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Adam KennedyView profile

Researcher

• Data Management
• Ecosystem Ecology
• Wireless Communication
• +4 more

Adam Kennedy serves as a Cyberinfrastructure Architect within the Department of Forest Ecosystems & Society at Oregon State University's College of Forestry. His role focuses on developing robust data systems to support environmental research, particularly in forest hydrology and ecosystem monitoring. His educational foundation includes: B.S. in Environmental Sciences and Resources (2004) from Portland State University with a Biology minor M.S. in Environmental Sciences and Resources (2006) from Portland State University with a Hydrology certificate Completed PhD coursework and comprehensive exams in Environmental Sciences (2012) alongside an Ecosystem Informatics Certificate through the IGERT program Dr. Kennedy's research integrates data engineering with ecological science, specializing in real-time environmental monitoring systems. His primary interests encompass Data Management, Ecosystem Ecology, Long-range Wireless Communication, Quality Control Algorithms for Streaming Data, and Sensor Network Best Practices. This interdisciplinary approach enables advanced studies of forest canopy processes and hydrological dynamics through innovative technological solutions. Analysis of his publication trajectory reveals consistent focus on canopy hydrology and sensor technology applications. His recent work (2019-2022) demonstrates sophisticated modeling of dewfall dynamics using machine learning, while earlier research pioneered distributed temperature sensing for stream ecosystems and explored climate-streamflow relationships through teleconnection indices. The body of work shows progressive technical refinement in environmental data acquisition and analysis. No scientific awards are documented in the available sources, though his contributions to environmental data infrastructure are substantiated through technical publications and system development. Information regarding graduate student advising or research grants is not publicly accessible in the provided materials. Dr. Kennedy contributes to the Ecosystem Informatics initiative through his development of real-time data systems, as evidenced by his work on provisional data graphs and sensor network infrastructure. His technical expertise supports long-term ecological research at facilities like the HJ Andrews Experimental Forest, enabling high-resolution environmental monitoring across complex forest landscapes.

• Computer Graphics
• Motion Capture
• Artificial Intelligence
• +9 more

Dr. Zhidong Xiao serves as Principal Academic (Associate Professor) at Bournemouth University's National Centre for Computer Animation within the Faculty of Media and Communication. With over ten years of leadership experience including roles as Programme Leader, Head of Education, and Deputy Head of Department, he drives academic strategy and research innovation in computer animation and digital media. His work bridges technical excellence with creative industry applications through extensive collaborations across the UK and China. Dr. Xiao's educational foundation includes a PhD in Computer Graphics (2010) and postgraduate certificates in Education Practice (2010) and Research Degree Supervision (2011) from Bournemouth University, complemented by a BEng (Hons) in Thermodynamics from Taiyuan University of Technology, China (1994). PhD in Computer Graphics, Bournemouth University (2010) PGCE in Education Practice, Bournemouth University (2010) PGCE in Research Degree Supervision, Bournemouth University (2011) BEng (Hons) in Thermodynamics, Taiyuan University of Technology (1994) His research spans Computer Graphics, Motion Capture, Artificial Intelligence, and Virtual Reality with focus on physics-based simulation, sign language recognition, and motion synthesis. Recent work integrates partial differential equations with machine learning to solve animation challenges in facial realism, deformation simulation, and 3D reconstruction. His interdisciplinary approach connects computer science with creative industries, healthcare applications, and educational technology while advancing core techniques in neural rendering and motion analysis. Analysis of his 15 most recent publications reveals consistent innovation in physics-based animation techniques (40%), motion capture processing (25%), and neural approaches to 3D reconstruction (35%). Key trends include the fusion of analytical physics models with deep learning architectures, development of efficient real-time simulation methods, and expansion into accessibility applications through sign language recognition systems. Scientific recognitions include: Fellow of British Computer Society (2023) Fellow of Higher Education Academy (2011) Best Poster Award at Pacific Graphics 2014 He maintains active peer review roles for EPSRC, ESRC, IEEE Transactions on Multimedia, and ACM SIGGRAPH conferences. Dr. Xiao has supervised seven PhD students to completion while currently guiding Alexandra Sergeeva Alexdottir's research on Phantom Touch phenomena. His grant portfolio demonstrates strong industry-academia collaboration: Principal Investigator Capturing and representing sign language (British Council, 2025) VE Communication Programme (Erasmus+, 2020) Co-Investigator Rehabilitation Enhancement via Motion Capture (BU Fusion Fund, 2013) Cross-Channel Film Lab (Interreg, 2012) Digital Beijing Opera Project (2010) As a core member of Bournemouth's Computer Graphics and Visualisation Research Group and Centre for Digital Entertainment, he leads initiatives in motion capture technology through AccessMocap Studio. His international outreach includes invited lectures across China on computer animation education and visual effects techniques, strengthening global partnerships in creative technology development.

Hansen A. MansyView profile

Associate Professor

• Acoustic and vibrational phenomena in biological systems
• Bioinstrumentation
• Noninvasive patient monitoring methodologies
• +6 more

Hansen A. Mansy is an Associate Professor in the Department of Mechanical and Aerospace Engineering at the University of Central Florida , where he leads the Biomedical Acoustics Research Lab . He holds a Ph.D. in Mechanical and Aerospace Engineering from the Illinois Institute of Technology (1990) and has a distinguished career spanning academia and industry, including prior roles at Rush University (assistant professor 2003–2013, then associate professor). Education: Ph.D. in Mechanical and Aerospace Engineering (1990), Illinois Institute of Technology Dr. Mansy's research focuses on vibro-acoustic phenomena in biological systems and the development of non-invasive medical diagnostic tools . His work spans bioinstrumentation , acoustic modeling of soft tissues , flow-induced vibrations , and seismocardiography for cardiac monitoring. He has secured $5+ million in federal grants and collaborates with medical centers and device manufacturers. Recent publications highlight his pioneering work in seismocardiographic (SCG) signal analysis , including machine learning applications for heart failure prediction, respiratory phase detection, and studies on signal variability. His team explores SCG's potential for non-invasive intracranial pressure monitoring and hip dysplasia detection in infants. Awards: Whitaker Foundation Career Award (1997), Excellence in Teaching Award (2002). Dr. Mansy serves on editorial boards and review panels for NIH, NSF, DoD, AFOSR , and other national/international organizations, advancing biomedical acoustics research and education. Labs & Collaborations: The Biomedical Acoustics Research Lab at UCF develops cutting-edge diagnostic technologies, working with industry partners and clinical institutions to translate research into medical practice.

Bappaditya MandalView profile

Senior Lecturer

• Computer Vision
• Machine Learning
• Deep Learning
• +7 more

Bappaditya Mandal is a Senior Lecturer in Computer Science at Keele University's School of Computer Science and Mathematics, Faculty of Natural Sciences. He holds positions as an Academic Conduct Officer and actively contributes to both teaching and research. His academic journey includes a B.Tech in Electrical Engineering from IIT Roorkee, a Ph.D. in Electrical and Electronic Engineering from Nanyang Technological University, Singapore, and an MA in Higher Education Practice from Keele University. Dr. Mandal's research spans computer vision and machine learning with specific applications in biomedical image analysis, civil infrastructure inspection, human behavior analysis, and marine life detection. His work focuses on attention mechanisms, deep learning architectures, and subspace modeling, with recent publications demonstrating applications in medical diagnostics, structural engineering, and traffic prediction systems. His research demonstrates a consistent trajectory from foundational computer vision work to increasingly applied, interdisciplinary projects addressing real-world problems. His scholarly contributions include numerous publications in top-tier journals and conferences, with recent work focusing on attention-based deep learning models for concrete defect recognition, macular disease classification, and traffic flow prediction. The publications reveal a strong emphasis on developing interpretable attention mechanisms that can be applied across diverse domains while maintaining high accuracy. Award for Leading, Educating and Nurturing Talent (TALENT) from A*STAR Singapore Best Student Paper Award 2016: Honourable Mention Award from IAPR in Singapore Long service award from the Institute in 2014 Best Biometric Student Paper Award at the 19th International Conference on Pattern Recognition, Florida, USA, 2008 Research Scholarship Award from Nanyang Technological University (2004-2008) Dr. Mandal supervises PhD students including Asad Inamdar, Jenni Watson, and Kody Mistry, with research spanning medical applications, structural analysis, and AI systems. His work demonstrates strong industry connections, having collaborated with SMEs in both Singapore and the UK to develop practical solutions for research and development challenges. He is actively involved in grant-funded research, particularly in healthcare technology and infrastructure monitoring applications, and maintains affiliations with professional organizations including IEEE (Senior Member), British Computer Society (Fellow), and Higher Education Academy (Fellow).

Syed RizviView profile

Lecturer

• AI and Healthcare
• Data Mining
• Machine Learning
• +5 more

Syed Rizvi is a Lecturer at the CBL School of Management, actively engaged in interdisciplinary research spanning AI in healthcare, data mining, and machine learning. He holds a Doctorate in Computer Science from Beihang University (2017–2023), focusing on Point of Interest based Passenger Flow Estimation using Machine Learning. Affiliations: CBL School of Management, Principal Investigator in AI/Healthcare projects. Education: PhD in Computer Science, Beihang University (2017–2023). Research Interests: Syed’s work emphasizes AI-driven solutions for healthcare challenges, including neurological disorder detection via Body Sensor Networks, mood analysis through chat data, and optimizing business strategies using passenger flow prediction. He also explores computational approaches to health policy implementation in developing countries. Projects: Notable projects include the Indigenous AI-based MYO Electrode System for neurological disorders and smart business models using passenger data analytics. Awards: Fellow of Advance HE (2024). Grants/Activities: Led a 2021–2023 project on AI for disability detection in Pakistan. Engaged in invited talks, professional memberships (ACM, BCS), and journal peer-review. Labs/Teams: Collaborates on interdisciplinary teams for AI healthcare systems and data-driven policy analysis.

Yaseen SharifView profile

Researcher

• Geotechnical Engineering
• Offshore Renewable Energy
• Screw Pile Foundations
• +4 more

Yaseen Sharif is a Researcher in the Department of Civil Engineering at the University of Dundee, specializing in geotechnical engineering for offshore renewable energy systems. His work focuses on screw pile foundations, centrifuge modeling, and numerical simulation techniques like the Discrete Element Method (DEM). He contributes to UN Sustainable Development Goal 7 (Affordable and Clean Energy) through innovations in offshore wind energy infrastructure. Key research interests include screw pile installation mechanics, helix interaction dynamics, and soil-structure interaction in marine environments. His recent work explores installation advancement ratios, cyclic load responses, and silent piling technologies to reduce environmental impacts. Recipient of the Institution of Civil Engineers Telford Gold Medal 2024 Finalist for the 2025 Scottish Knowledge Exchange Awards Winner of the 2023 International Marine Contractors Association Sustainability Award His research has produced over 37 publications and two significant datasets, including centrifuge experiments on screw pile performance. Collaborations involve institutions like NGI Norway and industry partners for offshore wind solutions.

• Assistive Technologies
• Biomedical Engineering
• Computational Intelligence
• +5 more

Dr Jon Cobb is a Professor in Electronics at Bournemouth University's Department of Electronics. His career spans over three decades, combining expertise in microelectronics, biomedical engineering, and assistive technologies. He holds Chartered Engineer status and has collaborated with hospitals, audio companies (e.g., Naim Audio), and sports science departments on interdisciplinary projects. Education includes a PhD in Biomedical Engineering (BU, 2000), MSc in Microelectronics (University of Southampton, 1991), and a BTEC Higher National Diploma in Electronic Engineering (1990). He also completed a MRES in Music Technology (University of York, 2012). Research focuses on assistive technologies for neurological disorders (e.g., stroke rehabilitation via FES systems), sports performance analysis using accelerometers, and low-noise power supplies for high-fidelity audio. Current projects include collaborations with Salisbury District Hospital (stroke rehabilitation), BU Sports Science (swimmer performance), and Naim Audio (audio power solutions). Publications emphasize biomedical engineering applications, such as FES devices, wireless sensor networks, and thermal imaging for diabetic foot assessment. Supervised four doctoral students, including work on FES systems and swimming biomechanics. Grants include EPSRC funding for blood flow sensor development and industry partnerships (e.g., Odstock Medical Limited). His work balances clinical impact, engineering innovation, and cross-disciplinary collaboration.

• Biomedical Engineering
• Artificial Intelligence
• Medical Instrumentation
• +4 more

Janusz Kulon is a Professor of Biomedical Engineering and Applied Artificial Intelligence at the University of South Wales (USW), UK, within the Faculty of Computing, Engineering, and Science. His research focuses on advancing medical instrumentation and clinical applications of machine learning, with notable contributions to musculoskeletal diagnostics, smart sensing technologies, and aerosol characterization. He leads the Biomedical Engineering and Computing Research Group (now part of the CCMI Research and Innovation Group), collaborating with Cardiff & Vale University Health Board and other institutions. Key research interests include: - Smart sensing systems for sitting posture monitoring and wheelchair design - AI-driven clinical diagnostics (e.g., skin lesion detection) - Biomedical instrumentation for aerosol drug delivery systems - 3D human modeling for severe postural conditions - Ultrasonic localization and signal processing for medical applications His work contributes to USW's Health and Well-being Accelerator initiative. As an educator, he has designed and led 21 modules across undergraduate and postgraduate programs in biomedical engineering and computing. Notable projects include the Smart Sensing Wheelchair System for real-time posture monitoring and the Bipolar Next Generation Impactor (bp-NGI) for pharmaceutical aerosol analysis. His research emphasizes cost-effective solutions for clinical challenges, blending engineering innovation with AI advancements. Lab/Affiliations: - Biomedical Engineering and Computing Research Group (BECRG) - CCMI Research and Innovation Group

• Artificial Intelligence
• Cyber Security
• Civil Engineering
• +3 more

Ian Wilson is an Associate Professor at the Faculty of Computing, Engineering and Science, University of South Wales. His research spans interdisciplinary areas including artificial intelligence, cyber security, and civil engineering. He holds a strong focus on applying machine learning techniques to structural integrity analysis and cyber resilience frameworks. Education: Academic qualifications not explicitly listed in provided texts. Affiliations: Faculty of Computing, Engineering and Science (University of South Wales). Wilson's research interests emphasize AI-driven solutions for civil infrastructure monitoring (e.g., concrete crack detection via deep learning) and cyber security for industrial systems. His work bridges theoretical advancements with practical applications, such as semantic analysis of medical referrals and vulnerability assessments in IoT-enabled environments. Recent publications reflect a growing emphasis on critical infrastructure protection and cyber attack vector analysis. Publications trends show a dual focus on: 1) AI applications in civil engineering diagnostics and 2) cyber security frameworks for operational technology systems. His work frequently integrates interdisciplinary methods like neural networks, image processing, and semantic analysis. Awards: No scientific awards explicitly mentioned in provided texts. Grants & Advising: No specific grants or student advising records listed. Contributions include technical leadership in collaborative research projects and institutional teaching responsibilities.

Karen Rial-LoveraView profile

Associate Professor

• Agroecology
• Sustainable Agriculture
• Precision Agriculture
• +4 more

Dr Karen Rial-Lovera is an Associate Professor in Agriculture and Co-Dean for Agricultural Science and Practice at the Royal Agricultural University (RAU). She holds a PhD from Coventry University, an MSc and BSc from the University of Santiago de Compostela. Her academic roles include Course Lead for BSc(Hons) Agriculture and BSc(Hons) Agricultural Management (Top-Up), as well as Programme Lead for Student Voice. She has held senior academic positions at RAU and Nottingham Trent University (NTU). Her research focuses on agroecological practices, sustainable intensification, and inclusion in agricultural education. Notable projects include a £2M BBSRC-funded study on UK food system resilience, an EDI scoping study in UK agricultural education, and a farmers-led net-zero project. She has also led the ARES Innovation Farm at NTU focusing on precision agriculture and soil health. Rial-Lovera’s teaching portfolio includes courses on Crop Technology, Agronomy, and Integrated Agricultural Systems. She actively supervises PhD students and serves on professional bodies like the Institute of Agricultural Engineers (IAgrE) and BBSRC Research Grants Board. Her work bridges academic research with practical applications through collaborations with DEFRA, Royal Botanic Gardens, and international institutions.

Christopher ChoiView profile

Professor

• Heat and Mass Transfer
• Computational Fluid Dynamics (CFD)
• Livestock Housing Design
• +7 more

Christopher Choi is a Professor in the Department of Biological Systems Engineering at the University of Wisconsin–Madison. His research focuses on computational and experimental fluid dynamics applied to agricultural and biological systems, including livestock housing microclimate control, IoT-enabled precision agriculture, and water distribution network optimization. He leads the Heat and Mass Transfer Laboratory and holds patents on conductive cooling systems for dairy cattle. Education: Ph.D. in Mechanical Engineering, Colorado State University, 1990 Research Interests: CFD modeling for livestock ventilation systems Real-time biosensor networks for livestock health monitoring Water distribution system design for urban and agricultural applications Conductive cooling technologies to mitigate heat stress in dairy farms Algal biofuel production optimization Key Contributions: Developed ear tag biosensors (ETAG) for real-time cattle temperature monitoring Advanced positive-pressure ventilation systems for large dairy facilities Validated CFD models for predicting methane/ammonia emissions from barns Awards: Multiple Superior Paper Awards from ASABE (2019, 2017, 2014) ASCE Best Paper Award (2008) Labs/Teams: Heat and Mass Transfer Laboratory, collaborating with microbiologists, animal scientists, and electrical engineers on interdisciplinary projects.

Dirk Martin LuchtenburgView profile

Associate Professor

• Dynamics and Control
• Fluid Mechanics
• Smart Vehicles
• +4 more

Dirk Martin Luchtenburg is an Associate Professor in the Department of Mechanical Engineering at The Cooper Union, holding the C. V. Starr Distinguished Professorship of Engineering. He leads the Dynamics and Control Lab, where undergraduate students design model-based controllers for smart vehicles such as quadcopters and ground robots. His research spans fluid mechanics, dynamics, and control systems, with applications in active flow control, nonlinear aerodynamics, and robotics. Education: He earned his MS in Aerospace Engineering from Delft University of Technology (Netherlands) and his PhD in Fluid Mechanics from TU Berlin. He held postdoctoral and lecturing roles at Princeton University before joining Cooper Union in 2013 as a research fellow, becoming a full-time faculty member in 2015. Key Research Areas: Fluid flows, feedback control, robotics, and model reduction. Applications: Active flow control, nonlinear stall models, and smart vehicle control. Recent work includes gyroscopic control of robotic systems, dynamic mode decomposition for complex systems, and compliant leg designs for robotic landings. His lab emphasizes hands-on student involvement in cutting-edge projects. Awards: C. V. Starr Distinguished Professor of Engineering (2023) Ben-Gurion University Summer Research Fellowship (2025) Grants & Advising: Co-authored papers with students, including David Shekhtman and Yeeho Song. Received the 2021 Educational Innovation Grant. Mentors undergraduates in the Dynamics and Control Lab, focusing on robotics and fluid dynamics research. Labs & Collaborations: Cooper Dynamics and Control Lab. Collaborations include work on plasma blasters and participation in conferences like ASME and ICRA.

• Wave Energy Conversion
• Machine Learning Applications
• Structural Analysis
• +2 more

Masoud Masoumi serves as Adjunct Professor in Mechanical Engineering at the Albert Nerken School of Engineering, The Cooper Union. His research integrates mechanical engineering principles with machine learning applications, focusing on renewable energy systems, structural analysis, and wave propagation phenomena. Key research domains include: Machine learning applications for wave energy conversion and offshore wind farms Computational modeling of ultrasonic wave propagation in structures Stress prediction in mechanical components using convolutional neural networks Fluid dynamics in biomass energy systems Development of wave energy converters for marine applications Masoumi's extensive publication record demonstrates consistent innovation in applying computational methods to renewable energy challenges, particularly in optimizing wave energy systems and developing predictive maintenance frameworks for offshore infrastructure. Recent work emphasizes data-driven approaches for ocean energy harvesting and structural health monitoring.

• Biosciences
• Food Quality and Safety
• Molecular Biology
• +6 more

Olena Doran is a Professor in Biomedical Research and currently serves as the College Dean in Research and Enterprise at the University of the West of England (UWE) Bristol. She holds dual affiliations within the College of Health, Science and Society and the Faculty of Health and Applied Sciences (HAS). Her roles have included Director of Research Development at the Institute of Bio-Sensing Technology and Centre Director of the Centre for Research in Biosciences between 2010–2017, followed by Associate Dean in Research and Enterprise at HAS before her current deanship since 2022. Education: Olena earned her BSc+MSc (Distinction) and PhD in Biology from Kharkov State University, Ukraine. She furthered her career through the European Fellowship Fund at the Nenski Institute of Experimental Biology in Poland and a Royal Society/NATO Fellowship at the University of Bristol, where she spent a decade contributing to apoptosis research. Research Interests: Her work focuses on molecular mechanisms underlying food quality traits, development of novel biosensing technologies, cancer biology (including ethnic-group specific prostate cancer), hepatic CYP450 systems in cancer and meat quality, and mitochondrial functions in aging and disease. These interests drive her interdisciplinary approach bridging food safety, animal health, and biomedical applications. Articles Trends: Over the past five years, her publications emphasize electrochemical biosensor innovation for food quality analysis (e.g., glycerol, fatty acids, vitamins) and antimicrobial strategies using plasma-activated water and nanoformulations targeting pathogens like Salmonella and E. coli. This reflects a strong focus on practical technologies for agri-food safety and livestock health. Scientific Awards: She has been recognized with the European Fellowship Fund and Royal Society/NATO Fellowship, supporting her early career research in molecular biology and apoptosis mechanisms. Advising & Grants: Olena has advised and mentored hundreds of students across undergraduate and postgraduate programs, including PhD Action Learning Sets. Her research has attracted £6m+ in grants from BBSRC, AHDB, EU, and industry partners. She actively reviews for funding bodies in the UK, New Zealand, Belgium, and Canada, and chairs strategic initiatives like the UK/China Partnership on Novel Technologies. Labs & Teams: As a leader, she established the Institute of Bio-Sensing Technology and directed the Centre for Research in Biosciences. Collaborations span over 100 institutions globally, including the Chinese Academy of Agricultural Sciences, Swedish University of Agricultural Sciences, and Pfizer Ltd. She is a member of the Board of Governors at Bristol Zoological Society and leads the Academic Research Science Network.

Aphrodite GalataView profile

Lecturer

• Computer Vision
• Machine Learning
• Human-Robot Interaction
• +3 more

Aphrodite Galata is a Lecturer in Advanced Interfaces at the Human Computer Systems department. She holds a Doctor of Philosophy from the University of Leeds (2001) in Learning Variable Length Markov Models of Behaviour. Her research focuses on Computer Vision and Machine Learning, with special emphasis on sign language processing, human-robot interaction, and embodied learning systems. She has contributed to advancements in artificial agents learning sign language through imitation, phonological property recognition, and dataset development for American Sign Language analysis. Her research interests also span robotics, 3D pose estimation, and real-time tracking systems. Key topics in her work include gesture analysis, multimodal communication, and neural network architectures for feature representation. She has published widely in top-tier conferences including IEEE ICASSP and ACL, with notable contributions to datasets like WLASL-LEX. Notable projects include developing algorithms for hand tracking from monocular RGB data and exploring anisotropic cost functions for facial landmark detection. She has collaborated with researchers like Angelo Cangelosi on embodied sign language systems. Her work bridges computer vision techniques with cognitive modeling to enhance human-agent communication systems. Her research is aligned with the Digital Futures research beacon, emphasizing innovation in human-computer systems. While no specific awards are noted, her work has garnered significant readership on platforms like Mendeley, reflecting its academic impact. She has supervised 8 research works, contributing to the training of future scholars in advanced interface technologies.