جستجوی استاد راهنمای دانشگاهی

Ole-Christoffer Granmoمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Tsetlin Machines
• +۷ مورد دیگر

Professor Ole-Christoffer Granmo is a distinguished academic at the University of Agder, Norway, where he serves as Professor in the Department of Information and Communication Technology. He is the Founding Director of the Centre for Artificial Intelligence Research (CAIR) at the University of Agder, leading cutting-edge research in artificial intelligence and machine learning. Dr. Granmo obtained his master's degree in 1999 and his PhD in 2004, both from the University of Oslo. His academic journey has been marked by significant contributions to the field of AI, most notably the creation of the Tsetlin machine in 2018, for which he received the AI research paper of the decade award from the Norwegian Artificial Intelligence Consortium (NORA) in 2022. Professor Granmo's research primarily focuses on logical and causal world modeling across multiple modalities including images, sound, and natural language. His work spans logical auto-encoding, convolution, regression, transformer architectures, and reinforcement learning, all with the overarching goal of creating ultra-low-power artificial general intelligence through transparent logical learning and reasoning. His publications reveal a strong emphasis on interpretable AI systems, hardware implementations, and applications across diverse domains including cybersecurity, healthcare, social media analysis, and bioinformatics. AI Research Paper of the Decade (2022) - Norwegian Artificial Intelligence Consortium (NORA) Eight paper awards in machine learning Professor Granmo has coordinated over seven research projects and mentored 55+ master's students and nine PhD students. His leadership extends to co-founding the Norwegian Artificial Intelligence Consortium (NORA) and establishing two companies: Anzyz Technologies AS and Tsense Intelligent Healthcare AS. As an advisor at Literal Labs, he actively bridges academic research with practical industry applications, demonstrating his commitment to translating theoretical innovations into real-world solutions that address complex challenges across multiple sectors.

Weimin Huangمشاهده پروفایل

استاد

• Radar Remote Sensing
• Ocean Remote Sensing
• GNSS Reflectometry
• +۳ مورد دیگر

Professor Weimin Huang is a full Professor in the Faculty of Engineering and Applied Science at Memorial University of Newfoundland, where he has served since 2010 and became a full professor in 2019. He held the position of Department Deputy Head from 2020 to 2023. Education: BSc in Radio Physics (Radio Wave Propagation and Antennas), Wuhan University, 1995 MSc in Radio Physics (Radio Wave Propagation and Antennas), Wuhan University, 1997 PhD in Space Physics, Wuhan University, 2001 MEng in Electrical and Computer Engineering, Memorial University of Newfoundland, 2004 Postdoctoral Fellowship in Electrical and Computer Engineering, Memorial University of Newfoundland, 2007 Research Focus: Huang specializes in radar-based ocean remote sensing , with core expertise in high-frequency ground wave radar (HF radar) , GNSS Reflectometry , and synthetic aperture radar (SAR) . His work targets ocean surface parameter mapping including wind speed, oil spills, ship detection, and sea ice monitoring through advanced digital image processing and applied electromagnetics . Recent innovations integrate deep learning (CNNs, physics-informed models) with radar data for enhanced environmental monitoring. Publication Trends: His 2025 publications reveal a strong shift toward AI-driven solutions in remote sensing, with 5 high-impact papers in IEEE TGRS and Remote Sensing focusing on wind speed estimation (using GNSS-R and wavelet-CNN hybrids), oil spill mapping via SAR, ship detection with HF radar, and climate change analysis. These works demonstrate cross-disciplinary integration of machine learning with geophysical remote sensing. Scientific Awards: No awards were documented in the source material. Advising & Collaboration: With 358 co-authors including Bahram Salehi and Biyang Wen, Huang maintains a robust global research network. While specific student supervision isn't listed, his leadership role and publication volume indicate active graduate mentoring. The text mentions no grant details. Research Infrastructure: His work operates within Memorial University's engineering faculty, leveraging radar facilities for ocean sensing. Collaborations span institutions including Wuhan University and SUNY, suggesting participation in international radar remote sensing consortia focused on maritime applications.

• AI-enabled communications
• Green and energy-efficient communications
• Online optimization and machine learning
• +۶ مورد دیگر

E. Veronica Belmega is a Full Professor at ESIEE Paris (Université Gustave Eiffel) and a researcher at the LIGM laboratory in Marne-la-Vallée, France. Previously, she served as an Associate Professor at ENSEA graduate school and Deputy Director of the ETIS laboratory in Cergy. She holds an Engineer Degree from the University Politehnica of Bucharest, M.Sc. and Ph.D. from Université Paris-Sud 11, and an HDR habilitation from Université de Cergy-Pontoise. Her research focuses on AI-driven communication systems, energy efficiency, online optimization, and cyber-physical security, with a strong emphasis on applications in smart grids and IoT. Her work spans securing wireless communications against adversarial attacks, optimizing resource allocation in cognitive radio networks, and leveraging machine learning for GNSS localization and MIMO systems. Notable contributions include game-theoretic frameworks for PMU deployment and energy-efficient NOMA systems. Belmega has received prestigious awards such as the 2021 CY Alliance Award and the L’Oréal-UNESCO fellowship, and serves as an Area Editor for IEEE Trans. on Machine Learning in Communications and Networking. Current projects include a CEA LETI postdoc position on AI localization and a PEPR 5G project. She actively contributes to special issues like the EURASIP JASP on sustainable wireless communications. Belmega’s advising includes PhD student S. Maleki, co-author of her 2024 IEEE SmartGridComm Best Paper Award-winning work.

Jonathan Bedfordمشاهده پروفایل

استاد

• Physical Geodesy
• Earthquake Science
• Subduction Zone Dynamics
• +۳ مورد دیگر

Prof. Dr. Jonathan Bedford is a leading researcher in physical geodesy at Ruhr-Universität Bochum's Institute of Geology, Mineralogy and Geophysics. Previously, he worked at the German Research Centre for Geosciences (GFZ) in Potsdam and the Free University of Berlin. His research focuses on subduction zone dynamics, coseismic/postseismic deformation, and machine learning applications in geophysics. University of Leeds (BSc Geosciences) Colorado School of Mines (MS Geosciences) Free University of Berlin (PhD 2015) His work spans: Subduction zone mechanics and earthquake cycles Viscoelastic relaxation and afterslip modeling Machine learning for earthquake prediction Geodetic data analysis with GPS and InSAR Fault interaction and seismic hazard assessment Power-law rheology in crustal deformation Research trends from his publications show emphasis on: Pre-earthquake deformation patterns (wobbling, gradual unlocking) Postseismic processes (afterslip, viscoelastic relaxation, poroelasticity) Integration of geodetic and seismic data Physics-based and data-driven earthquake analog models Notable collaborations include GFZ Potsdam, Free University of Berlin, and Chilean institutions. His work combines numerical modeling with observational data to understand megathrust earthquake mechanisms and improve seismic hazard assessments.

Tommy Chanمشاهده پروفایل

استاد

• Structural Health Monitoring
• Bridge Engineering
• Moving Force Identification
• +۲ مورد دیگر

Professor Tommy Chan is Chair in Civil Engineering at Queensland University of Technology's School of Civil and Environmental Engineering. With over $10M in research funding, his work focuses on structural health monitoring of bridges and infrastructure systems. His research group develops cutting-edge methods for assessing structural integrity using vibration analysis, optical sensors, and machine learning. Professor Chan leads major projects including the ARC-funded 'Next Generation Bridge Monitoring' initiative developing real-time monitoring systems for prestressed concrete bridges. His team's innovations include GNSS-based settlement monitoring and synergic identification methods for prestress force evaluation. Current research explores vehicle-bridge interactions, damage detection algorithms, and novel materials for impact protection. He has received numerous honors including the Vice Chancellors' Leadership Award and Top Supervisor Award. Professor Chan founded the Australian Network of Structural Health Monitoring and serves on editorial boards for multiple journals in structural engineering.

Tyson Govan Phillipsمشاهده پروفایل

مدرس ارشد

• Autonomous Systems
• Robotics
• Mining Automation
• +۴ مورد دیگر

Dr. Tyson Phillips serves as Senior Lecturer and Director of Teaching and Learning at The University of Queensland's School of Mechanical and Mining Engineering within the Faculty of Engineering, Architecture and Information Technology. He is an active Affiliate of the Future Autonomous Systems and Technologies research group, focusing on translating robotics innovations into practical mining applications. His academic leadership includes curriculum development for engineering programs and direct industry engagement with major mining equipment manufacturers. He earned his Doctor of Philosophy (PhD) from The University of Queensland in 2016, with thesis research centered on LiDAR-based perception systems for autonomous excavators. His doctoral work established foundational methods for object pose verification in mining contexts. Phillips' research specializes in robotics perception for extreme mining environments, developing LiDAR-centric solutions for autonomous equipment operation amid dust, fog, and unstructured terrain. Key contributions include evidential reasoning frameworks for uncertainty management, real-time pose estimation algorithms, and sensor fusion techniques for excavators and bulldozers. His work bridges theoretical computer vision with industrial deployment, targeting operational safety and efficiency in mineral extraction. Publication analysis reveals consistent focus on mining robotics since 2012, with recent works (2021-2024) emphasizing minimal-sensor configurations, probabilistic terrain mapping, and vibration-assisted gripper technology. His 14 scholarly outputs demonstrate evolution from sensor evaluation (2012-2015) toward integrated autonomy systems (2018-2024), predominantly in Journal of Field Robotics and Sensors . He actively supervises graduate researchers as Principal Advisor for a PhD on multimodal perception mapping and Associate Advisor for two PhD projects involving spreader systems and physics-informed neural networks. Completed supervision includes a 2024 PhD on bulldozer terrain mapping and a 2021 Master's on shovel/hopper interaction strategies. Research funding spans 14 projects from 2012-2026, including current Australian Coal Association Research Program support (2025-2026) and major Caterpillar Inc. collaborations for ERS self-protection and articulated truck automation. Phillips operates within The University of Queensland's Future Autonomous Systems and Technologies group, which develops field-deployable autonomy solutions for mining partners. This team conducts real-world testing of perception systems using Caterpillar and FMG operational sites as validation environments.

Samer M. Khanafsehمشاهده پروفایل

استاد پژوهش

• Navigation Systems
• Aerospace Engineering
• Sensor Integration
• +۵ مورد دیگر

Samer M. Khanafseh is a Research Associate Professor in the Department of Mechanical, Materials, and Aerospace Engineering at Illinois Institute of Technology (IIT), affiliated with the CARNATIONS research group. He holds a Ph.D. in Mechanical and Aerospace Engineering from IIT (2008), an M.S. from IIT (2002), and a B.S. in Mechanical Engineering from Jordan University of Science and Technology (2000). His research focuses on high-accuracy navigation algorithms, cycle ambiguity resolution, fault monitoring, and robust estimation techniques. Key areas include GNSS spoofing detection, integrity risk bounding, and sensor integration for aerospace applications. He is a member of the Institute of Navigation (ION) and the American Institute of Aeronautics and Astronautics (AIAA). His publications span navigation integrity, fault-tolerant systems, and GNSS applications, with notable work on Bayesian fault-tolerant estimators and GNSS spoofing attack detection using aircraft autopilot responses. His work bridges theoretical modeling with experimental validation, such as testing ground-based augmentation systems (GBAS). Awards: Best-of-Session Paper Award, Institute of Navigation (2006) Institute of Navigation 2011 Early Achievement Award Grants/Advising: Active involvement in CARNATIONS research initiatives, though no formal advisee list is provided. Labs/Teams: CARNATIONS (Context-Aware Navigation and Optimal Sensing) research group at IIT.

• Autonomous Systems
• Signal Processing
• Vehicle Health Management
• +۷ مورد دیگر

Dr Ivan Petrunin is a Research Professor in Signal Processing for Autonomous Systems and a DARTeC Fellow at Cranfield University's School of Aerospace, Transport and Manufacturing. His work focuses on advancing sensor technologies, data fusion, and decision-making systems for Cyber-Physical Systems, with applications in aerospace, ground-based autonomous systems, and urban air mobility. Key areas include Position, Navigation and Timing (PNT), vehicle health management, and AI-driven fault detection. He leads research at facilities like the Muti-User Environment for Autonomous Vehicle Innovation (MUEAVI) and collaborates with industry partners like Airbus, Rolls-Royce, and Thales. Education: BSc and MSc in Design of Electronic Equipment from National Technical University of Ukraine (1996–1998), followed by a PhD in Signal Processing for Condition Monitoring from Cranfield University (2013). Prior to Cranfield, he was a Lecturer in Digital Signal Processing at NTU Ukraine (2001–2005). Research Interests: Autonomous Systems & Sensor Fusion Machine Learning in Navigation and Safety GNSS Integrity & Urban Air Mobility Condition Monitoring & Structural Health Multi-Agent Reinforcement Learning Publications: Over 100 journal/conference articles and book chapters, with recent works emphasizing hybrid sensor fusion, resilient navigation architectures, and AI-driven solutions for GNSS-denied environments. Notable contributions include multi-sensor fusion frameworks for UAVs and Bayesian filter innovations. Awards: FRIN Fellowship, SMAIAA Membership, IEEE and ION Fellowships, and FHEA recognition. His work is supported by ESA, Innovate UK, and EPSRC. Advising & Labs: Supervises PhD students in UAV navigation and machine learning. Leads Cranfield's facilities for autonomous systems experimentation and advanced timing node infrastructure.

Peter F. Swaszekمشاهده پروفایل

استاد

• Digital Communications Systems
• Electronic Navigation Systems
• Signal Detection
• +۲ مورد دیگر

Peter F. Swaszek is a Professor in the Department of Electrical, Computer and Biomedical Engineering at the University of Rhode Island. His contact details include phone: 401.874.5802, email: swaszek@uri.edu, and office location: Fascitelli Center for Advanced Engineering, Rm 492. Education: Ph.D., Electrical Engineering, Princeton University, 1982 M.S., Electrical Engineering, Princeton University, 1979 B.S., Electrical Engineering, New Jersey Institute of Technology, 1978 Research Focus: Professor Swaszek specializes in Digital Communications Systems and Electronic Navigation Systems. His work spans signal detection, vector quantization, GNSS spoofing mitigation, celestial navigation optimization, and satellite positioning technologies. Recent publications emphasize maritime security, high-latitude navigation challenges, and innovative positioning methods like R-Mode. Publication Trends: His 2018–2020 articles cluster around enhancing navigation resilience, with themes including spoof detection (using bearing measurements), celestial navigation refinements, and satellite system performance limits. This reflects a consistent focus on reliability and security in electronic navigation.

Clark N. Taylorمشاهده پروفایل

دانشیار

• Computer Engineering
• Navigation Systems
• Sensor Fusion
• +۱۲ مورد دیگر

Dr. Clark N. Taylor is an Associate Professor of Computer Engineering and Director of the ANT Center at the Air Force Institute of Technology (AFIT), located at Wright-Patterson Air Force Base, Ohio. He is actively engaged in research and education within the Graduate School of Engineering and Management, focusing on advanced navigation and sensor fusion technologies for autonomous systems. Ph.D., Electrical and Computer Engineering (Computer Engineering), University of California, San Diego, 2004 M.S., Electrical and Computer Engineering, Brigham Young University, 1999 B.S., Electrical and Computer Engineering, Brigham Young University, 1995 Dr. Taylor's research spans computer engineering, navigation systems, and autonomous robotics, with a strong emphasis on sensor fusion, state estimation, and robust uncertainty modeling. His work integrates vision, inertial, magnetic, and pressure sensors for navigation in GPS-denied environments, particularly for unmanned aerial vehicles (UAVs). He is a leading expert in factor graph-based estimation, visual-inertial odometry, cooperative localization, and magnetic navigation. His publications demonstrate a consistent trend toward robust, uncertainty-aware estimation frameworks. Over the past decade, his research has evolved from early work on visual stabilization and pose estimation to advanced topics such as conservative covariance estimation, invariant filtering, and machine learning for spacecraft pose estimation. His recent articles focus on factor graphs, multi-agent fusion, and deep learning, indicating a trajectory toward intelligent, resilient navigation systems for defense and aerospace applications. Scientific awards include a Best Presentation in Session award at the ION GNSS+ conference in 2021. His research is supported by the U.S. Air Force and related defense agencies, with applications in surveillance, autonomous refueling, and on-orbit inspection. Dr. Taylor has advised numerous MS and PhD students, particularly in the areas of UAV navigation, sensor fusion, and cooperative localization. His lab, the ANT Center, focuses on advanced navigation and tracking, bringing together students and researchers to develop cutting-edge solutions for real-world operational challenges. The team conducts both simulation and experimental work, often integrating novel sensor modalities and estimation algorithms for improved system performance.

O-Jong Kimمشاهده پروفایل

استادیار

• Nano-satellite development and operation
• Alternative positioning navigation and timing
• Indoor precise positioning
• +۵ مورد دیگر

O-Jong Kim is an Assistant Professor in the Department of Aerospace Engineering at Sejong University, specializing in satellite navigation systems and precise positioning technologies. His research bridges theoretical advancements with practical applications in aerospace engineering, particularly focusing on CubeSat development and GNSS technologies. His educational background includes: B.A. from Seoul National University (2011) M.A. from Seoul National University (2013) Ph.D. from Seoul National University (2018) Dr. Kim's research interests center on nano-satellite development and operation, alternative positioning navigation and timing systems, indoor precise positioning, and GNSS receiver technology. His work addresses critical challenges in navigation systems, particularly in urban and indoor environments where traditional GNSS signals face significant limitations due to signal obstructions and multipath effects. Analysis of his recent publications reveals a strong focus on practical navigation solutions, with particular emphasis on multipath mitigation techniques, CubeSat-based navigation systems, and alternative positioning approaches for emerging applications like Urban Air Mobility. His research demonstrates consistent progression from theoretical algorithms to field-tested implementations, with publications showing increasing citation impact. Dr. Kim has established productive research collaborations, particularly with Seoul National University colleagues, evidenced by his extensive co-authorship network. His research output shows steady growth, with significant publication activity in 2020, 2023, and 2024, indicating active research momentum and sustained scholarly productivity. His major achievements include the design, development, launch, and in-orbit operation of the SNUGLITE cubesat, and the development of single-transmitter-based positioning systems for alternative navigation and indoor navigation applications. These accomplishments demonstrate his ability to translate theoretical research into operational space systems.

Dennis Akosمشاهده پروفایل

استاد

• RF Signal Processing
• RF Interference
• Integrated Navigation Systems
• +۳ مورد دیگر

Dennis Akos is a Professor in the Department of Aerospace Engineering Sciences at the University of Colorado Boulder. He is affiliated with the Research and Engineering Center for Unmanned Vehicles (RECUV) and the Colorado Center for Astrodynamics Research (CCAR). His research focuses on RF signal processing, RF interference mitigation, integrated navigation systems, and VHF modulation. He holds a Ph.D. in Electrical and Computer Engineering from Ohio University (1997), with earlier degrees from the same institution. His professional experience includes roles at Stanford University’s GPS Laboratory and the Lulea Institute of Technology. He has received notable awards such as the Institute of Navigation Fellow (2022), Thurlow Award (2009), and multiple best paper awards. His work emphasizes GNSS security, spoofing detection, and low-cost receiver solutions. Recent articles highlight advancements in GNSS RFI localization, Android device navigation, and software-defined radio applications. His lab explores innovations in space situational awareness, multi-sensor PVT solutions, and interference-resistant systems. Collaborative projects leverage crowdsourced smartphone data to enhance GNSS reliability. Awards: Fellow of the Institute of Navigation, Thurlow Award, Samuel M. Burka Award, and FAA Excellence in Aviation Research. Grants/Advising: Advising on GNSS security and Android-based navigation systems; involved in federally funded research on interference mitigation and satellite clock stability. Labs/Teams: Leads research at RECUV and CCAR, focusing on unmanned systems and astrodynamics challenges.

Kyle O'Keefeمشاهده پروفایل

استاد

• Global Navigation Satellite Systems (GNSS)
• Indoor Positioning and Navigation
• Ultra-wideband Ranging
• +۶ مورد دیگر

Kyle O'Keefe is a Professor in the Department of Geomatics Engineering at the University of Calgary's Schulich School of Engineering. He holds dual B.Sc. degrees in Geomatics Engineering (University of Calgary, 2000) and Honours Physics (University of British Columbia, 1997), and a Ph.D. in Geomatics Engineering (University of Calgary, 2004). He is a Professional Engineer (P.Eng.) registered with the Association of Professional Engineers and Geoscientists of Alberta since 2005. His research focuses on positioning and navigation technologies, including Global Navigation Satellite Systems (GNSS) advancements Ultra-wideband (UWB) ranging for vehicle/pedestrian navigation Indoor positioning using wireless signals Wearable sensor integration for biomechanics and navigation GNSS spoofing detection and cybersecurity Notable projects include: Development of UWB-augmented GNSS for RTK surveying (2007–present) Wearable sensor systems for rowing/kayaking motion analysis (2017–present) CanX-2 nanosatellite GPS receiver operations (2008) Igliniit project with Inuit hunters for Arctic environmental monitoring (2006–2009) Multi-constellation GNSS evaluation across 20+ years He has received prestigious awards including the Michael Richey Medal (2011) and multiple Best Paper Awards at IPIN and ION conferences. His teaching includes courses like Advanced GNSS Theory and Wireless Location. Active in professional organizations, he co-edits special journal issues and advises industry on emerging navigation technologies.

Ciriaco D'Ambrosioمشاهده پروفایل

پژوهشگر

• Combinatorial Optimization
• Heuristics
• Metaheuristics
• +۴ مورد دیگر

Ciriaco D'Ambrosio is a Research Fellow at the Department of Mathematics, University of Salerno, specializing in combinatorial optimization and its applications to wireless sensor networks. He teaches courses in operations research and maintains regular reception hours for students on Tuesdays (3:00-5:00 PM) and Wednesdays (4:00-5:00 PM), conducted both in-person and via Microsoft Teams. Education: PhD in Computer Science, University of Salerno (2015) - Thesis: models and algorithms for coverage in Wireless Sensor Network Laurea cum laude in Computer Science, University of Salerno (2011) Research Focus: D'Ambrosio specializes in combinatorial optimization, developing heuristics, metaheuristics, and math-heuristics for mixed integer linear programming problems. His work addresses challenging optimization problems in wireless sensor networks, particularly network lifetime maximization under coverage, connectivity, and interference constraints. His research bridges theoretical computer science with practical applications in sensor network design, seismic monitoring systems, and resource allocation problems. His methodology often combines exact approaches with sophisticated heuristic techniques to solve computationally difficult problems. Publication Trends: Analysis of D'Ambrosio's publications (2017-2025) reveals a progression from foundational work on sensor network lifetime problems toward increasingly sophisticated algorithmic approaches for combinatorial optimization. His recent work shows expansion into seismic monitoring applications while maintaining strong focus on knapsack problem variants and network optimization. His publications appear in high-quality journals including Soft Computing, Computers & Operations Research, and Networks, demonstrating both theoretical rigor and practical relevance of his research. Professional Activities: Member of the Italian Operations Research Society (AIRO) Associate Editor for Soft Computing, A Fusion of Foundations, Methodologies and Applications Active collaborator with researchers including Andrea Raiconi, Raffaele Cerulli, and Francesco Carrabs Research Infrastructure: D'Ambrosio works within the Department of Mathematics at University of Salerno's Fisciano Campus (Building F2, Room 040). His research contributes to the university's growing expertise in computational optimization and has practical applications in environmental monitoring systems like SEISMONOISY.

Mingfeng Wangمشاهده پروفایل

مدرس ارشد

• Continuum Robotics
• Legged Robotics
• Soft Robotics
• +۵ مورد دیگر

Dr. Mingfeng Wang is a Senior Lecturer in Robotics and Autonomous Systems at Brunel University London, affiliated with the Department of Mechanical and Aerospace Engineering within the College of Engineering, Design and Physical Sciences. His research focuses on specialized robotic systems including continuum, legged, soft, precision farming, and miniaturized robots. Chartered Engineer (CEng) with Engineering Council UK Fellow of the Higher Education Academy (FHEA) Member of IEEE, IEEE-RAS, IMechE, and IFToMM Editorial roles: Associate Editor of International Journal of Advanced Robotic Systems (JCR-Q3); Associate Editor of Frontiers in Robotics and AI (JCR-Q2); Editor of Information Processing in Agriculture (JCR-Q1), Biomimetic Intelligence and Robotics (JCR-Q1), and STEM Education Research expertise includes: Continuum Robotics : Design of extra-slender continuum robots (diameter-to-length ratio Legged Robotics : Parallel mechanism-based biped and hexapod robots for extreme environments Miniaturized Robotics : Active locomotion and drug delivery in capsule endoscopes Soft Robotics : Compliant end-effectors and bio-inspired designs Precision Farming : Laser weeding systems and agricultural automation Key scientific awards: BRIEF award (2022) TAROS Best Paper Post Nomination (2022) IFToMM Asian-MMS Best Paper Award (2014) Recent publications focus on: Cochlear implant surgery robotics Passive compliance in train fluid servicing Snake-biomimetic sealing surfaces Parallel kinematic manipulators Capsule endoscope image enhancement Professional services include conference organization (TAROS 2023/2024 Steering Committee; TAROS 2024 Programme Chair) and journal refereeing for IEEE-ASME Transactions on Mechatronics and Scientific Reports.