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Qi ZhengView profile

Professor

• Mathematical Modeling of Biological Processes
• Applied Stochastic Processes
• Application of Computer Algebra
• +1 more

Qi Zheng is a Professor at Texas A&M University's Department of Epidemiology & Biostatistics, with research interests in Mathematical Modeling of Biological Processes, Applied Stochastic Processes, Application of Computer Algebra, and Estimation of Microbial Mutation Rates. He holds a PhD in Statistics (1993) and a BA in Mathematics (1982) from Zhejiang University. Education: PhD in Statistics from Texas A&M University (1993), BA in Mathematics from Zhejiang University (1982) Research Interests: Mathematical Modeling of Biological Processes, Applied Stochastic Processes, Application of Computer Algebra, Estimation of Microbial Mutation Rates Teaching Interests: Biostatistics, Categorical and Longitudinal Data Analysis, Statistical Computing Contact: qzheng@tamu.edu | Phone: 979.436.9398 Recent publications focus on swarm robotics, mixed-reality interfaces, and reconfigurable robotic mechanisms. Key themes include entropy-based consensus algorithms for artificial swarms, adaptable sensorimotor systems for human-swarm interaction, and innovative designs for multiterrain locomotion and robotic grasping. These works bridge theoretical stochastic modeling with practical applications in robotics and computational systems.

Xiaolin HuView profile

Professor

• Modeling and Simulation
• Complex Systems Science
• Agent-Based Systems
• +3 more

Xiaolin Hu is a Professor in the Department of Computer Science at Georgia State University within the College of Arts & Sciences. His research focuses on modeling and simulation theory with applications in complex systems science, agent-based systems, and advanced computing environments. Ph.D. in Electrical and Computer Engineering, University of Arizona (2004) NSF CAREER Award recipient Senior member of IEEE and Society for Modeling and Simulation International (SCS) Associate editor for ACM Transactions on Modeling and Computer Simulation (TOMACS) and other journals SIMULATION: Transactions journal and International Journal of Modeling, Simulation, and Scientific Computing (IJMSSC) Dr. Hu's research spans three major areas: Dynamic Data-Driven Simulation (DDDS): Development of simulation frameworks that assimilate real-time data, particularly applied to wildfire spread prediction and autonomous systems. Multi-Agent Systems: Study of adaptive behaviors and coordination mechanisms for unmanned aircraft and social/public health systems. Advanced Computing: Implementation of parallel and cloud computing solutions for large-scale simulations. His recent publications (2025-2023) demonstrate a strong focus on integrating real-time data from UAVs and satellite systems into wildfire simulations, utilizing Bayesian methods for sequential data assimilation, and developing cloud-based simulation services. These works bridge computational modeling with environmental science applications. Scientific recognitions include: National Science Foundation (NSF) CAREER Award Dr. Hu has chaired multiple international conferences in modeling and simulation and leads the SIMS Lab at Georgia State University, which specializes in simulation technologies and their applications in diverse domains.

• Mobile Communications
• Radio Frequency Radiation Safety
• Biometric Radio Systems
• +3 more

Dr Robert Edwards is a Reader in Mobile Communications and Director of the 5G Research Centre at Loughborough University. Formerly Director of Sheffield's Centre for Mobile Communications Research, he holds Senior Member status in IEEE and is a Chartered Engineer with the IET. His research focuses on biometric radio systems, mobile communications advancements, and the health implications of radio frequency radiation exposure. Education : BEng (Hons) in Electronic Engineering (Communications), University of Sheffield PhD in Communications & Radar Engineering from Sheffield University Research Interests : Developing biometric authentication through radio channel characteristics Antenna design for on-body and industrial applications IoT-based flood monitoring systems in developing regions RF safety assessment and mitigation strategies Key Activities : External Examiner for multiple institutions including American College of Thessaloniki and Arab Open University Member of Wireless World Research Forum's Communications Division Subject advisor for British University in Egypt (Communications Electronics) Labs/Teams : Leads the Loughborough 5G Research Centre and collaborates with the Antenna Team (as noted in his 2013 publications).

• Rail Transportation
• Control Systems
• Machine Learning
• +5 more

Bilal Abduraxman is a Researcher at Loughborough University, affiliated with the Control Systems Group. He holds a BEng, MSc in Advanced Systems and Control Engineering (University of Manchester, 2013), and a PhD in Aerospace Engineering (Cranfield University, 2018). Prior to joining Loughborough in 2020, he worked as a post-doctoral researcher at The University of Sheffield. His research focuses on rail transportation systems, including wheel-rail dynamics, machine learning applications for friction estimation, electrification strategies for energy efficiency, and underwater vehicle control systems. He also investigates pantograph-catenary systems and sustainable energy solutions in transportation. Publications highlight advancements in neural network-based friction coefficient estimation, optimal intermittent electrification models, and guidance algorithms for autonomous underwater vehicles. His work integrates experimental methods, high-fidelity simulations, and sensor technology to enhance rail safety and reduce environmental impact. Bilal contributes to the development of on-train low adhesion detection systems and has explored CO 2 emission reduction through electrification innovation. His interdisciplinary approach bridges mechanical engineering, control systems, and robotics.

Seongim ChoiView profile

Assistant Professor

• Computational Design Optimization
• CFD (Computational Fluid Dynamics)
• Multidisciplinary Analysis and Design Optimization (MADO)
• +5 more

Seongim Choi is an Assistant Professor in the Kevin T. Crofton Department of Aerospace and Ocean Engineering at Virginia Tech and an Adjunct Professor at KAIST's Graduate School of Transportation. His research focuses on computational design optimization, advanced CFD methods, and multidisciplinary analysis for aerospace systems. He holds a Ph.D. from Stanford University (2006) and degrees from Seoul National University (B.S. 1997, M.S. 1999). His expertise includes unsteady flow analysis, fluid-structure interaction, and rotorcraft design. Notable awards include the Young Investigator Award from the Asian/Australian Rotorcraft Forum (2012) and Best Paper Awards from AIAA conferences (2004). Professional roles span NASA Ames, the U.S. Army Aeroflightdynamics Directorate, and KAIST. Research interests emphasize adjoint-based sensitivity analysis, time-spectral methods for CFD, and machine learning integration in design optimization. Current work addresses low-boom supersonic jets, helicopter rotors, and autonomous UAV systems. His affiliations include the Virginia Tech College of Engineering and collaborations with KAIST's aerospace programs.

• Digital Health
• Wearable Computing
• Data Science
• +3 more

Dr. Ian Cleland serves as Research Director at the School of Computing, Ulster University. He holds a B.Sc. in Biomedical Engineering and a Ph.D. in Computer Science from Ulster University. His research focuses on digital health solutions combining wearable/pervasive computing with AI/data science to enable personalized healthcare. Key areas include sensor-based activity recognition, synthetic data generation, and technology-enabled care for patients with conditions like Parkinson’s and dementia. Education: B.Sc. Biomedical Engineering, Ulster University Ph.D. Computer Science, Ulster University Research Highlights: Over 100 peer-reviewed publications in health informatics Secured £20M+ in research funding (e.g., CHIC Phase 2: £3.36M, ARC: £3.13M) Co-Chair of UCAmI2024 and Vice Chair of Alzheimer’s Association Technology & Dementia Committee His work emphasizes ethical technology adoption, with projects like the iMPAKT mobile app and thermal imaging solutions for diabetic foot monitoring. He leads the Human-Computer Interaction group within the Pervasive Computing Research Centre and the Human Health and Activity Lab (H2Al).

Mircea NicolescuView profile

Professor

• Computer Vision
• Surveillance Systems
• Robotic Vision
• +3 more

Mircea Nicolescu is a Professor in the Department of Computer Science and Engineering at the University of Nevada, Reno. He holds a Ph.D. (2003) and M.S. (1999) from the University of Southern California, and a B.S. (1995) from Polytechnic University Bucharest. He co-directs the Computer Vision Laboratory . His research focuses on computer vision , particularly in video content understanding , surveillance systems , robotic vision , and human-computer interaction . Key areas include robust tracking in dynamic scenes, autonomous navigation, and gesture/face recognition. Recent work addresses maritime safety, cryptocurrency forecasting, and robotic task parameter estimation via multimodal data fusion. He has published over 100 peer-reviewed articles and holds a U.S. patent for 'Fast Digital Pan-Tilt-Zoom Video'. His work has earned a Best Paper Award Finalist distinction (2021). Teaching responsibilities include Programming Languages and Advanced Computer Vision courses. Collaborative projects involve multi-agent systems, intent recognition, and spiking neural networks for pattern analysis.

Narada Dilp WarakagodaView profile

Associate Professor

• Artificial Intelligence
• Autonomous Systems
• Computer Vision
• +3 more

Narada Dilp Warakagoda is an Associate Professor at the University of Oslo, affiliated with the Section for Autonomous Systems and Sensor Technologies. His research focuses on Artificial Intelligence, Autonomous Systems, Computer Vision, Robotics, Machine Learning, and Deep Learning, with notable contributions to underwater acoustics, renewable energy forecasting, and unmanned vehicle control systems. He collaborates extensively with researchers across disciplines to advance applications in environmental monitoring, energy systems, and autonomous technologies. His work integrates advanced machine learning techniques with domain-specific challenges, such as synthetic aperture sonar analysis, spatio-temporal wind forecasting, and reinforcement learning for autonomous navigation. He has published in leading journals and conferences, addressing topics like probabilistic solar irradiance prediction, graph-based wind energy modeling, and deep learning for seabed munitions detection. Warakagoda’s research bridges theoretical advancements with practical implementations, emphasizing applications in robotics, environmental science, and defense technologies. His projects often involve interdisciplinary teams, reflecting his commitment to solving real-world problems through innovative AI-driven solutions.

Senem VelipasalarView profile

Professor

• Machine Learning
• Computer Vision
• Wireless Smart Camera Networks
• +8 more

Senem Velipasalar is a Professor in the Department of Electrical Engineering and Computer Science (EECS) at Syracuse University, affiliated with the Smart Vision Systems Laboratory and the Aging Studies Institute. She holds a Ph.D. and M.A. from Princeton University, an M.S. from Brown University, and a B.S. from Bogazici University. Her research focuses on machine learning, computer vision, and wireless smart camera systems, with applications in human activity classification, driver behavior analysis, and defense against adversarial attacks. Her honors include the NSF CAREER Award (2011), 2021 IEEE Technological Innovation Award, and multiple doctoral prizes for her advisees. She leads grants totaling over $4M, including ARPA-E projects on occupancy detection and DOE-funded research on aerial energy modeling. Research interests span embedded vision, distributed multi-camera tracking, and energy-efficient algorithms. Her lab develops technologies like wearable camera-based fall detection and autonomous UAV navigation. Notable publications include works on adversarial attacks, fNIRS brain activity analysis, and thermal pedestrian detection.

Philipp BraunView profile

Senior Lecturer

• Control Theory
• Dynamical Systems
• Optimization
• +3 more

Dr. Philipp Braun is a Senior Lecturer in the School of Engineering at The Australian National University (ANU), Canberra. He holds a Diploma in Mathematics from Technical University Kaiserslautern (2012) and a Ph.D. in Mathematics from the University of Bayreuth (2016). Prior to ANU, he served as an Assistant Professor at the University of Bayreuth (2016–2018) and a Senior Research Associate at the University of Newcastle, Australia (2016–2020). His research focuses on applied dynamical systems and control theory , including nonsmooth control Lyapunov functions, numerical construction of control Lyapunov functions, obstacle avoidance, distributed optimization, and smart grid applications. Recent projects include work on hybrid systems, pursuit-evasion algorithms, and sensor-based navigation for robots. Dr. Braun has contributed to over 20 peer-reviewed articles and led projects such as Control at What Cost? One-Shot Real-Time Dual Inverse Optimal Control (2025–2027) and Solution Concepts and Performance Guarantees in Partial Information Multi-Player Games (2024–2027). His work bridges theoretical advancements with practical applications in robotics, energy systems, and environmental modeling. Key awards and recognitions are not explicitly listed, but his extensive publication record reflects significant contributions to control theory and robotics. Supervision of research students is ongoing, though specific advisee names are not documented in the provided texts.

Andreas NüchterView profile

Professor

• Robotics
• Computer Vision
• Sensor Fusion
• +5 more

Andreas Nüchter is a Professor and Chair of Robotics at Julius-Maximilians-University Würzburg (Germany), leading the Chair of Computer Science XVII. He holds additional roles including Visiting Chair at ENSTA - Institut Polytechnique de Paris, Dean of Studies at the Institute of Computer Science, and Vice President of Zentrum für Telematik e.V. His research focuses on robotics, 3D reconstruction, SLAM, and sensor systems for autonomous systems. He has authored influential papers in IEEE Transactions on Robotics, Acta Astronautica, and robotics conferences like ICRA and IROS. Education: Not explicitly detailed in text, but inferred through academic roles. Research Interests: Robotics, computer vision, sensor fusion, autonomous systems, 3D reconstruction, and space robotics applications. His work emphasizes real-time systems, planetary exploration, and open-source software frameworks like SceneFactory and libBICOS. Recent projects include CNN-based spacecraft pose estimation, spherical mobile mapping systems, and radar SLAM (RIV-SLAM). Advising & Grants: Mentors a team including MSc/BSc students (e.g., Luca Anteunis, Fabian Arzberger). Involved in grants related to robotics, mining automation (AMADEE-24), and space exploration. Collaborates with institutions like NASA (CADRE lunar rovers) and Fraunhofer IPM. Labs/Teams: Leads the Robotics Lab at JMU, develops spherical robots for planetary missions, and maintains open-source libraries (libBICOS, SceneFactory). Active in projects like AMADEE-24 Mars simulation for human-robot interaction.

• Medical Image Analysis
• Distributed Systems
• Acoustic Location
• +2 more

Kuo-Ming Chao is a Researcher at the Centre for Research in Arts and Creative Exchange within the School of Arts, Humanities, and Social Sciences. His work bridges computational methods and applied research, with focus areas spanning medical imaging systems, distributed computing architectures, acoustic positioning technologies, social network analysis, and multimodal misinformation detection. Chao maintains active involvement in the academic community through sustained editorial contributions and conference participation. Research Focus: His interdisciplinary research integrates computer science with domain-specific applications. Key themes include: Development of orchestrated workflows for medical image analysis systems Multimodal fusion techniques for information verification Acoustic signal processing for location tracking Graph-based algorithms for social network prediction Professional Activities: Peer reviewer for Service-Oriented Computing and Applications journal since 2006 Invited keynote speaker for the 2025 IEEE Conference on Artificial Intelligence

Hugues MOUNIERView profile

Professor

• Control Theory
• Differential Flatness
• Controllability Analysis
• +5 more

Professor Hugues MOUNIER is affiliated with Paris Saclay University and the Laboratoire des Signaux et Systèmes (L2S) at CentraleSupélec. His primary role is as a Professor leading the COMEDY team, focusing on control systems and their applications. He has been a permanent member of L2S since 2010 and joined Paris Saclay University in 2008. His research spans theoretical and applied domains: differential flatness (for nonlinear and infinite-dimensional systems), Liouvillian systems, controllability/observability properties, and applications in contemplative neuroscience, physiological systems, and engineering systems like drilling, automotive, and network control. He leads the ANR project MindMadeClear, integrating mathematical models for meditation practices with physiological and phenomenological analysis. Key contributions include modeling oilwell drilling vibrations, model-free control strategies for vehicles and data centers, and neuroscientific studies using EEG classification for meditation states. His work bridges abstract theory (e.g., flatness analysis for HPA axes) with real-world applications (e.g., congestion control, energy management). He collaborates internationally, presenting at venues like ECC, IFAC, and IEEE conferences. His lab teams include SYCOMORE and MODESTY, focusing on dynamical systems modeling and estimation. No awards are explicitly listed, but his extensive peer-reviewed publications reflect sustained academic impact.

Hasan KivrakView profile

Assistant Professor

• Cyber-Physical Systems
• Autonomous Robots
• Indoor Wireless Positioning
• +3 more

Dr. Hasan Kivrak is an Assistant Professor in the Department of Computer and Information Science at Northumbria University, UK, since 2023. He holds a B.Sc. in Computer Engineering from Selcuk University, Turkey, and M.Sc. and Ph.D. degrees from Istanbul Technical University. Before joining Northumbria, he served as a Research Associate at the University of Manchester's Department of Electrical and Electronic Engineering (2021–2023). His research focuses on cyber-physical systems, autonomous robotics for extreme environments, and indoor wireless positioning. Key areas include developing socially-aware robots, digital twin approaches for industrial inspection, and navigation frameworks for human-robot interaction. His work addresses challenges in nuclear environments, assistive robotics, and 3D environmental modeling. Dr. Kivrak’s interdisciplinary projects bridge robotics, AI, and wireless networks. Notable contributions include the Cyber-WISE positioning system, symbiotic autonomous ecosystems for nuclear applications, and adaptive social navigation models. His research emphasizes practical solutions for industrial automation, human-robot collaboration, and extreme environment robotics. He currently resides at Northumbria University’s Ellison Building, Room ELB120, contributing to academic and applied research in computer science and robotics.

John EconomouView profile

Professor

• Defence Sensors
• Gun Technologies
• Robotics and Autonomous Systems
• +4 more

Professor John Economou is Professor of Defence Robotics and Autonomous Systems and Deputy Director of Consultancy at Cranfield University's Centre for Defence Engineering and Physical Science. He holds a BEng from University of Wales, MSc from University of Sheffield, and PhD from Cranfield University. His research focuses on uncrewed vehicle systems, control methods, and autonomous technologies for defence applications. Research areas include autonomous systems control, fuzzy logic systems, inertial sensing, and energy-based path planning. He leads the Robotics and Autonomous Systems and Human Machine Teaming (RAS-HMT) campaign and directs the Aerosystems MSc program. Recent publications focus on vehicle control systems, sensor fusion algorithms, and autonomous navigation. His research receives funding from UK Ministry of Defence, US Department of Defense, and defence industry partners including BAE Systems and QinetiQ.