Find Academic Supervisors

• Optical Sensors
• Micro-Electro-Mechanical Systems (MEMS)
• Fluid Mechanics
• +4 more

Volkan Otugen is a Professor in the Department of Mechanical Engineering at the University of South Florida (USF), College of Engineering, where he serves as founding director of the Optical Sensors Laboratory. Holding a Ph.D. in Mechanical Engineering from Stanford University, his career spans advanced optical sensor development for aerospace and fluid mechanics applications. His research focuses on: Micro-optical sensors using whispering gallery mode (WGM) resonators Wall shear stress, pressure, acceleration, and electromagnetic field detection MEMS-based instrumentation for extreme environments Structural health monitoring systems Smart materials integration Aerospace fluid dynamics diagnostics Recent publications (2024-2014) demonstrate sustained innovation in WGM resonator applications, particularly for high-speed transient sensing and aerospace instrumentation like EDL air-speed sensors and cryogenic seismometers. This work bridges photonics, fluid dynamics, and MEMS engineering with emphasis on resolution, data rate, and environmental robustness. Scientific recognition includes: ASME Fellow designation Otugen has secured major research funding and mentored graduate students through projects with NASA and the National Science Foundation: Advising: Extensive mentorship of PhD/Master's candidates in optical sensor development Grants: NASA for atmospheric sensors, NSF for SGER projects on wall shear stress sensors The Optical Sensors Laboratory at USF specializes in designing and testing photonic sensors for propulsion systems, structural monitoring, and space exploration missions.

• Mechanical Engineering
• Automotive Engineering
• Mechatronics
• +9 more

Andrea Tonoli is a Full Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) at Polytechnic University of Turin. He serves as Scientific Advisor for partnerships with DAYCO, ITALDESIGN GIUGIARO, and STELLANTIS, and leads Spoke 2 'Sustainable Road Vehicle' at the National Center for Sustainable Mobility (MOST). He coordinates the DIMEAS-LIM research group and participates in CARS and PEIC interdepartmental centers. His teaching includes courses on Car Body Design, Motor Vehicle Design, and Mechatronic Systems Simulation. His research focuses on electric/hybrid powertrain optimization, mechanical design of electric traction machines, energy management in autonomous vehicles, longitudinal/lateral dynamics, virtual sensors for vehicle state estimation, electro-hydraulic/electromechanical shock absorbers, and magnetic bearings. Key subfields include rotordynamic analysis, harmonic finite element modeling for turbines, maglev stability, mechatronic systems for autonomous vehicles, and sustainable transportation. Recent publications emphasize electrodynamic maglev damping, compact assistive knee prostheses, electromagnetic shock absorber testing, and multi-objective optimization of regenerative suspensions. His work spans automotive, aerospace, and biomedical domains with applications to energy recovery, vibration control, and sustainable mobility. He supervises PhD students in mechatronics and automotive engineering, and leads numerous funded research projects including SPHERE (PNRR), MINERVA (PNRR), SmartCorners (EU), and industry collaborations with Hyperloop Transportation Technologies, Dayco Europe, and Racing Force Spa.

Tony SzturmView profile

Professor

• Technology-assisted rehabilitation
• Telerehabilitation
• Game-based rehabilitation
• +7 more

Tony Szturm is a Professor and Senior Scholar in the Department of Physical Therapy at the College of Rehabilitation Sciences, University of Manitoba. His work bridges clinical rehabilitation and engineering innovation, focusing on technology-assisted and game-based therapeutic interventions delivered through telerehabilitation platforms. Institution: University of Manitoba School: College of Rehabilitation Sciences Department: Department of Physical Therapy Location: Bannatyne Campus, Winnipeg, MB Dr. Szturm holds a BSc in Biology and a BSc in Physical Therapy from the University of Western Ontario, and a PhD in Neurophysiology from the University of Manitoba. His research is deeply interdisciplinary, integrating wireless sensors, digital media, and interactive systems to support rehabilitation in both clinical and home environments. His primary research interests include technology-assisted rehabilitation , telerehabilitation , game-based motor training , and neurological recovery across diverse populations such as stroke survivors, children with neurodevelopmental disabilities, individuals with traumatic brain injuries, Parkinson’s patients, and aging adults. A key focus is enhancing accessibility, accountability, and engagement in therapy through innovative, low-cost digital tools. The 15 most recent inferred articles reflect a strong trend toward digital health innovation , remote monitoring , and interdisciplinary rehabilitation engineering . These works span areas such as upper limb recovery, balance and gait training, dual-task performance, vestibular rehabilitation, and patient engagement. The integration of wearable sensors, real-time feedback, and gamification principles is a consistent theme, demonstrating his commitment to translating research into practical, scalable solutions. Dr. Szturm is actively involved in mentoring, supervising postdoctoral fellows, PhD, and master's students through the Mentoring of Highly Qualified Personnel (HQP) Program, fostering collaboration between rehabilitation sciences and engineering disciplines. While no formal scientific awards are listed, his leadership in high-impact, publicly featured research projects underscores his contribution to the field. His lab and research group focus on developing and evaluating plug-and-play rehabilitation technologies that can be deployed in resource-limited settings, including international applications such as projects in India. These initiatives emphasize affordability, usability, and clinical effectiveness, aiming to expand access to high-quality rehabilitation globally.

• Computer Vision
• Image Processing
• Photometric Stereo
• +12 more

Vasileios Argyriou is an academic researcher affiliated with Kingston University, with extensive contributions in computer vision, image processing, and AI applications in IoT, healthcare, and smart agriculture. His work spans photometric stereo, motion estimation, federated learning, and UAV-based remote sensing. Research Interests: His research focuses on developing advanced computer vision techniques including photometric stereo for 3D reconstruction, deep learning for anomaly detection, federated learning for privacy-preserving AI, and AI-driven solutions for smart farming and healthcare. He explores motion estimation, facial recognition, and synthetic data generation for training robust models. The recent publications (2024–2025) highlight a strong trend toward applying machine learning in real-world systems—particularly federated learning for intrusion detection, UAV-based agricultural monitoring, 5G security, and medical imaging. His work integrates computer vision with IoT, wireless communications, and edge computing, demonstrating interdisciplinary innovation. Scientific Contributions: Author of a book on image and video registration with quality metrics. Extensive publication record in top journals including IEEE Transactions, Sensors, and Pattern Recognition. Pioneering work in photometric stereo, motion estimation using phase correlation, and GAN-based face reenactment. He has advised or collaborated with numerous researchers across fields, though specific student names are not listed. His work often involves large-scale data analysis, simulation frameworks, and real-time systems. He is involved in projects related to smart cities, precision agriculture, and autonomous systems. Laboratories and Teams: His collaborations suggest involvement with research groups focused on intelligent systems, computer vision, and IoT at Kingston University and beyond, particularly with Panagiotis Sarigiannidis, Thomas Lagkas, and others in networking and AI.

Jürgen BechtloffView profile

Professor

• Mechatronics
• Automation Technology
• Digital Production
• +3 more

Prof. Dr.-Ing. Jürgen Bechtloff serves as Professor of Measurement, Control and Regulation Technology at the South Westphalia University of Applied Sciences since 1998. He has held significant administrative roles including Founding Dean of Mechanical and Industrial Economics (2002-2004), Dean of Engineering and Economics (2004-2012), and Head of Scientific Center for Dual Studies and Continuing Education (2012-2019). His academic career spans industrial experience at Klöckner-Moeller GmbH (1992-1998) and academic research at TU Braunschweig (1987-1992). Education: Diplom from TU Braunschweig (1987), Dr.-Ing. from TU Braunschweig (1992) Laboratory: Operates the TransferFactory Industry 4.0 demonstrator since 2013 Research Focus: Industrial automation systems, particularly in Industry 4.0 implementation, Digital Production methodologies, and Mechatronic Systems simulation. His work emphasizes practical solutions for real-world challenges in: IoT gateway and platform integration Feasibility studies and implementation support Control engineering and measurement technology Electronics cam systems for motion control Robotic programming and interpolation methods Publication Trends: 15 most recent publications (2000-2020) demonstrate consistent focus on Industry 4.0 implementation, Mechatronics , and Digital Production technologies. His work bridges theoretical concepts with practical applications through case studies and demonstrator projects like the TransferFactory system. Teaching Contributions: Coordinates courses in Mechatronic Systems and Simulation and Digital Production for both bachelor and master programs, with emphasis on project-oriented learning and practical implementation of automation concepts using modern tools like MATLAB/Simulink. Technology Transfer: Provides services in measurement technology (data processing/visualization), control engineering (simulation and implementation), and mechatronics (3D motion design, kinematic analysis). Operates with state-of-the-art equipment including Beckhoff TwinCAT, Siemens S7/TIA systems, ABB/Kuka robots, and MES platforms.

• Digital Photogrammetry
• Computer Vision
• Geospatial Imaging
• +10 more

Dr. Jackson David Cothren is a Professor in the Department of Geosciences at the University of Arkansas, where he also serves as the Leica Geosystems Chair in Geospatial Imaging. He holds dual leadership roles as Director of the Center for Advanced Spatial Technologies (CAST) and the Arkansas High Performance Computing Center (HPCC). His academic affiliations are deeply rooted in geospatial science, computer vision, and high-performance computing, bridging engineering and environmental applications. Ph.D. in Geodetic Science and Surveying, The Ohio State University M.S. in Geodetic Science and Surveying, The Ohio State University B.S. in Applied Mathematics, United States Air Force Academy Dr. Cothren's research spans digital photogrammetry, computer vision, UAV-based geospatial monitoring, and spatial archaeometry. He investigates non-traditional sensor modeling, feature extraction, surface generation, and integration with enterprise geospatial systems. His work increasingly incorporates deep learning, transformer models, and AI-driven analytics for applications in renewable energy, autonomous systems, and environmental sustainability. His recent publications highlight innovations in solar PV profiling, aerial image segmentation, and fairness-aware domain adaptation. The trends in his recent scholarly output reflect a strong shift toward machine learning and AI in geospatial analysis, particularly using transformer architectures for high-resolution imaging and cross-domain adaptation. His work integrates Lidar, GPS, and InSAR for deformation monitoring and leverages HPC for large-scale data processing. Applications span archaeology, agriculture, transportation, and energy infrastructure. Dr. Cothren has received numerous competitive grants from NSF, NEH, and USDA, supporting interdisciplinary research in geospatial analytics, smart transportation, and cultural heritage. His projects emphasize data-driven decision-making, community engagement, and workforce development in geospatial technologies. Principal Investigator, NSF E-RISE Rll: Arkansas Smart Transportation Research Incubator (2025–2029) Lead, RII Track-1: DART – Data Analytics that are Robust and Trusted (NSF, 2020–2025) Director, OPEN-GATE: Expanding Geospatial Education (NSF, 2016–2020) He mentors a broad interdisciplinary team and leads collaborative research initiatives involving computer vision, environmental science, and archaeology. His labs and research centers—CAST and HPCC—serve as hubs for innovation in spatial technologies, high-performance computing, and data-intensive research across the university and beyond. These centers support large-scale projects in archaeo-geophysics, UAV monitoring, and enterprise GIS integration.

Qingping YangView profile

Associate Professor

• Measurement Systems
• Quality Engineering
• Smart Technologies
• +5 more

Dr. Qingping Yang is a Reader (Associate Professor) in the Department of Mechanical and Aerospace Engineering at Brunel University London, affiliated with the College of Engineering, Design and Physical Sciences. He directs the Brunel Quality Engineering and Smart Technology (QUEST) and Robotics and Automation Research Groups, focusing on sensor systems, AI, and industrial metrology. Education: PhD in Engineering, Brunel University London (1992) BEng in Instrumentation and Measurement Technology, Chengdu Aeronautical Polytechnic (1983) Research Interests: Dr. Yang integrates measurement systems, quality engineering, and smart technologies (AI/robotics). His work spans industrial metrology, IoT-driven manufacturing optimization, renewable energy forecasting, medical diagnostics, and autonomous inspection systems. Key methodologies include machine learning, Bayesian risk modeling, and non-destructive evaluation. Publication Trends: Recent articles emphasize AI applications in manufacturing (defect detection, robotic path planning), IoT-based monitoring (3D printing, building safety), and healthcare analytics (COVID-19 diagnosis). Methodological innovations include graph theory optimization, computer vision, and ontology-driven quality frameworks. Awards: Three Brunel University Performance Bonuses Marquis Who's Who in the World (1998) Marquis Who's Who in Science and Engineering (2000) Advising & Grants: Supervised 39+ PhD/MPhil students (23 as primary supervisor). Secured £2.7M as PI and £1.2M as Co-I across 18 projects (EU/UK industry/government-funded). Current PhD projects include AI for non-destructive testing and sustainable manufacturing. Leadership: Heads QUEST and Robotics research groups. Former EU research coordinator and MSc program director. Editor-in-Chief of the International Journal of Metrology and Quality Engineering .

• Computational Neuroscience
• Robotics
• Machine Learning
• +3 more

Florentin Wörgötter is a faculty member at the Department for Computational Neuroscience , Georg August University of Göttingen, Germany. His research bridges robotics , computational neuroscience , and machine learning , focusing on action prediction, neural networks, and human-robot interaction. Key Research Areas : Action segmentation, semantic decomposition of manipulation sequences, 3D object reconstruction, and sensor fusion for infant movement classification. Recent Trends : Combining task-dependent learning with optimal path search, using foundation models for graph-based action recognition, and improving CNN interpretability through influence functions. He collaborates extensively with researchers like Minija Tamosiunaite , Tomas Kulvicius , and Poramate Manoonpong , contributing to journals such as NeuroImage , Robotics and Autonomous Systems , and IEEE Transactions on Neural Networks . His work often integrates deep learning , semantic reasoning , and biologically inspired models for robotic applications.

Chao ZhangView profile

Associate Professor

• Dielectrics
• Electrochemistry
• Electrolyte materials
• +3 more

Chao Zhang is an Associate Professor at the Department of Chemistry-Ångström Laboratory, Uppsala University, specializing in computational electrochemistry and multi-scale modeling of electrolyte materials. His research bridges atomistic simulations with machine learning approaches to address challenges in energy storage and conversion systems. Education: Dr. rer. nat. from RWTH Aachen University (2013); Docent from Uppsala University (2020) Appointments: Postdoctoral researcher at the University of Cambridge (prior to joining Uppsala in 2017) His group develops finite-field methods for computational electrochemistry and investigates electrified solid-liquid interfaces. Recent research trends include neural rendering for underwater SLAM systems (2025), robust path-following control in marine robotics, and event-based localization in LiDAR-integrated environments. Scientific Awards: ERC Starting Grant (2020) Junior Research Fellowship, Wolfson College (2015) Jülich Excellence Prize for Young Scientists (2013)

• Marine Engineering
• Digital Twins
• Co-simulation Systems
• +3 more

Yingguang Chu is an Associate Professor at the Institute of Mechanical and Electrical Engineering, University of Southern Denmark, specializing in Mechatronics. His research focuses on co-simulation systems, digital twins, and marine engineering applications. Research Interests : Digital twin technologies, co-simulation frameworks, marine crane systems, hydraulics, and control algorithms. Projects : Active participant in the ShippingLab II project (2024-2027) on digital twins and human factors in vessel performance. Research Output Trends : Recent work emphasizes physics-inspired neural networks for mobile machinery dynamics, environmental load sensitivity analysis, and Vico-based co-simulation systems for marine operations. Publications frequently address crane path planning, digital twin implementation, and dynamic response optimization. Scientific Awards : IEEE Robotics and Automation Magazine Best Paper Award (2024) Teaching Responsibilities : Supervises master's theses on topics like CFD simulations, membrane valve systems, and fluid mechanics, while teaching mobile hydraulics courses.

• Signal Processing
• Communications Engineering
• Radar Signal Processing
• +7 more

Stefan Hägele is a researcher at the Chair of Media Technology, Technical University of Munich, affiliated with the Munich Institute of Robotics and Machine Intelligence (MIRMI). He completed his B.Sc. and M.Sc. in Electrical and Computer Engineering at TUM, graduating with distinction in 2022. B.Sc. in Electrical and Computer Engineering, TUM (2019) M.Sc. in Electrical and Computer Engineering, TUM (2022) His research focuses on signal processing applications in communications, radar, and image processing, combined with applied machine learning. Key areas include mmWave radar analysis, WiFi-based indoor positioning, privacy-preserving rehabilitation systems, and complex-valued neural networks. Recent publications highlight his work in radar-based object classification (using MIMO architectures), material recognition (SMCNet), visible light positioning (VLP-KAN), and skeleton estimation for rehabilitation (PoinTS). His contributions also appear in projects like 6G-Life, DFG Teleoperation over 5G, and CeTI (Tactile Internet).

• Radar engineering and signal processing
• Cloud and precipitation microphysics and dynamics
• Boundary-layer turbulence
• +3 more

Dr. Pavlos Kollias is a Professor at Stony Brook University’s School of Marine and Atmospheric Sciences and holds a joint appointment as Atmospheric Scientist in the Environmental Science and Technologies Department at Brookhaven National Laboratory. He also serves as International Faculty at the University of Cologne and Adjunct Professor at McGill University. Education Ph.D. in Meteorology, University of Miami, 2000 M.S. in Atmospheric Science, University of Athens, Greece, 1996 B.S. in Physics, University of Athens, Greece, 1994 Research Interests Kollias’s research integrates radar engineering, signal processing, and smart-sensor development to advance understanding of cloud and precipitation microphysics, boundary-layer turbulence, and satellite remote sensing . His work spans the design of novel phased-array and space-borne radars, fusion of multi-sensor observations, and agile adaptive observing strategies for weather and climate science. Key thrusts include: Development and deployment of ground-based and airborne radar networks Spaceborne cloud-profiling missions (EarthCARE, WIVERN, INCUS) High-resolution observations of marine boundary-layer clouds and polar mixed-phase systems Algorithms for retrieving vertical air motion, liquid water content, and drizzle microphysics Scientific Awards & Recognition AGU Atmospheric Sciences Ascent Award (2020) NASA Group Achievement Awards (2015, 2003) Humboldt Research Fellowship for Experienced Researchers, Germany (2013–2014) Canada Research Chair (Tier I 2012–2017, Tier II 2007–2012) Visiting Scientist Fellowship, CIRES, University of Colorado (2003–2004) Leadership & Service Since 2020 he directs the SBU–BNL Radar Observatory and since 2017 has led the Center for Multiscale Applied Sensing at BNL. Editorial roles include Editor of the AMS Journal of Applied Meteorology and Climatology (2024–present) and Associate Editor of EGU Atmospheric Measurement Techniques (2019–present). He sits on mission advisory groups for ESA EarthCARE and WIVERN, the NASA INCUS and ACCP science teams, and the DFG Collaborative Research Center CRC1502 advisory board.

Tommaso LenziView profile

Associate Professor

• Robotics
• Prosthetics
• Biomechanics
• +3 more

Tommaso Lenzi is an Associate Professor in the Department of Mechanical Engineering at the University of Utah , where he also serves as Director of the RMCOEH Ergonomics and Safety Program . His research focuses on wearable robotics , prosthetics , and biomechanics , with emphasis on developing technologies to improve mobility for individuals with amputations and stroke survivors. His work involves bio-inspired actuation systems , EMG control algorithms , and metabolic cost reduction in robotic prostheses. Notable contributions include the first technology to improve metabolic efficiency in above-knee amputations and open-access datasets for gait analysis. Recent publications highlight advancements in adaptive control , series-elastic actuators , and assistive robotics for daily ambulation. His research integrates human-machine interfaces and machine learning for terrain adaptation. Scientific awards include the NSF CAREER Award (2021) for bio-inspired wearable robots. His team collaborates with academic labs and industry partners to license technologies, focusing on self-aligning mechanisms and ultrasound-based kinematic prediction .

Bruce DobkinView profile

Professor

• Neurorehabilitation
• Stroke Recovery
• Neuroplasticity
• +4 more

Bruce Dobkin, M.D. is a Professor of Neurology at the David Geffen School of Medicine, UCLA , and Director of the UCLA Neurological Rehabilitation and Research Program . He co-leads the UCLA Stroke Program and contributes to the UCLA Wireless Health Institute , Brain Research Institute , and CTSI (Clinical and Translational Science Institute). Research Focus: Neurorehabilitation, stroke recovery, spinal cord injury, neuroplasticity, wearable sensor technology, robotic-assisted rehabilitation. Awards: Honorary Fellow of the Royal College of Physicians (2005), multiple research awards including the Kenneth Viste Memorial Award and Furst von Donnersmarck Prize for lifetime achievement. Leadership: Editor-in-Chief of Neurorehabilitation and Neural Repair (since 2006), former Scientific Officer for Neural Repair at the Adelson Medical Research Foundation (2006–2009). Recent Publications highlight trends in sensor-integrated rehabilitation systems , plasticity assessment , stroke outcome metrics , and neurological applications of machine learning . His work bridges clinical trials , neuroimaging , and technology-driven rehabilitation . Scientific Awards & Leadership: Honorary Fellow, Royal College of Physicians, London (2005) Editor-in-Chief, Neurorehabilitation and Neural Repair (2006–present) Irwin Levy Lectureship (2006) Kenneth Viste Award (2006) International Furst von Donnersmarck Prize (2006) Grants & Collaborations: Directed NIH-funded trials like LEAPS and SIRRACT, focusing on locomotor training, wireless health, and stroke recovery across global populations. His lab develops sensor-based systems for real-time activity monitoring and outcome assessment.

Rui LoureiroView profile

Professor

• Biomedical engineering
• Mechanical engineering
• Clinical sciences
• +8 more

Rui Loureiro is a full Professor of Surgical and Rehabilitation Engineering at University College London (UCL), where he leads the Department of Orthopaedics and Musculoskeletal Science and the Aspire Centre for Rehabilitation and Assistive Technology . Since 2017, he has served as Head of the Institute of Orthopaedics and Musculoskeletal Sciences and was appointed Research Director and Chair of the Research & Innovation Board at the NHS-led National Rehabilitation Centre in 2024. His work bridges advanced engineering with clinical applications, focusing on stroke rehabilitation, spinal/brain injuries, bionics, and assistive technologies. Research Interests : Loureiro specializes in Biomedical Engineering Medical Robotics Artificial Intelligence for Rehabilitation Virtual and Mixed Reality in Healthcare Wearable Technologies for Pain Management His publications highlight trends in functional near-infrared spectroscopy (fNIRS), edge computing for neurofeedback, and frugal medical device design. He advocates for interdisciplinary collaboration between engineers and clinicians to address global healthcare challenges. Scientific Recognition : Loureiro has received prestigious awards including SET for Britain Young Engineer Award (2004) IET Emerging Technology Award (2023) He founded the International Consortium on Rehabilitation Robotics (ICORR) and regularly serves as a keynote speaker at global conferences. Teaching Contributions : At UCL, he co-directs MSc programs in Rehabilitation Engineering and Assistive Technologies Minimally-invasive and Virtual Reality Surgery and teaches modules on virtual reality in healthcare and musculoskeletal biomechanics.