جست‌وجوی استاد و پژوهشگر

Claudio De Persisمشاهده پروفایل

استاد

• Automatic Control
• Data-driven Control
• Cyber-Physical Systems
• +۴ مورد دیگر

Claudio De Persis is a Professor in the Faculty of Science and Engineering at the University of Groningen, Netherlands. He holds a Laurea degree (cum laude) in Electrical Engineering from the University of Rome La Sapienza (1996) and a PhD in Control Systems (2000) from the same institution. His research focuses on automatic control, particularly data-driven control, nonlinear systems, cyber-physical systems, and energy systems. He has held academic positions at the University of Rome La Sapienza (2002–2011), the University of Twente (2009–2011), and currently leads the Groningen Center for Systems and Control within the Engineering and Technology Institute. His expertise includes fault detection in nonlinear systems, resilient control under Denial-of-Service attacks, and distributed control of energy networks. He has authored over 250 publications, including seminal works on quantized control and cyber-physical systems. He serves on editorial boards of journals like Automatica and IEEE Transactions on Automatic Control . De Persis has received two IEEE Outstanding Paper Awards for contributions to control theory. His research integrates control theory with data science, addressing challenges in smart grids and distributed systems. He holds patents for energy system control and collaborates on interdisciplinary projects, such as data center optimization and resilient networked systems. His current research emphasizes data-driven methods for controller synthesis, leveraging convex optimization and system identification to ensure stability and performance. He also explores privacy-preserving distributed control algorithms for power networks and aggregative games.

Yi-Zhuang Youمشاهده پروفایل

دانشیار

• Condensed Matter Physics
• Quantum Entanglement Dynamics
• Topological Phases
• +۴ مورد دیگر

Yi-Zhuang You is an Associate Professor in the Department of Physics at the University of California, San Diego (UCSD). He holds a Ph.D. from Tsinghua University (2013). His research focuses on theoretical investigations of correlated topological phases, quantum entanglement dynamics, and machine learning applications in many-body systems. Key areas include deconfined quantum criticality, symmetry-protected topological (SPT) phases, and the interplay between topology and quantum matter. His work bridges condensed matter physics and high-energy physics, exploring topics such as topological responses in gauge theories, entanglement holography, and quantum machine learning. Recent studies involve machine learning-driven approaches to quantum state preparation, symmetry discovery, and tomographic reconstruction of quantum systems. His contributions span theoretical frameworks for understanding topological transitions, fractionalization in lattice models, and the role of symmetry in quantum critical phenomena. Notable research highlights include the study of symmetric mass generation as a deconfined quantum criticality mechanism, the application of classical shadow tomography for efficient quantum state estimation, and the development of algorithms for self-similar dynamics modeling. His publications frequently intersect with experimental proposals for observing topological phases in materials like graphene and iridates. Dr. You’s affiliations include the UCSD Physics Department, with collaborations extending to institutions globally. His research is supported by grants focusing on quantum information, topological materials, and machine learning applications in physics. While no specific awards are listed, his work has been widely cited in high-impact journals across condensed matter and theoretical physics.

• Control Systems
• Model Predictive Control
• Power Systems Engineering
• +۳ مورد دیگر

Morten Hovd is a Professor in the Department of Engineering Cybernetics at the Norwegian University of Science and Technology (NTNU). His research focuses on advanced control systems, model predictive control (MPC), power electronics, and optimization algorithms. He has contributed significantly to the development of robust control strategies for uncertain systems and has published extensively in leading journals and conferences in the field of control engineering. His research interests span several key areas in control systems engineering, including model predictive control, nonlinear control systems, optimization under uncertainty, and applications in power systems and energy efficiency. He is particularly known for his work on discrete-time bilinear systems, modular multilevel converters (MMCs), and the integration of machine learning techniques with control theory. His contributions address both theoretical advancements and practical implementations in industries such as energy and petroleum engineering. Hovd's recent publications highlight advancements in energy-efficient control systems, stochastic surrogate modeling for subsurface flows, and optimization algorithms tailored for complex engineering problems. His work often combines rigorous mathematical frameworks with real-world applications, such as improving the reliability of power systems and enhancing reservoir management through data-driven methods. He is actively involved in teaching courses such as TTK4210 (Advanced Control of Industrial Processes) and TK8118 (Mini-seminar in Cybernetics). His research has led to innovations in fault detection for power systems, energy-efficient building climate control, and robust MPC strategies for uncertain systems.

Raúl Suárez Feijóoمشاهده پروفایل

پژوهشگر

• Robotized Assembly
• Fine Motion Planning
• Robotized Grasping and Manipulation
• +۴ مورد دیگر

Summary Raúl Suárez Feijóo is a Researcher at the Universitat Politècnica de Catalunya (UPC) in the Institut d'Organització i Control de Sistemes Industrials (IOC). Born in Asturias, Spain (1959), he holds an Electronic Engineering degree from the National University of San Juan, Argentina (1984), and a Doctorate in Engineering from UPC (1993). His research focuses on robotized assembly, fine motion planning, grasping, and multi-robot systems. He has led the IOC as Deputy Director (2003–2009) and Director (2009–2016). He coordinates doctoral programs in Automation and Robotics at UPC. Suárez has authored numerous publications and received awards including the Best Paper Award at IEEE ISATP (1995) and the Best Reviewer Award at ICRA (2015). Education: Electronic Engineer (1984, Argentina), Doctor Engineer (1993, UPC) Leadership Roles: Director of IOC (2009–2016), Coordinator of Doctoral Programs Research: Over 100 publications in robotics, emphasizing grasping, manipulation, and industrial automation. His work includes contributions to robotic hands, motion planning, and collaborative robotics. Notable projects involve 5G-enabled robotic systems and multi-AGV traffic management. Awards highlight his impact in both international and national robotics communities.

Emanuele Crisostomiمشاهده پروفایل

دانشیار

• Smart Grids
• Electric Vehicles
• Control Systems
• +۲ مورد دیگر

Emanuele Crisostomi is Associate Professor of Electrical Systems at the University of Pisa's Department of Energy, Systems, Territory and Constructions Engineering. He holds PhD and graduate degrees in Automation Engineering from the University of Pisa, with research visits to University of Cambridge, University of Leicester, and Hamilton Institute. His research bridges control theory, energy systems, and smart mobility. His research integrates: Smart grid control and renewable energy integration Electric vehicle charging infrastructure and routing algorithms Urban traffic modeling and optimization Nonlinear system dynamics and Lyapunov stabilization Machine learning applications in energy systems Crisostomi's publications demonstrate consistent innovation in electric vehicle-grid integration, with recent focus on predictive charging control, highway EV circulation patterns, and hydropower monitoring. His work shows increasing application of deep reinforcement learning for multi-regional power systems and hybrid network models for infrastructure monitoring. He leads research on IoT-enabled energy efficiency in buildings and contributes to epidemic modeling through network science. Current projects examine battery sizing optimization, charging station scheduling under uncertainty, and synergetic building management systems integrating environmental monitoring with energy conservation.

• Control Theory
• Applied Mathematics
• Computational Mechanics
• +۷ مورد دیگر

Goong Chen is a Professor at Texas A&M University (TAMU) within the College of Arts & Sciences. His research focuses on Control Theory, Applied Mathematics, and interdisciplinary applications in computational mechanics, fluid dynamics, and quantum systems. He holds a Ph.D. from the University of Wisconsin (1977) and a B.S. from National Tsing-Hua University (1972). His research interests span computational biomechanics, forensic modeling, nanofluidics, and mathematical physics. Recent work includes modal analysis of animal motion, crash mechanics of aircraft, and forensic reconstruction of disasters. He has contributed to theoretical advancements in PDEs, nonlinear dynamics, and quantum computing. Chen’s articles address cutting-edge topics like thermoelastic plates, Volterra equations, and DFIM systems. He has pioneered numerical methods for complex systems using OpenFOAM and finite element techniques. His computational models have been applied to real-world scenarios such as submarine implosions and chemical warfare forensics. No academic awards are explicitly listed, but his extensive publication record reflects significant contributions to applied mathematics and engineering. He leads research teams focused on interdisciplinary challenges in computational science and engineering.

Mohamed Gharibمشاهده پروفایل

عضو هیئت علمی

• Vibration Control
• Robotics Systems Design
• Dynamic Systems
• +۴ مورد دیگر

Dr. Mohamed Gharib is an Instructional Associate Professor in the Department of Engineering Technology and Industrial Distribution at Texas A&M University's College of Engineering. He also serves as Program Coordinator for Multidisciplinary Engineering Technology and holds affiliated faculty status in Multidisciplinary Engineering. His roles include teaching, research leadership, and academic program development. Educational Background: Ph.D., Mechanical Engineering, Southern Methodist University (2011) M.S., Aerospace Engineering, Cairo University (2007) B.S., Aerospace Engineering, Cairo University (2002) Research Interests: Dr. Gharib focuses on advanced engineering systems and education innovation. His technical work spans vibration control , robotics systems design , and impact mechanics , with notable contributions to drill string vibration suppression and novel damping technologies. In education, he pioneers STEM outreach programs and curriculum development, including initiatives like the Awesome STEM Lab and e-STEM programs . His COBOTICS Lab integrates robotics research, undergraduate training, and community engagement. Research Impact: Recent work addresses dexterous robotics (via NSF's HAND ERC), adaptive control algorithms for drilling systems, and advanced composite coatings for tribological applications. His publications emphasize real-world applications in oil well operations, structural acoustics, and educational technology. Awards: Francisco José de Caldas Award for Sustainable Excellence (2021) Excellence in STEM Implementation Award (ASME, 2020) Outstanding Graduate Student Awards (2010) Labs & Programs: Director of the COBOTICS Lab , which develops robotic systems, control technologies, and STEM education tools. Active in multidisciplinary projects like the NSF-funded Human Augmentation via Dexterity (HAND ERC) collaboration.

• Signal Processing
• Machine Learning
• Acoustics
• +۷ مورد دیگر

Luis Antonio Azpicueta Ruiz is an Associate Professor in the Department of Signal Theory and Communications at Carlos III University of Madrid. He leads research in the Signal Processing and Learning Group (GTSA) and Machine Learning for Data Science (ML4DS) group, focusing on interdisciplinary applications spanning acoustics, telecommunications, and machine learning. Research Interests: His work bridges signal processing theory with practical applications in environmental acoustics, adaptive filtering systems, and machine learning. Key research themes include: Advanced adaptive filtering architectures for nonlinear systems Distributed estimation in sensor networks Acoustic echo cancellation and room equalization Psychoacoustic evaluation methods Machine learning applications in noise monitoring and sound analysis Research Projects: Principal investigator for multiple funded projects including: Diagnóstico del ruido de chorro en aeronaves (AEI, 2022-2025) LearnINg FLow and Noise Dynamics via AI (COMUNIDAD DE MADRID, 2024-2026) BODYinTRANSIT - Sensory-driven Body Transformation (EUROPEAN COMMISSION, 2022-2026) Aprendizaje Automático para análisis Big Data (MINISTERIO DE ECONOMÍA, 2018-2021)

Thomas Chaffeyمشاهده پروفایل

مدرس

• Nonlinear Control Theory
• Convex Optimization
• Circuit Theory
• +۳ مورد دیگر

Dr. Thomas Chaffey is a Lecturer in the School of Electrical and Computer Engineering at The University of Sydney. His research focuses on nonlinear control theory, convex optimization, and neuromorphic systems. He obtained his PhD from the University of Cambridge (2022) and held the Maudslay-Butler Fellowship at Pembroke College, Cambridge (2022–2025). Education: PhD in Control Theory, University of Cambridge (2022) Maudslay-Butler Fellowship in Engineering, Pembroke College, Cambridge (2022–2025) Master's in Mechanical Engineering, University of Sydney (Australia) Bachelor's in Mathematics and Computer Science, University of Sydney (Australia) Research Interests: Nonlinear control theory and its intersections with optimization and circuit theory Development of neuromorphic systems and analog hardware simulation Monotone operator methods and large-scale optimization algorithms Key Research Trends in Articles: Advances in graphical methods for nonlinear system analysis (e.g., scaled relative graphs) Analysis of neuromorphic circuits using convex optimization frameworks Exploration of symmetry properties in physical systems Awards: Best Student Paper Award, 2021 European Control Conference Outstanding Student Paper Award, 2021 IEEE Conference on Decision and Control Labs/Teams: Leading projects on learning in physical systems and monotone circuits Collaborations with institutions like Lund University and University of British Columbia

• Signal processing
• Fault detection and diagnosis
• Rotordynamics
• +۷ مورد دیگر

Konstantinos Gryllias is a Professor in the Department of Mechanical Engineering at KU Leuven's Faculty of Engineering Sciences. He leads research in the Mechatronic System Dynamics (LMSD) unit at the Arenberg campus. His academic affiliations extend across multiple KU Leuven institutes including Leuven.AI, Leuven.AM (Additive Manufacturing), and the Gravitation Institute. He serves on important governance bodies as a member of the Faculty Council of Engineering Sciences, Faculty Doctoral Committee of Engineering Sciences, and Departmental Council of Mechanical Engineering. Dr. Gryllias specializes in signal processing, fault detection and diagnosis of rotating machinery, condition monitoring, and machine learning applications in structural health monitoring. His research spans linear and nonlinear vibrations, anomaly detection, rotordynamics, and pattern recognition. His work bridges theoretical signal processing with practical engineering applications in wind turbines, marine propulsion systems, and industrial machinery. His recent publications demonstrate strong focus on deep learning approaches for wind turbine anomaly detection, bearing diagnostics, stern bearing lubrication optimization, and structural health monitoring using advanced signal processing techniques. The research shows increasing integration of explainable AI methods with traditional vibration analysis. Dr. Gryllias teaches advanced courses including Monitoring & Prognostics, Structural Dynamics, Smart Sensing Technologies, and Applied AI perspectives. His teaching portfolio reflects the interdisciplinary nature of his research, connecting mechanical engineering fundamentals with cutting-edge AI methodologies. He currently leads multiple research projects through 2025-2029, primarily as Promotor, focusing on fault detection in gears using fiber optic sensors, multi-sensor monitoring of drivelines, physics-inspired machine learning for condition monitoring, and digital twin applications for wind turbine efficiency improvement.

Victor Gabriel Lopez Mejiaمشاهده پروفایل

پژوهشگر

• Control Theory
• Machine Learning
• Multi-Agent Systems
• +۳ مورد دیگر

Dr. Victor Gabriel Lopez Mejia is a postdoctoral researcher at the Institute of Automatic Control Engineering, Faculty of Electrical Engineering and Computer Science, Leibniz University Hannover. His work focuses on data-driven control systems, reinforcement learning, and multi-agent system synchronization. PhD in Electrical Engineering (2019), University of Texas at Arlington M.Sc. in Electrical Engineering (2013), CINVESTAV, Mexico B.Sc. in Telecommunications and Electronics (2010), Universidad Autonoma de Campeche Research interests include: Neural network applications in control systems Reinforcement learning for cooperative control Game-theoretic analysis of multi-agent systems Data-based modeling of nonlinear dynamics Publications highlight advancements in data-driven predictive control, Gaussian process-based estimation, and nonlinear system analysis, with recent work in IEEE Transactions on Automatic Control and conferences like CDC and ECC. He has held academic roles including Adjunct Professor at the University of Texas at Arlington and Research Assistant at UTARI (2016-2019).

Vahé Nerguizianمشاهده پروفایل

استاد

• Telecommunications
• Bioengineering
• Cancer Cell Detection
• +۸ مورد دیگر

Vahé Nerguizian is a full Professor in the Department of Electrical Engineering at École de technologie supérieure (ÉTS) in Montreal, Canada, where he has established himself as a leading researcher in microelectronics, MEMS, and biomedical applications. Affiliated with the LACIME (Communications and Microelectronic Integration Laboratory), his work bridges engineering disciplines with healthcare innovations, particularly in cancer research and point-of-care diagnostics. His educational background includes a B.Ing. from Polytechnique Montréal, an M.Eng. from McGill University, and a Ph.D. from Concordia University. This strong foundation in electrical engineering has enabled his interdisciplinary research across multiple domains. Nerguizian's research focuses on the intersection of microfluidics, MEMS, and biomedical applications, with particular emphasis on cancer cell detection, liposome production for drug delivery, and microelectronic integration for healthcare solutions. His laboratory develops microfluidic devices for synthesizing nanoparticles and liposomes, with applications in cancer therapeutics and diagnostics. The work combines microwave engineering, bio-MEMS, and microelectronics to create innovative diagnostic tools and therapeutic delivery systems. His recent publications (2021-2025) demonstrate a clear trajectory toward increasingly sophisticated biomedical applications of microfluidic and MEMS technologies, with growing emphasis on cancer research, extracellular vesicle analysis, and therapeutic delivery systems. The research has evolved from fundamental MEMS and microwave engineering toward highly translational biomedical applications. 2015: Excellence in Teaching Award from the Board of Directors Nerguizian has supervised over 25 graduate students across doctoral and master's programs, with current projects focusing on microfluidic systems for nanoparticle synthesis and sensor systems for biomolecule detection. His research has received significant funding through collaborations with medical researchers, particularly with Julia Burnier's team at McGill University. The LACIME laboratory, where he conducts his research, provides state-of-the-art facilities for micro- and nanofabrication, integrated circuit design, and photonic microsystems. As part of the LACIME research group, Nerguizian contributes to a dynamic environment focused on both fundamental and applied research with strong industry connections. The laboratory's work spans from materials science to communication protocols, with particular strength in developing innovative solutions for healthcare applications.

Puren Ouyangمشاهده پروفایل

دانشیار

• Robotics and Control
• Mechatronics
• Integrated Design and Control
• +۱ مورد دیگر

Dr. Puren Ouyang serves as an Associate Professor in the Department of Aerospace Engineering at Toronto Metropolitan University, where he holds a Professional Engineering license (PEng). His academic foundation includes a BASc from Huazhong University of Science and Technology (1985), followed by MSc and PhD degrees from the University of Saskatchewan (2002, 2005). He teaches core courses including AER 509 Control Systems, AER 520 Stress Analysis, and AE 8141 Advanced Aerospace Manufacturing. His educational credentials: PhD in Engineering, University of Saskatchewan (2005) MSc in Engineering, University of Saskatchewan (2002) BASc in Engineering, Huazhong University of Science and Technology (1985) Ouyang pioneered position domain control methodology, replacing traditional time/frequency references with position-based systems to enhance robotic precision in contour tracking. His research directly addresses industrial manufacturing challenges where 24/7 machine reliability determines product accuracy. Key focus areas include robotic control systems, mechatronics integration, hybrid system dynamics, and synchronized multi-DOF manipulation for CNC applications. His 2013-2016 publications reveal consistent innovation in position-domain robotics control, with emphasis on contour tracking algorithms, multi-axis synchronization, and adaptive learning techniques. These works bridge theoretical control frameworks with industrial manufacturing applications, frequently targeting CNC machine optimization where 80% of North American factories rely on automated systems. Key recognitions: Best Conference Paper in Integration Award at IEEE ICIA 2011 NSERC Postdoctoral Fellowship (2005-2007) As an active supervisor, Ouyang mentors graduate students in robotics and control systems through the ISRMM Laboratory. His NSERC fellowship demonstrates sustained research capability, while his industry-focused publications suggest ongoing grant activity in advanced manufacturing automation. Current supervision availability indicates active research program development. The Intelligent Systems & Robotics / Micro Manufacturing (ISRMM) Laboratory serves as his primary research hub, driving innovations in robotic precision manufacturing, micro-scale production systems, and real-time control architectures for industrial applications.

• Stochastic Control
• Financial Mathematics
• Probability
• +۲ مورد دیگر

Nacira Agram is an Associate Professor at Kungliga Tekniska Högskolan (KTH), specializing in stochastic analysis, mean-field processes, and mathematical finance. She contributes to education through roles as Examiner and Teacher in advanced financial mathematics courses. Research Focus: Her work centers on stochastic differential equations with applications to financial markets, energy systems, and population modeling. Key areas include conditional McKean–Vlasov jump diffusions, singular control of stochastic Volterra equations, and deep learning applications in stochastic modeling. Publications: Recent research explores mean-field control, optimal stopping, and SPDEs with space interactions, emphasizing advanced mathematical techniques for financial and ecological systems. Teaching: Currently involved in courses like Financial Derivatives and Martingales and Stochastic Integrals , where she serves as course responsible and examiner.

• Integrated optics
• Nanocrystals
• Nanomaterials
• +۱۱ مورد دیگر

Lorenzo Pavesi is a Full Professor of Experimental Physics at the Department of Physics, University of Trento (Italy), where he leads the Nanoscience Laboratory with 25 members. His academic career spans over 30 years, including roles as Assistant Professor (1990), Associate Professor (1999), and Full Professor (2002). He founded semiconductor optoelectronics research at the university and established photonics laboratories focused on growth and advanced treatment of materials. Research Focus: Silicon photonics, quantum optics, nonlinear optics, optical sensors, and neuromorphic computing. Leadership: IEEE Italian Chapter on Nanotechnology founder, editorial board member for Frontiers in Physics , ETRI Journal , and Sensors . His work bridges photonics and electronics, with recent advancements in integrated quantum photonics and neuromorphic systems. He has managed numerous national and international projects, holds 9 patents, authored over 500 papers, and edited 15+ books. Awards include the Cavaliere title (2001), IEEE Distinguished Speaker (2010-2011), and fellowships from IEEE, SPIE, and SIF.