جست‌وجوی استاد و پژوهشگر

Andrew van Paridonمشاهده پروفایل

مدرس ارشد

• Thermal Management
• Spacecraft Propulsion
• Thermal Modeling
• +۷ مورد دیگر

Dr. Andrew van Paridon is a Senior Lecturer and Research Associate in the Sibley School of Mechanical and Aerospace Engineering at Cornell University. His work bridges advanced thermal systems research and innovative engineering education, with a focus on aerospace applications and satellite technology. Education: B.E. in Mechanical and Aerospace Engineering, University of Queensland (2010) B.Sc. in Physics, University of Queensland (2010) Ph.D. in Aerospace Engineering, University of Oxford (2016) Dr. van Paridon's research interests center on thermal management , particularly in satellites and propulsion systems, as well as system optimization and spacecraft design . He has made significant contributions to thermal modeling in both aerospace and turbomachinery contexts, including the development of the Transient Heat Transfer Facility and reduced-order modeling techniques. His educational initiatives include co-organizing the SmallSat Mission Design School and exploring mastery-graded assessment methods to improve learning outcomes in core engineering courses like Statics and Mechanics of Solids. His recent publications reflect a strong trajectory in space-based thermal systems , water-based propulsion , and SmallSat mission design , with emerging work on exoplanet imaging and zodiacal light observation. These works span experimental, computational, and systems-level approaches, demonstrating interdisciplinary innovation. Scientific Awards: Rolls Royce’s Civil Large Engine Best Patent award Dr. van Paridon has been actively involved in mentoring through course development and outreach programs with the Sciencenter and Cornell’s Office of Engagement Initiatives. While formal advisees are not listed, his leadership in educational programs indicates a strong commitment to student development. He has also contributed to grant-funded research through facility development and thermal modeling innovations. His work with the SmallSat Mission Design School suggests ongoing collaboration with space systems teams and potential future projects in space exploration and in-situ resource utilization. He leads and contributes to research teams focused on thermal systems and satellite technology, integrating academic research with practical engineering solutions.

Xanthi S. Papageorgiouمشاهده پروفایل

استادیار

• Neuro-Robotics
• Human-Robot Interaction
• Robot Control Systems
• +۸ مورد دیگر

Xanthi S. Papageorgiou is an Assistant Professor in the Department of Product & Systems Design Engineering (DPSD) at the University of the Aegean's School of Engineering (2025–present). She concurrently serves as Head of the Robotics and Cognitive Systems Unit at UBITECH in Athens and Limassol. Her academic roles also include adjunct positions at National Technical University of Athens (NTUA) School of Mechanical Engineering (2022–2024), University of Athens Department of Physics (2019–2021), and others. She holds a Mechanical Engineering Diploma (2003) and PhD (2009) from NTUA, with postdoctoral research at NTUA's Intelligent Robotics Lab (2013–2018). Research focuses on neuro-robotics, human-robot interaction, rehabilitation robotics, and adaptive control systems. Her work addresses challenges in gait analysis for mobility assistance devices, assistive bathing robots, and real-time human state estimation. Key contributions include user-adaptive control frameworks, gait stability prediction, and multimodal sensing integration. Publications span over 70 peer-reviewed articles in IEEE journals and conferences. Awards include multiple Thomaidion Awards (NTUA), Best Paper Awards, and scholarships from Eugenides Foundation. She reviews for international journals and conferences and is active in IEEE Robotics & Automation Society. Her labs and projects include the I-Support assistive bathing system and the development of robotic platforms for elderly care. Research collaborations span academia and industry, addressing both technical and clinical validation aspects of robotic systems.

Pierre Haessigمشاهده پروفایل

پژوهشگر

• Energy Management
• Dynamic Optimization
• Stochastic Optimization
• +۳ مورد دیگر

Pierre Haessig is a researcher and teacher at CentraleSupélec's Rennes campus, part of the Automation Team within the Rennes Institute of Electronics and Telecommunications (IETR). His work focuses on optimal energy management of storage systems (batteries) integrated with renewable energy sources like wind and photovoltaic. Research addresses uncertainties in energy inputs, such as solar variability and load fluctuations, using stochastic optimization techniques. He teaches Automation and Electrical Engineering in engineering programs. Affiliations: CentraleSupélec, IETR (Rennes) Key Research Areas: Energy Management, Stochastic Optimization, Renewable Integration, Battery Aging Models His publications (36+) explore topics like microgrid optimization, Kalman filter-based battery state estimation, and the impact of uncertainties on energy systems. He has contributed to open-source benchmarks like Solar Home 2020 and collaborated on projects involving hardware-in-the-loop testing for power electronics. His research emphasizes real-world applications in resilient energy systems and control strategies. Notable contributions include developing convex models for battery aging and advancing methods for anticipative/non-anticipative microgrid sizing. His work bridges theoretical optimization with practical implementations in energy storage and renewable integration.

Amir Shahiriniaمشاهده پروفایل

دانشیار

• Power Electronics
• Renewable Energy Systems
• Smart Grids
• +۵ مورد دیگر

Amir Shahirinia is an Associate Professor of Electrical and Computer Engineering at the University of the District of Columbia (UDC), leading the Electrical Engineering Undergraduate Program and directing the Smart Grids & Artificial Intelligence Laboratory (SGAI) and the Center of Excellence for Renewable Energy (CERE). He holds a Ph.D. in Electrical and Computer Engineering from the University of Wisconsin-Milwaukee. His research focuses on power electronics, renewable energy systems, AI-driven smart grid optimization, and electric vehicle technologies. He has secured grants from the National Science Foundation, Department of Defense, and other agencies, and has been recognized with awards such as the UDC Outstanding Professor (2020-21) and Chancellor Award for Academic Excellence (2010-14). Research interests include developing high-efficiency power converters, integrating renewable energy into smart grids, applying machine learning for grid resilience, and advancing wireless power transfer systems. He is an editorial board member of Frontiers in Energy Research and has presented at IEEE conferences on topics like copula-based dependence modeling and Kalman filter applications. His work spans academic leadership, curriculum development, and K-12 outreach in energy systems and cybersecurity. Leadership Roles: Director of SGAI Lab, CERE, and EE Undergraduate Program Key Awards: NSF grants (2019-2020), Best Paper Awards (2020), and multiple teaching recognitions Grants: Includes projects on wind-penetrated systems, robotics in smart grids, and streamflow modeling using Bayesian methods Labs/Teams: SGAI Lab (AI in energy systems), CERE (renewable energy innovation)

• Applied Mathematics
• Mathematical Physics
• Battery Technology
• +۴ مورد دیگر

Dr. Wei Pan is an Honorary Research Fellow in the Department of Mathematics at Imperial College London, affiliated with the Faculty of Natural Sciences. His research focuses on applied mathematics, mathematical physics, and computational modeling with applications in energy systems, particularly fuel cells and lithium-ion batteries. He specializes in developing advanced models for electrochemical systems, integrating machine learning and multi-physics approaches to address challenges in energy storage and conversion. Dr. Pan's work spans interdisciplinary areas including electrochemistry, thermal engineering, and material science. His affiliations include the Mathematics of Planet Earth initiative and the Stochastic Analysis Research Group, reflecting his commitment to applied mathematical research with real-world impact. His recent publications highlight innovative methods for fuel cell performance optimization, battery state-of-charge estimation, and degradation modeling to enhance energy system reliability and efficiency. Key research trends in his articles include the application of reduced-order models, machine learning-driven simulations, and coupled electrochemical-thermal-mechanical frameworks to improve energy storage technologies. His methodologies emphasize practical implementation through computational tools and multi-scale analysis. Dr. Pan has not listed any awards or grants in the provided text, but his affiliations suggest ongoing collaborations within Imperial College's research networks. No advising roles or student supervision details are available in the current data.

• Antennas and Propagation
• 5G/6G Communications
• Integrated Sensing and Communications (ISAC)
• +۶ مورد دیگر

Distinguished Professor Yingjie Jay Guo is a leading academic at the University of Technology Sydney (UTS), holding positions as Professor and Director of multiple research centers including the Global Big Data Technologies Centre and the NSW Connectivity Innovation Network (CIN). His expertise spans antennas and propagation, 5G/6G communications, and integrated sensing and communications (ISAC). He has authored over 700 publications, including 350+ IEEE journal papers and six books, and holds 27 international patents. His research focuses on reconfigurable antennas, hybrid arrays, and environmental sensing using 5G/6G networks. Education: PhD (Antennas and Electromagnetics) from Xi'an Jiaotong University (1984–1987), BEng/MEng (Microwave Engineering) from Xidian University (1977–1984). Leadership Roles: Chair of ISAP International Steering Committee (2020–2021), Guest Editor for IEEE Transactions on Antennas and Propagation, and Member of Standards Australia IoT Committee. Research Contributions: Pioneered hybrid antenna arrays, base station antennas, and the Generalized Joined Coupler (GJC) matrix theory, earning the IEEE Schelkunoff Prize Paper Award (2023). His recent work includes environmental sensing projects with NSW governments to mitigate flood risks, leveraging 5G/6G networks. He has led over 30 best paper awards and is a Fellow of the Australian Academy of Engineering, Royal Society of NSW, and IEEE. Current projects include multibeam antenna systems, in-band full-duplex communications, and AI-driven metasurface design. Key Grants: NSW Smart Flood Sensing Initiative, TPG Telecom collaborations, and ARC Discovery Projects. Students: Supervised numerous PhD/MSc students in antenna design, sensing, and wireless systems. Labs: Director of TPG-UTS Network Sensing Lab and founder of GBDTC and NSW CIN.

Will Boylesمشاهده پروفایل

استادیار

• Statistical Education
• Classroom Resource Development
• Spatial Statistics
• +۳ مورد دیگر

Will Boyles is an Assistant Professor of Statistics at Whitman University. He holds a Ph.D. in Statistics from Texas A&M University (2023) and a B.S. in Mathematical Statistics with a minor in Environmental Studies from Wake Forest University (2018). His research focuses on statistical education, classroom resource development, and spatial/environmental statistics. He teaches courses including Introduction to Statistics , Statistics with Applications , and Statistical Modeling . Recent publications explore university mathematics assessments and ensemble Kalman filter methods for weather modeling. Email: boylesw@whitman.edu

• Meteorology
• Climate Change
• Severe Weather Prediction
• +۵ مورد دیگر

Víctor Homar Santaner is a Professor in the Meteorology Group at the University of the Balearic Islands (UIB) . His research focuses on Mediterranean climate systems , severe weather predictability , and high-resolution ensemble forecasting . Currently supervising two doctoral students, he has contributed to understanding flash floods , secondary cyclones , and climate change impacts through over 65 peer-reviewed articles. Key research areas: Severe Weather , Climate Adaptation , Data Assimilation Major projects: HyMeX Program , PREGRIDBAL Rainfall Atlas Editorial roles: Associate Editor at Atmospheric Research Recent work explores Liouville equation solutions for ensemble prediction limits, convection-permitting models in Maritime Continent studies, and quantile–quantile calibration of regional climate projections. His team's hydraulic simulations of the 2018 Sant Llorenç flood demonstrate the low predictability of extreme convective systems in data-scarce Mediterranean regions.

Yaakov Bar-Shalomمشاهده پروفایل

استاد

• Control Systems
• Signal Processing
• Estimation Theory
• +۳ مورد دیگر

Yaakov Bar-Shalom is a Professor in the Department of Electrical and Computer Engineering at the University of Connecticut's Storrs campus. His research focuses on control systems, signal processing, and estimation theory with applications to tracking systems and sensor fusion. He has contributed to foundational work in probabilistic data association and Kalman filtering. Contact: ybs@engr.uconn.edu | Phone: (860) 486-4823 | Address: 371 Fairfield Way, U-4157, Storrs, CT 06269-4157

Ivan Petrovićمشاهده پروفایل

استاد

• Control Systems
• Robotics
• Computer Vision
• +۳ مورد دیگر

Ivan Petrović is a Full Professor at the Department of Control and Computer Engineering, Faculty of Electrical Engineering and Computing (FER), University of Zagreb. His research focuses on advanced control systems, mobile robotics, computer vision, and estimation theory, with significant contributions to autonomous navigation, path planning, and sensor fusion techniques. Specializations in robotics , SLAM , visual odometry , and nonlinear control systems . Recent work includes transformer-based gesture recognition pipelines, uncertainty-aware calibration methods, and reinforcement learning approaches for soft robotic control. His projects integrate probabilistic models, deep learning, and geometric algorithms for real-time autonomous systems. For collaboration or further information, contact: ivan.petrovic@fer.unizg.hr

Sabah Badri-Höherمشاهده پروفایل

استاد

• Digital Signal Processing
• Underwater Robotics
• Sonar and Image Processing
• +۴ مورد دیگر

Sabah Badri-Höher is a Professor at the Kiel University of Applied Sciences (UAS Kiel) in the Department of Digital Signal Processing. She leads the AUV team 'TomKyle' in collaboration with GEOMAR Helmholtz Centre for Ocean Research Kiel and oversees projects like MAUS (autonomous underwater vehicles) and UFOTriNet (automated fish detection). Research Focus: Her work spans digital signal processing, underwater robotics, sonar data interpretation, acoustic communication, and computer vision. Key applications include AUV navigation, fish tracking, and underwater sensor networks. Publications: Recent articles emphasize sonar-based fish detection, AUV collision avoidance, cooperative swarm navigation, and signal processing for underwater environments. Trends include machine learning integration (e.g., Kalman filters, deep learning) and multi-sensor fusion. Student Advising & Projects: She supervises doctoral candidates in signal processing, computer vision, and underwater systems. Major grants include: MAUS: Development of interconnected AUVs for coordinated missions. UFOTriNet: Automated fish population monitoring using low-light cameras/sonar. Labs & Teams: Heads the DSV research group, collaborating with GEOMAR on student AUV teams. The lab focuses on underwater robotics, sensor algorithms, and participates in competitions like SAUC-E.

Bosen Lianمشاهده پروفایل

استادیار

• Cooperative Control
• Graphical Games
• Inverse Reinforcement Learning
• +۹ مورد دیگر

Bosen Lian is an Assistant Professor in the Department of Electrical and Computer Engineering at Auburn University's College of Engineering. He received his Ph.D. in Electrical Engineering from the University of Texas at Arlington, where he also served as a postdoctoral researcher and adjunct professor before joining Auburn in August 2023. His research focuses on distributed control, reinforcement learning, game theory, and their integration in cyber-physical and robotic systems. Research Interests: His work centers on designing safe, optimal, and resilient multi-agent systems through data-driven control and inverse reinforcement learning. Key areas include cooperative control, graphical games, robotics, distributed estimation, and anomaly detection in autonomous systems. He applies these methods to robotic platforms such as robot arms, unmanned vehicles, and sensor networks. His recent publications show a strong trend in leveraging inverse reinforcement learning for multi-agent and adversarial systems, with applications in tracking, estimation, and optimal control. He frequently publishes in top IEEE journals and Automatica, demonstrating consistent contributions to control theory and machine learning integration. Scientific Awards and Recognition: Appointed Associate Editor at IEEE Transactions on Neural Networks and Learning Systems Appointed Associate Editor at IEEE Transactions on Cybernetics Appointed Associate Editor at Transactions of the Institute of Measurement and Control Published first textbook: 'Integral and Inverse Reinforcement Learning for Optimal Control Systems and Games' Advising and Grants: He actively mentors students and researchers such as Wenqian Xue, Vrushabh S. Donge, and others, many of whom are co-authors on his publications. While specific grant details are not listed, his continuous publication output and editorial appointments suggest strong research support and funding. His lab conducts rigorous theoretical analysis alongside practical robotic applications. Labs and Teams: His research group focuses on cyber-physical feedback systems, working on both theoretical algorithms and real-world implementations. The team explores dynamic clustering, consensus, and learning-based control in networked environments, maintaining a balance between provable guarantees and data efficiency.

• Stochastic Control
• Probabilistic Modeling
• Decentralized Control Systems
• +۷ مورد دیگر

Dr. Yuyang Zhou is a Lecturer in the School of Computing, Engineering and the Built Environment at Edinburgh Napier University, where he contributes to the Centre for Artificial Intelligence and Robotics. His research focuses on advanced control systems, probabilistic modeling, and intelligent robotics, with active involvement in EU-funded projects such as iMARS (2024–2028). Institution: Edinburgh Napier University School: School of Computing Engineering and the Built Environment Research Centre: Centre for Artificial Intelligence and Robotics Role: Lecturer Email: Y.Zhou@napier.ac.uk Dr. Zhou's research centers on stochastic and nonlinear control systems, with a strong emphasis on decentralized and probabilistic frameworks. His work integrates machine learning, entropy-based monitoring, and message-passing algorithms to enhance system performance under uncertainty. Key domains include smart grids, industrial prediction systems, and robotics. The recent publications highlight a consistent trend in developing innovative control strategies for complex stochastic systems. These include event-triggered relearning, variance and entropy assignment, and fully probabilistic design methods. The research spans applications in industrial automation, energy systems, and future grid technologies, demonstrating a strong interdisciplinary approach combining AI, control theory, and IoT. Dr. Zhou supervises postgraduate research students, including Anna Chernikova (Hybrid and Switched Control Systems) and Fatima Mumtaz (AI-driven smart banking). He collaborates extensively with Prof. Randa Herzallah and is a co-investigator on the European Commission-funded iMARS project, which aims to develop intelligent multi-agent robotic systems for first responders using AI, IoT, and 5G technologies.

Raymond de Callafonمشاهده پروفایل

استاد

• System Identification
• Control Theory
• Adaptive Control
• +۱۳ مورد دیگر

Raymond de Callafon is a Professor in the Department of Mechanical and Aerospace Engineering (MAE) at the University of California, San Diego (UCSD). He is a key faculty member in the Dynamic Systems & Control (DS&C) group, where he conducts research and teaches in system identification, adaptive control, and modeling of mechatronic systems. He directs the System Identification and Control Laboratory (SICL) and manages the CMRR Servo Laboratory, both at UCSD. His work bridges theoretical control with practical applications in data storage, aerospace, and vibration control systems. M.Sc., Mechanical Engineering, Delft University of Technology, 1992 Ph.D., Mechanical Engineering, Delft University of Technology, 1998 Raymond de Callafon's research centers on experiment-based modeling, control-relevant system identification, and recursive/adaptive control. His interests extend to nonlinear and linear parameter varying (LPV) systems, with applications in hard disk drives, tape storage systems, active noise and vibration control, and aeroelastic flutter prediction. He has developed modeling techniques applied to structural damage detection and controller tuning for high-precision systems. His recent publications reflect a strong trend in closed-loop system identification, Hammerstein models, adaptive disturbance rejection, and high-precision motion control in data storage devices. The articles span both theoretical advances and experimental validations, often involving dual-stage actuators and real-time control implementations. Co-authored book: Realtime Controller Tuning for Periodic Disturbance Rejection Developed MATLAB toolboxes: LTSfit, CLOSID, FREQID NASA-funded research on flutter control and aeroservoelastic systems Active collaboration with CMRR and industry partners in data storage Raymond de Callafon has advised multiple graduate students and contributed to significant research projects involving adaptive control, robotic systems, and coordinated ocean sensing networks. His teaching includes both graduate and undergraduate courses in system identification, control theory, and laboratory-based engineering education. He has also established the Undergraduate Control Laboratory (UGCL) and taught in the COSMOS summer program on kinetic sculptures. His laboratories, SICL and CMRR Servo Lab, are equipped with advanced facilities for sound and vibration control, real-time prototyping, and high-precision motion experiments, supporting both academic and industrial research in control engineering.

• Applied Mathematics
• Numerical Methods
• Differential Equations
• +۹ مورد دیگر

Jesús Cardenal Carro is a Professor in the Department of Applied Mathematics at the Ferrol Engineering Polytechnic University College, part of the University of A Coruña (UDC). He teaches a wide range of courses across engineering disciplines, including Numerical Methods, Differential Equations, Linear Algebra, and specialized topics in mobility and industrial design. He is actively engaged in research through the Observatorio para el diseño e innovación en movilidad, medios de transporte y automoción, contributing to both academic and applied engineering projects. His research interests span Applied Mathematics , Computational Mechanics , Multibody System Dynamics , and Automotive and Mobility Engineering . He focuses on numerical methods, inertial data filtering, vehicle dynamics, and the development of test benches for simulating mechanical motion. His work bridges theoretical mathematics with practical engineering applications in automotive and industrial systems. The recent articles highlight a strong trend in applied computational mechanics, particularly in vehicle dynamics, numerical simulation, and sensor data processing. Many publications focus on the development and validation of algorithms for orientation estimation from inertial sensors, simulation of mechanical systems, and practical engineering solutions such as vehicle conversions and test bench design. Collaborations with researchers like Javier Cuadrado and Eduardo Bayo Pérez are frequent and long-standing. No scientific awards were explicitly mentioned in the provided text. Jesús Cardenal Carro has directed multiple final degree and master’s theses in Industrial Engineering, including those of José Augusto Antón Nacimiento and Alvaro Deibe Díaz. He has participated in numerous research projects funded by national programs such as the Programa Nacional de Investigación del Transporte, the Secretaria Xeral de Investigación e Desenvolvemento Tecnolóxico, and international entities like the U.S. Army Research Office. These projects span areas of multibody dynamics, vehicle systems, and applied mechanics. He is affiliated with the research group Observatorio para el diseño e innovación en movilidad, medios de transporte y automoción, which focuses on innovation in transportation and automotive design. His work involves close collaboration with industry partners such as NAVANTIA and LABORATORIO OFICIAL DE VEHÍCULOS HISTÓRICOS, as well as academic networks including the Asociación Española de Ingeniería Mecánica (AEIM) and IFToMM.