin Graduate School of Business. His research interests span Power Electronics, Renewable Energy Sources, Electrical Power Systems, and Autonomous Electricity Networks. Professor Angelidis has made significant contributions to the development of advanced power conversion techniques, grid integration of renewable energy sources, and the application of artificial intelligence in power system analysis and prediction. His work has been instrumental in advancing the field of smart grid technologies and sustainable energy systems. An analysis of his recent publications reveals a strong focus on power electronics applications in renewable energy integration, particularly in photovoltaic systems and electric vehicle charging infrastructure. His research demonstrates expertise in developing advanced algorithms for power system monitoring and control, with particular emphasis on frequency estimation, phase angle calculation, and power quality enhancement in modern grids with high penetration of distributed energy resources. Among his notable scientific achievements, Professor Angelidis has been recognized as an IEEE Fellow for his significant contributions to power electronics and the conversion and integration of renewable energy sources into power grids. He has also received the prestigious Advanced Research Fellowship for young researchers from the Engineering and Natural Sciences Council of the United Kingdom. Throughout his career, Professor Angelidis has secured research funding from various organizations across Australia, the United Kingdom, Denmark, China, India, and Malaysia, as well as industry partners with global reach. He has served on the International Councils of Beijing Jiaotong University and Universiti Tenaga Nasional (UNITEN), and currently holds the position of Vice President-elect of the IEEE Power Electronics Community. At Democritus University of Thrace, Professor Angelidis is affiliated with the Electrical Machines Laboratory within the Energy Systems Sector, where he leads research on Control and Diagnostic Methods of Electrical Machines. His current work focuses on advancing the integration of renewable energy sources into electrical power systems while maintaining grid stability and reliability.

Konstantinos G. ArvanitisView profile

Professor

• Electrification
• Automation
• Digitalization in Agriculture
• +23 more

Konstantinos G. Arvanitis is a Professor in the Department of Natural Resources Management & Agricultural Engineering at the Agricultural University of Athens, affiliated with the Agricultural Engineering Laboratory. He holds a PhD in Electrical and Computer Engineering from the National Technical University of Athens and has held diverse research and teaching roles across Greek institutions. Teaches courses on electrical engineering, sensors, automation, and AI in agriculture Supervised 2 PhD, 9 MSc theses, and guides 6 ongoing PhD projects Member of FEANI, EurAgEng, and IFAC Technical Committee (2000-2017) His research integrates IoT, machine learning, and cyber-physical systems into agricultural practices, focusing on precision agriculture and sustainability. He contributes to editorial boards of journals like Sensors and Energy , and has published over 342 technical works with significant citation metrics. His recent work explores quantum technologies, edge computing, and 3D printing in agricultural systems, emphasizing energy efficiency and educational innovation. He actively reviews for 130+ journals and conferences.

Oscar Esparza MartinView profile

Professor

• Network Security
• Information Security
• Cryptography
• +5 more

Oscar Esparza Martin is a Professor at the Department of Telecommunications Engineering within the Barcelona School of Telecommunications Engineering at Universitat Politècnica de Catalunya (UPC). He is an active researcher with over 222 academic activities documented, specializing in network security and information security. His work spans multiple research groups including ISG - Grup de Seguretat de la Informació and ISG-MAK - Information Security Group - Mathematics Applied to Cryptography. Dr. Esparza Martin holds a Telecommunications Engineering degree and a Doctorate from UPC, with postgraduate studies in Networks, Advanced Broadcasting Systems and Services. His expertise centers on network security, with significant contributions to blockchain security, IoT security, satellite communications security, and data exchange protocols. His recent research output shows strong focus on secure blockchain applications, particularly with his work on DA2Wa (a secure pairing protocol between DApps and wallets), and data exchange protocols with free sampling services. His publications span high-impact journals including Computer Communications, IEEE Access, and Electronics. Award or recognition Dr. Esparza Martin actively participates in numerous international conferences as committee member, particularly in areas of IoT, wireless communications, vehicle technology, and security. His collaborations span multiple institutions with key partners including Muñoz Tapia, Soriano Ibáñez, Alins Delgado, and Mata Diaz. His research is supported by various competitive projects including the Cátedra CARISMATICA and Catalonia Digital Innovation Hub (DIH4CAT). His work connects theoretical cryptography with practical security implementations across multiple domains including blockchain, IoT, satellite communications, and data marketplaces, demonstrating both academic rigor and practical relevance to current security challenges.

• Robotics
• Autonomous System Design
• Control Theory and Applications
• +3 more

Abdurrahman Yılmaz is an Assistant Professor at Istanbul Technical University's Department of Control and Automation Engineering within the College of Electrical-Electronics. His career spans academic and industrial roles, including a Research Assistant position at Istanbul Technical University (2018-2022) and Test Rig Design Engineer at ASELSAN INC. (2014). Education: PhD in Control and Automation Engineering (Istanbul Technical University, 2014-2022) MSc in Mechatronics Engineering (Yildiz Technical University, 2014-2017) BSc in Electronics Engineering (Istanbul Technical University, 2009-2014) Double Major in Control and Automation Engineering (Istanbul Technical University, 2011-2014) Research Interests focus on Robotics, Autonomous System Design, and Control Theory. His work includes localization frameworks for autonomous mobile robots, adaptive control algorithms for quadcopters, and soft haptic sensing technologies. Recent research explores digital twin simulators and quadruped robot dynamics. Scientific Output trends highlight advancements in mobile robot navigation, industrial automation, and autonomous systems. Publications span journals like Journal of Field Robotics and conferences including TAROS and RoboSoft. Awards: The Most Successful Doctoral Thesis Award of 2022 (University, 2023) 1st Water Management Awards (Ministry of Forestry and Water Affairs, 2019) Collaborations extend to international researchers in robotics and control systems. He serves as PI for the project "Development of a Design-Aiding Analysis Tool for Four-Legged Robots" (2023-2024).

• Control Engineering
• Process Control
• Optimal Control
• +11 more

Torsten Wik is a Professor in Control Engineering at Chalmers University of Technology. He leads the Control Engineering research group and focuses on process control with theoretical and applied methodologies. Institution: Chalmers University of Technology Department: Control Engineering His research spans optimal control, model reduction, and systems with model uncertainties. Applications include energy-saving systems, environmental improvement, biological systems (water purification, recirculating fish farms, LED greenhouse lighting), and battery estimation/modeling/control. Recent work emphasizes battery degradation diagnosis, state estimation, fast charging, and reconfigurable systems. Key methodologies include physics-informed frameworks, machine learning integration, entropy-based predictive algorithms, and hypergraph modeling. Applications extend to electric vehicles, photovoltaic systems, fuel cells, and biofilm reactors. Publications highlight collaborations across engineering domains, focusing on control theory, electrochemical modeling, and real-time optimization. His work bridges theoretical advancements with industrial applications in energy systems, transportation, and sustainable agriculture.

Yunlong ZhangView profile

Professor

• Traffic operations
• Transportation modeling and simulation
• Intelligent transportation systems
• +2 more

Dr. Yunlong Zhang is a Professor at the Zachry Department of Civil & Environmental Engineering at Texas A&M University and holds a joint appointment with the Texas A&M Transportation Institute. With over 35 years of experience in transportation engineering, he specializes in traffic operations, transportation modeling, intelligent transportation systems, and AI applications in transportation. Ph.D. in Transportation Engineering from Virginia Tech (1996) M.S. in Highway and Traffic Engineering from Southeast University (1987) B.S. in Civil Engineering from Southeast University (1984) Research Interests: Traffic flow modeling, simulation, and analysis Traffic control devices and signal systems Safety analysis in transportation Evaluation of connected and autonomous vehicle (CAV) technologies Artificial intelligence and advanced computing applications Professional Affiliations: Joint appointment with Texas A&M Transportation Institute Member and sub-committee chair of TRB’s Artificial Intelligence and Advanced Computing committee

Yafeng YinView profile

Professor

• Transportation Systems
• Sustainable Transportation
• Urban Infrastructure Systems
• +5 more

Yafeng Yin is Professor of Civil and Environmental Engineering and Professor of Industrial and Operations Engineering at the University of Michigan, College of Engineering, where he serves as Donald Malloure Department Chair of Civil and Environmental Engineering and holds the Donald Cleveland Collegiate Professorship in Engineering. His educational background includes: PhD in Civil Engineering from University of Tokyo (2002) ME in Civil Engineering from Tsinghua University (1996) BE in Environmental Engineering from Tsinghua University (1994) BE in Structural Engineering from Tsinghua University (1994) Dr. Yin's research centers on developing sustainable and economically efficient transportation systems through analysis, modeling, design, and optimization. He investigates how emerging technologies—including connected/automated vehicles, electric vehicles, drones, and mobile sensing—impact transportation demand and supply. His work extends to interdependencies between transportation, power, and communications networks in urban infrastructure systems. Key focus areas include mobility services, ride-sourcing markets, traffic management, and integration of artificial intelligence in transportation. His recent publications (2023-2025) demonstrate a pronounced shift toward leveraging large language models and agent-based frameworks for transportation analysis, with significant emphasis on on-demand mobility services (ride-sourcing, food delivery), traffic control with connected vehicles, and economic implications of emerging technologies. The research spans theoretical foundations in game theory and optimization to practical applications in urban settings. As director of the Lab for Innovative Mobility Systems, Dr. Yin leads interdisciplinary research developing solutions that enhance transportation efficiency, reliability, safety, and service diversity through technological integration. His work bridges theoretical modeling with real-world implementation challenges in evolving transportation ecosystems.

Corina SanduView profile

Professor

• Multibody Dynamics
• Vehicle Systems Engineering
• Terramechanics
• +5 more

Corina Sandu is the Robert E. Hord Jr. Professor in the Department of Mechanical Engineering at Virginia Tech. She leads the Terramechanics, Multibody, and Vehicle Systems Laboratory, focusing on advanced modeling of multibody dynamics, vehicle-terrain interaction, and tire performance optimization. Her research integrates computational methods, experimental validation, and interdisciplinary approaches to address challenges in off-road mobility, autonomous systems, and vehicle dynamics. Dr. Sandu holds a Ph.D. (2000) and M.S. (1995) in Mechanical Engineering from the University of Iowa, complemented by an Engineering Diploma in Mechanics from the Bucharest Polytechnic Institute (1991). She serves as the President of the International Society for Terrain-Vehicle Systems and chairs the SAE Fellow Committee, underscoring her leadership in automotive and mechanical engineering fields. Her research interests span: Uncertainty quantification in multibody systems Optimization of vehicle dynamics and tire performance Terramechanics and terrain-vehicle interaction modeling Sensitivity analysis and adjoint methods for complex systems Recent publications highlight innovations in tire-ice interface models, hydroplaning risk estimation, and advanced multibody system simulation frameworks. She has pioneered experimental methodologies for tire performance evaluation on ice and soft soils, linking material science with mechanical engineering principles. Her work impacts automotive safety, off-road vehicle design, and autonomous systems, with applications in both industry and academia. Awards include recognition for her contributions to terrain-vehicle systems research and leadership in professional societies.

• Control Systems Engineering
• Mechatronics
• Condition Monitoring
• +5 more

Roger Dixon is a Professor of Control Systems Engineering at the University of Birmingham's School of Engineering and a Visiting Professor at Loughborough University. His expertise spans applied control systems, mechatronics, condition monitoring, fault detection, and systems engineering. He holds a PhD from Lancaster University (1996) and has led major research initiatives in academia and industry, publishing over 150 papers. His work focuses on rail, road, aerospace, and energy sectors, emphasizing innovative solutions for industrial challenges. Education: BEng (Hons) Mechanical Engineering, Lancaster University (1992) MSc Mechatronics, Lancaster University (1993) PhD Control Systems Engineering, Lancaster University (1996) Research Interests: His research integrates advanced control strategies, fault detection, and condition monitoring. Key areas include: Rail infrastructure (e.g., fault-tolerant track switches) Aerospace actuator systems and fault-tolerant designs Energy systems (e.g., LNG platform monitoring) Model-based control and simulation Professional Highlights: Notable contributions include the 2013 REPOINT railway track switch concept and 2003 gas turbine fault-tolerant control patents. He chairs the UK Automatic Control Council (2017–2020) and has editorial roles in international journals. Awards: Fellow of the IMechE (2011) Fellow of the Higher Education Academy (2006) Chartered Engineer (2000) Lab & Collaborations: Leads the Control Systems theme at the Birmingham Centre for Railway Research & Education (BCRRE), focusing on rail innovation and multidisciplinary projects.

Tieming LiuView profile

Associate Professor

• Supply Chain Coordination
• Logistics Planning
• Healthcare Data Analytics
• +4 more

Dr. Tieming Liu is an Associate Professor in the School of Industrial Engineering and Management at Oklahoma State University , where he has served since 2005, first as Assistant Professor and then promoted to Associate Professor in 2011. His expertise bridges operations research, supply-chain coordination, healthcare analytics, renewable-energy policy, and production scheduling. Education Ph.D. in Transportation and Logistics, Massachusetts Institute of Technology, 2005 M.S. in Industrial Engineering and Management Science, Northwestern University, 2001 M.S. in Control Theory and Control Engineering, Tsinghua University, 2000 B.S. in Control Theory and Control Engineering, Tsinghua University, 1997 Research Interests Dr. Liu’s scholarship is organized around three pillars: Supply-Chain & Logistics: coordination contracts, inventory bounds, responsive pricing, channel rebates, and production flexibility under uncertainty. Healthcare Analytics: machine-learning models for diabetic retinopathy and sepsis risk prediction, clinical decision-support systems, and handling imbalanced EHR data. Energy & Sustainability: renewable portfolio standards, capacity coordination with renewable energy certificates, and incentive mechanisms for renewable and conventional generators. Recent methodological contributions include hidden Markov models for continuous mortality prediction, tree-augmented Bayesian networks for sepsis risk, and tensor-completion-driven convolutional networks for longitudinal medical data. Scientific Awards & Honors EJOR Reviewer Award, 2019 IEM Faculty Award, 2019 Halliburton Outstanding Faculty Award, OSU, 2014 Merrick Foundation Teaching Award, OSU, 2013 Riata/Koch Faculty Fellow, OSU, 2012 Lockheed Martin Teaching Award, OSU, 2011 Student Organization Faculty Advisor of the Year, OSU, 2010 Student Mentorship & Collaboration Dr. Liu has advised or co-advised a large cohort of doctoral and master’s students whose names appear as first or co-authors on his publications. His collaborative network spans MIT, Northwestern, IBM T. J. Watson Research Center, and multiple departments across OSU, fostering interdisciplinary projects that integrate operations research with real-world healthcare, transportation, and energy challenges. Laboratories & Teams He conducts research within the analytics and optimization laboratories of the School of Industrial Engineering and Management, directing projects funded by federal agencies and industry partners aimed at next-generation decision-support systems for healthcare providers, logistics operators, and energy market regulators.

Didier TheilliolView profile

Professor

• Fault Tolerant Control
• Control Engineering
• Aerospace Systems
• +3 more

Didier Theilliol is a Professor of Control Engineering at the University of Lorraine, France, since 2004. He holds a Ph.D. in Control Engineering from Nancy-University (1993). He was awarded the CAS Visiting Professorship by the Chinese Academy of Sciences (CAS) in 2012, during which he collaborated with the Shenyang Institute of Automation (SIA) on flight control and fault-tolerant systems. His research focuses on model-based fault diagnosis (FDI), fault-tolerant control (FTC) for complex systems, and reliability analysis, with applications in aerospace, industrial automation, and robotics. Education: Ph.D. in Control Engineering (Nancy-University, 1993). Research interests include advanced control strategies for linear and nonlinear systems, multi-agent coordination, and safety-critical applications. His work integrates theoretical advancements with practical implementations across industries such as steel production, wastewater treatment, and aerospace. Notable contributions include methodologies for degradation management, distributed observer design, and health-aware control. Recent article trends emphasize fault-tolerant control in multi-agent systems, reinforcement learning for safety-critical tasks, and integration of physics-informed neural networks for system modeling. His publications span topics from model-based diagnostics to real-world applications in UAVs and propulsion systems. Awards: CAS Visiting Professorships for Senior International Scientists (2012). Collaborations include co-working with SIA’s rotorcraft UAV project team and leading European R&D initiatives. He serves as Associate Editor for ISA Transactions and Unmanned Systems , and chairs conferences on fault-tolerant control systems. His research also extends to Bayesian networks for system reliability and particle filter-based prognostics in industrial settings. Labs/Teams: Active in the State Key Laboratory of Robotics (visited during his CAS tenure) and coordinates projects within the German-French Institute for Automation and Robotics.

Dan NegrutView profile

Professor

• Computer Modeling and Simulation
• Autonomous Vehicles
• High Performance Computing
• +3 more

Professor Dan Negrut is a faculty member in the Department of Mechanical Engineering at the University of Wisconsin–Madison, affiliated with the College of Engineering. He holds the Mead Witter Foundation Chaired Professorship and is a recognized leader in high-performance computing and robotics simulation. Education: PhD in Mechanical Engineering, University of Iowa (1998) BS in Mechanical Engineering, Polytechnic Institute of Bucharest (1992) Research Interests: Computer modeling and simulation of robots and autonomous vehicles High-performance computing and GPU-accelerated algorithms Fluid-solid interaction and granular dynamics Terramechanics and extraterrestrial mobility Autonomous systems and sensor simulation Recent Contributions: His work focuses on advancing physics-based simulation tools like Project Chrono , which supports open-source frameworks for robotics, autonomous vehicles, and granular systems. Recent trends in his publications emphasize sim-to-real gap quantification, lunar rover mobility, and AI-driven digital twins. Awards: NSF CAREER Award (2009) NVIDIA CUDA Fellow (2010) LEED Scholar (2017) ASME Best Paper Awards (2017–2023) Advising & Grants: He advises graduate students in mechanical engineering and computer science, focusing on robotics and autonomous systems. His research is supported by federal grants and industry partnerships. Notable projects include the Synchrono platform for autonomous vehicle simulation and Chrono::Electronics for electro-mechanical systems. Labs & Teams: His team develops Project Chrono , an open-source simulation engine used globally for robotics, automotive, and aerospace applications. Collaborations span academia and industry to address challenges in autonomous systems and space exploration.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +5 more

Bo Wang is an active academic researcher primarily affiliated with multiple Chinese institutions, with strong connections to Tsinghua University, Beijing Jiaotong University, and other leading Chinese universities. His research spans artificial intelligence, machine learning, computer vision, medical image analysis, and intelligent control systems, demonstrating significant interdisciplinary work across computer science, engineering, and biomedical applications. Primary institutional affiliation: School of Computer Science and Technology at multiple Chinese universities Active research areas: AI/ML applications in healthcare, computer vision, federated learning, and intelligent control systems Extensive publication record across top-tier venues in multiple disciplines Wang's research interests focus on the intersection of artificial intelligence and practical applications. His work demonstrates strong expertise in developing novel machine learning architectures for medical image analysis, including applications in CT imaging, MRI, and sperm tracking. He has made significant contributions to federated learning approaches for large language models, sliding mode control systems, and molecular optimization frameworks. His research consistently bridges theoretical advances with practical implementations across healthcare, manufacturing, and environmental monitoring domains. Analysis of Wang's recent publications reveals a strong trend toward interdisciplinary AI applications, particularly in medical imaging and bioinformatics. His work on VAE-GANMDA for microbe-drug association prediction, ACE-QSM for accelerating MRI acquisition, and text-guided molecular optimization demonstrates innovative approaches at the intersection of AI and life sciences. Wang also maintains active research in industrial applications including digital twin technology for energy systems and robust scheduling approaches for multi-factory production. Notable research contributions include: FLFT: A Large-Scale Pre-Training Model Distributed Fine-Tuning Method with Federated Learning VAE-GANMDA: Microbe-drug association prediction model ACE-QSM: Accelerating quantitative susceptibility mapping using diffusion models Digital twin-empowered power consumption prediction systems Wang actively collaborates with researchers across China and internationally, with publications spanning computer science, engineering, medical imaging, and environmental science journals. His work demonstrates strong technical depth across multiple AI methodologies while maintaining focus on practical applications that address real-world challenges in healthcare, manufacturing, and environmental monitoring.