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Xuyang WuView profile

Associate Professor

• Distributed Optimization
• Machine Learning
• Federated Learning
• +3 more

Xuyang Wu is an Associate Professor at the School of Automation and Intelligent Manufacturing (AiM), Southern University of Science and Technology (SUSTech), China. Previously, he served as an Assistant Professor at SUSTech and held a postdoctoral position at KTH Royal Institute of Technology in Sweden under Professors Mikael Johansson and Sindri Magnússon. He completed his PhD in Communication and Information Systems at the University of Chinese Academy of Sciences (2015–2020) and a B.S. in Applied Mathematics from Northwestern Polytechnical University (2011–2015). His research focuses on distributed optimization, federated learning, and large-scale machine learning algorithms, emphasizing theoretical guarantees and practical implementations. Notable projects include safe resource allocation in power networks and asynchronous algorithms for distributed systems. He has published extensively in top-tier journals like IEEE Transactions on Automatic Control and conferences such as ICML and ICLR. Dr. Wu has received recognition including a best student paper finalist award at IEEE ICCA 2019. His work bridges theoretical advancements with real-world applications in smart networks and cyber-physical systems.

Josef KittlerView profile

Professor

• Pattern Recognition
• Computer Vision
• Image Analysis
• +5 more

Josef Kittler is a Professor at the University of Surrey, affiliated with the School of Computer Science and Electronic Engineering and the Centre for Vision, Speech and Signal Processing (CVSSP). He holds editorial roles in journals like IEEE Transactions on Pattern Analysis and Machine Intelligence and serves on the IAPR's KS Fu Prize Committee. His research focuses on pattern recognition, computer vision, and applications in system identification, medical diagnosis (ECG), and automatic inspection. He has received prestigious awards, including the Honorary Medal from the Czech Technical University. His work spans theoretical advancements and practical implementations, with notable contributions to multimodal tracking, deep learning, and fusion techniques. Education & Roles: Research Assistant, Engineering Department, University of Cambridge (1973–75) SERC Research Fellow, University of Southampton (1975–77) Royal Society European Research Fellow, Paris (1977–78) IBM Research Fellow, Balliol College, Oxford (1978–80) Principal Research Associate/Scientific Officer, Rutherford Appleton Laboratory (1980–85) Research Interests: Kittler's work emphasizes theoretical and applied aspects of pattern recognition, including computer vision applications in security, healthcare, and robotics. His recent publications address challenges in multimodal tracking, self-supervised learning, and fusion algorithms. Awards: Best Paper Awards from Pattern Recognition Society, British Machine Vision Association, and IEE Honorary Medal (Czech Technical University, 1995) Advising & Grants: While specific student/advisor details aren’t listed, his leadership in CVSSP and editorial roles indicates extensive mentorship and collaborative projects. His research has been supported by grants enabling advancements in AI and computer vision. Labs & Teams: He leads the CVSSP, a world-renowned center for vision, speech, and signal processing research, fostering interdisciplinary projects in AI and multimedia systems.

• Automatic control systems
• Optimization and estimation systems
• Nonlinear and high-performance systems
• +4 more

Alexey Pavlov is a Professor in Petroleum Cybernetics at the Norwegian University of Science and Technology (NTNU), leading the BRU21 program. He holds a PhD in Mechanical Engineering from Eindhoven University of Technology (2004), an MSc in Applied Mathematics from St. Petersburg State University (1998), and has industrial experience at Equinor and Ford Motor Co. His research focuses on automatic control systems, optimization, signal processing, and human-machine interaction, with applications in petroleum engineering, mechatronics, and medical fields. Current projects include digital solutions for oil and gas, high-performance systems, and shared human-machine control via haptics. Past work includes leading R&D projects at Equinor on drilling automation, production optimization, and heavy oil systems. He has supervised 8 completed PhD projects and authored over 120 publications, including the book Uniform Output Regulation of Nonlinear Systems (2005). His awards include the IEEE Control Systems Technology Award (2015) and multiple recognitions for academic and industrial contributions. Prof. Pavlov serves on editorial and program committees for IEEE, IFAC, and other conferences, and is a Senior Member of IEEE. His leadership in the BRU21 initiative aligns with Norway’s OG21 strategy for innovation in petroleum technology.

Kamran EntesariView profile

Professor

• Radio Frequency Integrated Circuits
• RF Photonics
• Microwave Sensing Systems
• +5 more

Kamran Entesari is a Professor of Electrical and Computer Engineering at Texas A&M University, holding the Texas Instruments Engineering Professorship. His research focuses on RF/microwave/mm-wave integrated circuits, integrated RF photonics, and biochemical sensing systems. He leads projects in silicon photonics, millimeter-wave communication, and dielectric spectroscopy. Education: Ph.D., Electrical Engineering, University of Michigan, Ann Arbor (2005) M.S., Electrical Engineering, Tehran Polytechnic University (1999) B.S., Sharif University of Technology (1995) Research Interests: RFIC and mm-wave systems for 5G and beyond Photonic-integrated circuits for next-gen communication Biomedical sensing via microwave dielectric spectroscopy Low-power, high-linearity transceiver architectures His work bridges silicon photonics with traditional RF systems to enable high-speed, low-power solutions. Recent Research Trends: Recent publications emphasize hybrid CMOS-silicon photonics for mm-wave front-ends, full-duplex transceivers, and ultra-wideband sensing systems. Key innovations include reconfigurable photonic filters, beamforming networks, and interferometric sensors. Awards: IEEE Fellow (2025) Qualcomm Faculty Award (2017, 2018) NSF CAREER Award (2011) Outstanding Faculty Award (2012) Grants & Labs: Leads the SpecEES Initiative for energy-efficient mm-wave platforms. Collaborates with Texas Instruments on silicon photonics integration. His lab develops prototypes ranging from chip-scale sensors to phased array systems. Facility Affiliations: Based in the Wisenbaker Engineering Building (WEB 315C), part of Texas A&M's College of Engineering. Active in the Department's photonics and RFIC research clusters.

Mike FaganView profile

Lecturer

• Programming Languages
• Automatic Differentiation
• High-Level Languages
• +3 more

Mike Fagan is a Lecturer in Computer Science and Research Scientist at Rice University. He holds a B.A. in Mathematics, Mathematical Sciences, and Electrical Engineering, an M.S. in Electrical Engineering, and a Ph.D. in Computer Science, all from Rice University. His research focuses on programming language design, automatic differentiation, and high-level language implementation. He has contributed to tools like HPCToolkit for performance analysis of parallel programs and explored inexact computation strategies to improve energy efficiency in supercomputing. Dr. Fagan has taught courses such as Introduction to Computer Systems, Cyber-Physical Systems, and Advanced Algorithms. His pedagogical approach emphasizes problem-solving and personalized instruction through class-wide collaborative sessions. He has collaborated on projects addressing energy-precision tradeoffs in computing systems and received a Distinguished paper award in 2009 for work on performance analysis of petascale applications. Education: B.A./M.S./Ph.D. in Mathematics/EE/CS (Rice University) Research: Programming Languages, Automatic Differentiation, Parallel Computing Tools: HPCToolkit, OpenAD/F Awards: Distinguished Paper Award (2009) His career has been entirely at Rice University, balancing research and teaching since 1991. He has explored innovative approaches to overcoming hardware limitations through inexact computing and contributed to advancing methodologies for scientific programming and libraries.

• Control Systems
• Optimization
• Engineering Education
• +7 more

Dr. Paul N Beuchat is a Senior Lecturer - Education Specialist in the Department of Electrical and Electronic Engineering at the Faculty of Engineering and Information Technology. His expertise spans control systems, optimization techniques, and engineering education, with a focus on approximate dynamic programming and its applications in robotics and autonomous systems. Education : PhD in Automatic Control from ETH Zurich (2019) M.Sc. in Robotics, Systems and Control from ETH Zurich (2014) B.Eng. in Mechanical Engineering and B.Sc. in Physics from University of Melbourne (2008) Research Interests : Paul's research integrates control theory with educational innovation. He develops approximate dynamic programming algorithms for large-scale systems, particularly in building control and quadcopter coordination . His work also explores project-based learning pedagogies, leveraging hardware-accelerated computing and IoT technologies to enhance engineering education. Recent Publications emphasize interdisciplinary teaching methods , quadcopter control systems , and data-driven optimization for autonomous vehicles. His projects include 5G URLLC Factory of the Future (2022-2023), reflecting his commitment to bridging theoretical control systems with practical educational frameworks. Advising & Grants : Paul contributes to educational grant initiatives such as the 5G URLLC Factory of the Future research contract. He actively participates in curriculum development and pedagogic research , focusing on student engagement and competency-based learning in engineering.

• Artificial Intelligence
• Fuzzy Logic
• Robotics and Automation
• +7 more

Dr. Raheleh Jafari is a University Academic Fellow in Artificial Intelligence Technology in Fashion Design at the University of Leeds' School of Design. Her expertise spans artificial intelligence, fuzzy logic, robotics/automation, and fashion design. She holds a B.S. in Pure Mathematics (2008) from Islamic Azad University, an M.S. in Applied Mathematics (2010), and a Ph.D. in Automatic Control (2017) from the National Polytechnic Institute (Mexico). She completed a postdoctoral fellowship at the University of Agder, Norway (2017–2019). Her research focuses on AI-driven solutions for pipeline systems, medical imaging, and industrial automation. She has published over 70 peer-reviewed papers and authored a book on fuzzy logic systems (2019). She is an IEEE member, served on editorial boards, and organized conferences. Key projects include applying AI to social health bots (Norway RC grant) and developing intelligent techniques for fluid mechanics. Her work bridges engineering and design, with applications in sustainable systems, medical diagnostics, and fashion technology. Awards include a 2019 Travel Award from Electronics-MDPI Journal. She advises postgraduate researchers and collaborates on interdisciplinary innovations.

Doug TudhopeView profile

Professor

• Knowledge Organization Systems
• Semantic Technologies
• Information Retrieval
• +13 more

Doug Tudhope is a Professor at the University of South Wales, affiliated with the Faculty of Computing, Engineering and Science and the Computing, Cybersecurity, Mathematics and Informatics Research and Innovation Group. His work bridges computer science, information science, and digital heritage, focusing on knowledge organization and semantic technologies. BSc (Hons) in Computer Science, University of Edinburgh (1976) PhD in Computer Science, University of Wales, Swansea (1981) His primary research interests lie in Knowledge Organization Systems (KOS), including thesauri, ontologies, taxonomies, and classifications, and their application in semantically indexed hypermedia systems for improved information retrieval. He investigates how controlled vocabularies can provide lightweight semantics for online services and linked data, particularly in digital heritage and archaeology. Recent work explores KOS-based Named Entity Recognition and Natural Language Processing for semi-automatic indexing of archaeological datasets and reports. The recent publications demonstrate a strong trend toward applying semantic technologies and KOS to real-world challenges in archaeology and digital curation. His work emphasizes automatic indexing, vocabulary mapping, temporal data normalization, and improved search interfaces for complex cultural datasets. These efforts highlight interdisciplinary collaboration and practical implementations of semantic standards. He was Editor of The New Review of Hypermedia and Multimedia from 1997 to 2022 and contributed to the development of the ISO 25964 thesaurus standard as a member of the ISO TC46/SC9/SC8 working group. He has also co-organized the NKOS workshops and co-edited special journal issues in this domain. Doug Tudhope has supervised multiple research students, as indicated by his profile listing five supervised works. His research has been supported through projects associated with the Hypermedia Research Group, though specific grants are not detailed in the text. He has an extensive publication record of 116 research outputs, with continued active contributions into 2024. He is a key member of the Hypermedia Research Group, which focuses on semantic technologies, KOS, and their applications in digital heritage and information retrieval. The group has fostered collaborations in archaeology, library science, and multimedia systems, contributing to international standards and interdisciplinary research initiatives.

• Robot Control
• Robotic Manipulation
• Human-Robot Interaction
• +12 more

Yiannis Karayiannidis is an Associate Professor in the Department of Automatic Control at Lund University's Faculty of Engineering (LTH). He is affiliated with major research initiatives including ELLIIT (the Linköping-Lund initiative on IT and mobile communication) and WASP (Wallenberg AI, Autonomous Systems and Software Program). A portion of his research team is based at Chalmers University of Technology, specifically within the Division of Systems and Control (SYSCON). He actively contributes to the robotics and control community through editorial roles and leadership in professional organizations. His research focuses on advanced robotic control systems, particularly in human-centered environments. Key areas include robotic manipulation, dual-arm coordination, force and grasping control, physical human-robot interaction, robot learning, navigation, reactive planning, multi-agent systems, and nonlinear and adaptive control. These interests are reflected in both his teaching and research output. The recent publication trends highlight a strong focus on autonomous navigation in dynamic environments, robust force control, multi-agent coordination, and learning-based manipulation. His work integrates model-based control with data-driven methods, particularly in complex and uncertain settings. Topics such as obstacle avoidance, tunnel-following MPC, friction modeling, and semantic feature estimation demonstrate technical depth and real-world applicability. Prof. Karayiannidis holds significant academic service roles: Associate Editor, IEEE Robotics and Automation Letters Associate Editor, IEEE/ASME Transactions on Mechatronics Associate Editor, International Conference on Robotics and Automation (ICRA) Associate Editor, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Associate Editor, European Control Conference Treasurer, IEEE Robotics Chapter in Sweden He has supervised numerous PhD and master's students and is actively involved in research projects funded by national and strategic initiatives. His editorial and supervisory roles underscore his leadership in the robotics and control community. He also contributes to infrastructure development as a manager of RobotLab LTH. He is involved in several key research labs and teams: RobotLab LTH – a shared robotics research infrastructure where he serves as a manager Division of Systems and Control (SYSCON), Chalmers University of Technology – hosts part of his research team Center for Construction Robotics – collaborative network involving Lund University researchers WASP and ELLIIT research networks – strategic national platforms for AI and robotics

• Control Systems
• Robotics
• Estimation Algorithms
• +2 more

Abdelhamid Tayebi is a Professor in the Department of Electrical Engineering at Lakehead University, Canada, and holds a courtesy Professorship in the Department of Electrical and Computer Engineering at Western University, Canada. He is the Founder and Director of the Robotics and Automatic Control Laboratory. His research focuses on control systems and robotics, specifically the design of estimation and control algorithms. Affiliations: Lakehead University, Western University Roles: Professor, Laboratory Director Dr. Tayebi's research interests span control systems, robotics, and algorithmic advancements in estimation and control. His work contributes to both theoretical foundations and practical applications in these fields. Awards: Fellow of the Engineering Institute of Canada (EIC), IEEE Fellow He is actively involved in academic leadership and has established key research initiatives through his laboratory.

• Biomaterials Science
• Bioelectronics
• Neural Engineering
• +5 more

Dr Thomas Paterson is a Lecturer at the University of Sheffield's School of Clinical Dentistry, with affiliations to the Insigneo Institute and Neuroscience Institute ECR committee. His research integrates biomaterials science and bioelectronics to develop wearable/implantable devices for healthcare applications, including bruxism monitoring, neural implants, and thermal cooling systems for epilepsy. He leads projects such as MND Diagnostic Gloves and Bite Force Sensing using conductive electrospun membranes. Key academic contributions include work on electrospun scaffolds with antimicrobial properties, conductive hydrogels, and 3D-printed composite materials. His interdisciplinary approach spans dentistry, materials engineering, and automatic control systems engineering. Education & Career: Joined University of Sheffield in 2023; prior visiting roles in China and India. Research Themes: Bioelectronic sensors, neural stimulation implants, and biohybrid robotics. Awards/Grants: Not explicitly listed, but notable projects funded by interdisciplinary collaborations. Teaching: Leads modules on Dental Materials, Tissue Engineering, and Polymer Biomaterials for undergrad/master’s students. Labs/Teams: Active in the Smart Devices and Sensors theme at Insigneo Institute. His lab focuses on translating lab research into clinical applications, such as commercializing wearable devices for neurodegenerative disease monitoring and developing implantable hydrogels for nerve repair.

Dominik BaumannView profile

Assistant Professor

• Systems and Control Theory
• Machine Learning
• Communication Networks
• +5 more

Dominik Baumann is an Assistant Professor at Aalto University's Department of Electrical Engineering and Automation since 2023. His research focuses on systems and control theory, machine learning, and cyber-physical systems, with an emphasis on safety, optimization, and robotics applications. His work addresses challenges in reinforcement learning, distributed control, and safe exploration strategies. Notable contributions include methods for non-ergodic reward systems, lightweight safe learning algorithms, and scalable optimization for dynamical systems. He is affiliated with the Cyber-physical Systems research group at Aalto. Awards include the 2019 Future Award from the Ewald Marquardt Foundation and multiple conference best paper/demonstration awards. His publications span journals like IEEE Transactions on Automatic Control and venues such as the International Conference on Cyber-Physical Systems. Research themes include: Safe learning and control for robotics Optimization under computational/resource constraints Ergodicity principles in reinforcement learning Event-triggered communication strategies

• Systems Engineering
• Climate Physics
• Biological Signal Analysis
• +3 more

Javier de Pedro Carracedo is an Associate Professor at the Department of Automatic Control, Universidad de Alcalá. He is a member of the Climate Physics Group (CPG) and holds a PhD from Universidad Politécnica de Madrid (2020), focusing on dimensional analysis of biological signals' dynamics and complexity. His research integrates systems engineering, climate physics, and nonlinear dynamics. Education: Doctorado en Ingeniería de Sistemas, Universidad Politécnica de Madrid (2020) Research interests emphasize the application of dimensional analysis to complex biological systems and climate-related phenomena. His work bridges theoretical physics and engineering, exploring dynamical systems in both natural and artificial contexts. No scientific awards or funded grants are explicitly listed in the provided data. Advising activity or lab affiliations beyond the Climate Physics Group are unspecified.

• Control Systems
• Fuzzy Logic
• Sliding Mode Control
• +3 more

Драган С. Антић је редовни професор на Катедри за Аутоматику на Факултету за електронику у Нишу, Универзитета у Нишу, Србија. Изабран је у звање професора 2005. године након што је целокупно академско образовање стекао на истом факултету. Његово образовање укључује: Дипломирао у области Аутоматика (1987) Магистрирао у области Аутоматика (1991) Докторирао у области Аутоматика (1994) Професор Антић се бави истраживањима у области управљачких система са посебним акцентом на слайдинг мод контролу, фази логику, адаптивне контролере и примену неуралних мрежа. Његов рад обухвата дизајн филтера за смањење шума, моделовање динамичких система помоћу ортогоналних функција и решавање проблема у системима са не-минималном фазом. Посебно је истакао се у развоју контролних алгоритама за анти-лок кочионе системе и адаптивне PID контролере. Са 51 радом у часописима са импакт фактором, његови најновији радови фокусирају се на интеграцију ортогоналних ендокриних неуралних мрежа у управљачке системе, што је довело до побољшаних решења у аутомобилској и индустријској аутоматизацији. Његове публикације објављене су у водећим часописима као што су IEEE/ASME Transactions on Mechatronics и Neural Networks. Ниједна специфична научна награда није наведена у пруженим текстовима. Тренутно је активан у истраживачким пројектима, учествујући у 2 национална и 8 интернационалних пројеката. Његов рад на овим пројектима наставља да развија теоријске основе и практичне примене управљачких система, посебно у домену неуралних мрежа и адаптивних техника.

Giovanni BerselliView profile

Professor

• Robotics
• Mechanical Engineering Design
• Automation
• +3 more

Giovanni Berselli is a Full Professor at the Department of Mechanical, Energy, Management and Transport Engineering (DIME), University of Genoa. He coordinates the PhD program in Mechanical, Energy, and Management Engineering and serves on the Department Board. His teaching focuses on mechanical design, robotics, and technical drawing, including courses such as MACHINE DESIGN and DESIGN OF AUTOMATIC MACHINERY AND ROBOTS. His research emphasizes advanced robotics and mechanical systems, particularly in cable-driven hyper-redundant manipulators, medical robotics, and trauma simulation devices. He has contributed to projects like robotic head prototypes for surgical training and wrist rehabilitation systems. His work bridges mechanical engineering with biomedical applications. Berselli’s publications span 2024–2025, addressing topics from device design to control systems in rehabilitation robotics. He actively engages in academic service roles, including PhD program coordination and departmental governance. His work reflects a commitment to both theoretical and applied engineering solutions.