Find Academic Supervisors

• Radar Sensing
• Biomedical Engineering
• Networked Radar Systems
• +6 more

Alan Bannon serves as a Research Associate in the Department of Electrical and Electronic Engineering at Imperial College London's Faculty of Engineering. He is actively involved with the UK Dementia Research Institute's Care Research and Technology (CR&T) Centre and maintains a visiting researcher position at the UCL Radar Group. His work focuses on developing practical radar sensing solutions for healthcare applications, particularly in dementia care and elderly monitoring. Dr. Bannon's research interests center on applying System-on-Chip (SoC) radar sensors to biomedical challenges, with specific focus on scalable networked radar systems and metamaterial applications in radar sensing . His work bridges electrical engineering with healthcare technology, developing unobtrusive monitoring systems that can track vital signs, gait patterns, and sleep quality without requiring patient compliance or wearable devices. This research has significant implications for dementia care, where continuous monitoring can detect subtle behavioral changes that might indicate disease progression. Analysis of his publication record reveals a consistent trajectory of innovation in radar technology applied to healthcare monitoring. His recent work (2024-2025) demonstrates increasing sophistication in UWB radar applications for physiological monitoring, gait analysis, and dementia care. The research shows a clear progression from basic radar system development toward integrated healthcare solutions that address specific clinical needs in elderly care. His publications frequently appear in IEEE journals and conferences, indicating strong recognition within the engineering community. Dr. Bannon completed his M.Eng in Electrical and Electronic Engineering at University College London with a focus on photonics and radar systems, including an exchange year at Georgia Institute of Technology where he specialized in VLSI techniques and digital synthesis. His technical background in both photonics and radar systems provides a unique foundation for his current work in biomedical radar sensing. Outside his academic work, Dr. Bannon practices and coaches archery and pursues various personal engineering projects, demonstrating a hands-on approach to both technical and physical challenges.

• Geriatric Medicine
• Bioengineering
• Perioperative Care
• +5 more

Prof. Michael Fertleman is a Professor of Practice in the Department of Bioengineering at Imperial College London’s Faculty of Engineering. He is also a consultant physician specializing in geriatric surgical care, focusing on perioperative management of elderly patients. Leading the Cutrale Perioperative & Ageing Group, his research integrates bioengineering tools to mitigate surgical risks for older adults, with a focus on frailty, postoperative cognitive decline, and home-based health monitoring systems. He currently supervises 12 doctoral students and chairs the Specialty Advisory Committee (SAC) for UK geriatric medicine training, overseeing 800+ registrars. His work spans clinical research, medical device innovation, and improving surgical outcomes through interdisciplinary collaboration. Research Interests: Prof. Fertleman’s work bridges geriatric medicine and bioengineering, addressing challenges such as perioperative neurocognitive disorders, sarcopenia post-surgery, and remote patient monitoring. His team develops AI-driven diagnostic tools and wearable sensors to assess mobility, cognitive function, and recovery in older adults undergoing surgery. Key themes include frailty assessment, geriatric trauma outcomes, and optimizing care transitions post-hospital discharge. Recent Work Trends: Recent publications emphasize home monitoring technologies for TBI patients, cytokine changes post-surgery, and the impact of cervical collars on swallowing function. His work also explores genetic risk factors for hip fractures and immunological responses to SARS-CoV-2 vaccines in diabetic populations. Clinical trials focus on reducing postoperative delirium and improving geriatric surgical protocols through multidisciplinary team approaches. Scientific Awards: None explicitly listed. Advising & Grants: Supervises 12 active PhD/MRes students; leads the SAC for UK geriatric medicine training; oversees multiple clinical studies funded by Imperial College and NHS partnerships. Labs/Teams: Cutrale Perioperative & Ageing Group (Imperial College London) focuses on bioengineering solutions for aging populations, collaborating with the St Mary’s Hospital surgical teams and NHS Trusts. Active projects include developing smart-home monitoring systems and predictive analytics for surgical risk assessment in elderly patients.

• Agricultural Safety
• STEM Education
• Farm Safety Education
• +4 more

Roger Tormoehlen is a Professor in the Department of Agricultural & Biological Engineering at Purdue University. He holds a B.S., M.S., and Ph.D. in Agricultural Education and Health and Safety from Purdue. He leads engineering initiatives in the Indiana 4-H program, focusing on aerospace, equipment safety, and disability inclusion through the Perfect Fit program. His research emphasizes computer-aided instruction and multimedia tools for youth education, including tractor safety and disaster preparedness programs. Dr. Tormoehlen has received numerous awards for safety advocacy, including the National Safety Council's Distinguished Service Award (2002). He develops curricula for PK-12 students and advises on agricultural safety standards. Education: B.S. Agricultural Education, Purdue University M.S. Agricultural Education, Purdue University Ph.D. Agricultural Health and Safety, Purdue University Research Interests: Dr. Tormoehlen pioneers innovative educational technologies to enhance agricultural safety and STEM engagement. His work bridges formal and informal learning through 4-H programs, emphasizing: Youth exposure to engineering concepts via hands-on projects Disability-inclusive agricultural education Multimedia tools for non-formal education environments Awards: National Safety Council's Award of Honor (1991) Blue Ribbon Awards (ASAE, 1983-1998) Professional Skills Award (Agricultural Communicators in Education, 1992) First Place National Safety Council Research Project (1993) Advising & Outreach: Leads 4-H engineering initiatives, mentors youth in STEM competitions, and collaborates on national safety programs like Gearing Up for Safety. His work extends to developing safety certification exams and training modules for young agricultural workers. Labs/Teams: Central to Purdue's 4-H educational infrastructure, collaborating with ADM Agricultural Innovation Center and Maha Fluid Power Research Center for applied safety and engineering solutions.

• Robotics
• Artificial Intelligence
• Educational Technology
• +3 more

Dr. Esyin Chew is a Reader in Robotics and Educational Technologies at Cardiff School of Technologies, Cardiff Metropolitan University, and Director of the EUREKA Robotics Centre. She leads research in AI, robotics, and EdTech, with over 140 publications and £multi-million grants from Welsh Government, British Council, and the Alan Turing Institute. Her work focuses on healthcare robots, STEM education, and policy consultation for AI and pandemic response. She has supervised over 20 PhD students and advises on robotics integration in healthcare, hospitality, and education. Affiliations: EUREKA Robotics Centre (80+ robots), Cardiff School of Technologies Research Focus: Healthcare robotics, AI-driven companionship, STEM equity, data visualization Grants: £multi-million projects in UK, EU, Australia, and Malaysia Key contributions include the HUG™ dementia care artifact, AI fall detection systems, and cross-cultural STEM initiatives. Her research bridges academia and industry, emphasizing ethical deployment and societal impact.

• Bioengineering
• Age-related Pathologies
• Robotics
• +6 more

Dr. Barry L. Bentley is an Associate Professor in Bioengineering at Cardiff Metropolitan University, leading the Bioengineering Research Group and serving as Deputy Director of the EUREKA Robotics Centre. He is also a Fulbright Scholar at Harvard Medical School and Massachusetts General Hospital, alongside holding fellowships with the Royal Society of Biology, Foresight Institute, and Higher Education Academy. His research spans bio preservation systems, age-related pathology classification under WHO ICD-11, and robotics for healthcare applications. He previously contributed to ESA’s Advanced Concepts Team on brain-inspired planetary rover control and space flight software verification with MIT and SUNY Buffalo. Education: PhD from University of Cambridge (MRC Laboratory of Molecular Biology), specializing in C. elegans neuromodulatory connectome mapping. Research interests include bioengineering innovations, AI-driven healthcare solutions, and global health policy. Notable projects include the ICCARP consortium for pathology classification and AI-enabled fall detection systems using EUREKA robots. Awards include Fulbright Scholar and multiple prestigious fellowships. Grants and collaborations involve organizations like the European Space Agency, ARM Holdings, and the Alan Turing Institute. He advocates for ethical AI, privacy protection, and intergenerational mental health programs. His work addresses societal challenges like aging populations, post-pandemic mental health, and STEM outreach in Wales and Malaysia.

Mohamed SedkyView profile

Professor

• Computer Vision
• Video Analytics
• Cyber-Physical Systems
• +4 more

Professor Mohamed Sedky holds the position of Professor of Cyber-Physical Systems at Staffordshire University. He previously founded SKM Communication Systems and served as a lecturer at the Arab Academy for Science and Technology before joining Staffordshire in 2003. His roles include MSc Computer Science Deputy Award Leader and BSc Internet of Things Award Leader. He leads research at AVA Technologies Ltd, focusing on real-time video analytics algorithms such as Spectral-360®, which addresses security, safety, and business intelligence applications. His patented work in object detection and change detection has been globally recognized. He teaches modules like Fundamentals of Computer Networks and Router Security Technologies. Education: BEng (Hons) Electro-Physics and Communications, Alexandria University (1996) MSc Communications and Electronics, Arab Academy for Science and Technology (2002) PhD Computer Vision, Staffordshire University (2009) PGC Research Supervision, Staffordshire University PGC Higher and Professional Education, Staffordshire University Research Interests: Object recognition/segmentation Video surveillance systems IoT forensic processes AI in healthcare and smart environments Commercial Ventures: Founder of Spectral-360® technology Lead Researcher at AVA Technologies Ltd Consultant for Serco, Centralweighing, and WMTN Labs & Projects: Developed AVA Technologies' Detect/Protect/Count/Summarise solutions Designed OpenSHS (Open Smart Home Simulator) Conducted feasibility studies for buried utility detection and industrial inspection His research bridges academia and industry through patented innovations in video analytics and IoT systems, addressing challenges in security, healthcare, and smart infrastructure.

Jingao XuView profile

Research Fellow

• Event Cameras
• Drone Systems
• SLAM
• +5 more

Jingao Xu is a Research Fellow in the Computer Science Department at Carnegie Mellon University's School of Computer Science, based in room 9120 of the Gates and Hillman Centers. His research bridges computer vision, robotics, and edge computing with a focus on real-world applications in drone systems and mobile sensing. His work addresses critical challenges in resource-constrained environments through innovative sensor fusion techniques. Xu's primary research centers on event camera technology , where he pioneers applications in drone navigation, SLAM, and environmental monitoring. His contributions include deraining algorithms using state space models (PRE-Mamba), mmWave radar-event camera fusion for drone landing, and multi-robot gas source localization (SniffySquad). He specializes in extracting value from high-frequency event streams under challenging conditions like rain, low light, and high-speed motion, with significant work in fall detection systems and urban air quality monitoring through mobile crowd-sensing (CatUA). Analysis of his 15 most recent publications (2024-2025) reveals three dominant trends: (1) Adoption of state space models (particularly Mamba variants) for efficient event stream processing, (2) Integration of event cameras with complementary sensors (mmWave radar, depth, IMU) for robust perception, and (3) Development of edge-assisted frameworks for real-time drone operations in wildfire suppression and autonomous navigation. His work consistently targets practical deployment on mobile platforms with severe computational constraints. No scientific awards or honors were mentioned in the available information. Details regarding student advising, research grants, laboratory affiliations, or team structures were not provided in the source material.

Tong XiaView profile

Research Fellow

• Machine Learning
• Artificial Intelligence
• Public Health
• +7 more

Tong Xia is a postdoctoral research associate at the Department of Computer Science and Technology, University of Cambridge , where he completed his PhD under Prof. Cecilia Mascolo . He will join the Vanke School of Public Health at Tsinghua University as an Assistant Professor in Fall 2025. His research focuses on human-centric data from mobile and wearable devices, with applications in public health , behavioral understanding, and urban management. Technological specializations include: Data-efficient machine learning (self-supervised learning, foundation models) Trustworthy deep learning (uncertainty quantification, federated learning) Statistical methods (clustering analysis, causal inference) His work explores ubiquitous sensing technologies and AI tools for affordable health screening, including projects like OPERA system for respiratory acoustic foundation models and RespLLM for multimodal health prediction. Research has been supported by ERC EAR and EPSRC RELOAD grants. Scientific awards include: Rising Star in Women in Engineering, Asian Dean’s Forum (2024) Chinese Government Award for Outstanding Self-financed Students Abroad (2023) Best Postgraduate Poster, Oxbridge Women in Computer Science Conference (2022) Better Future Award, Cambridge Hall of Fame (2022) As a mentor, he supervised: Yuwei Evelyn Zhang (MPhil, Uncertainty quantification in federated learning , 2022) Alex Wang (Part II, Bayesian model ensemble uncertainty , 2022) He co-organized the Mobile and Wearable Health Seminar Series (2023-2024) and serves as an associate editor for Frontiers in Digital Health (IF 3.2). Non-academic roles include Vice Secretary-General of UK Tsinghua Alumni Association (2023-present).

• Sustainable and Resilient Environments
• Workplace Safety and Health Risk Monitoring
• Digital Transformation in Project Management
• +6 more

Dr. Hoonyong Lee is a Lecturer at the School of Project Management, Faculty of Engineering, University of Sydney. His research focuses on building sustainable and resilient environments through advanced safety and health risk management frameworks. PhD in Construction Science, Texas A&M University Postdoctoral Fellow, University of Michigan Member, Net Zero Institute and Brain and Mind Centre Research spans human sensing technologies , data analytics , and behavioral intervention design , with applications in: Construction Safety Management Smart Home Healthcare Fall Risk Assessment Household Energy Conservation His work combines wearable biosensors , Wi-Fi CSI , and machine learning for proactive risk identification. Recent projects focus on team cohesion in project management using physiological data analytics. 2024 Best Paper Award, Construction Research Congress 2024 Best Data Award Honorary Mention, ASCE DSA Committee Multiple award-winning publications (2012–2024) Teaching includes Project Acceptance and Project Planning courses. Leads Team L in developing adaptive intervention systems.

• Health Informatics
• Digital Health
• Artificial Intelligence in Healthcare
• +3 more

Dr. Simon Poon is an Associate Professor at the University of Sydney with a cross-disciplinary focus at the intersection of Health Informatics , Computer Science , and Traditional Chinese Medicine (TCM) data analytics . He holds multiple academic roles including Honorary Associate at the University of Sydney Business School and Adjunct Associate Professor at Chinese University of Hong Kong (CUHK) in the Institute of Integrative Medicine. Co-founder and Director (2014-2019) of Master of Health Technology Innovation (MHTI) program Member of Charles Perkins Centre , Sydney Centre for Healthy Societies , and China Studies Centre International collaborations with institutions in Hong Kong, UK, and USA His research focuses on digital health evaluation and AI development for medical applications, including: Machine learning for stroke risk prediction through blood pressure variability Fall prevention systems via footstep pattern classification Electronic medication management system implementation Integrative medicine data analytics Health technology evaluation frameworks Recent publications show strong emphasis on AI in radiology , clinical process mining , and healthcare workflow optimization . His work spans both technical algorithm development and organizational implementation challenges. Key affiliations include: University of Sydney (School of Computer Science) Chinese University of Hong Kong (Adjunct Associate Professor) NSW Local Health Districts (Honorary Associate) He has supervised students across Computer Science , Biomedical Engineering , Medicine , and Business disciplines.

Kathleen SienkoView profile

Professor

• Biomechanics
• Medical Device Design
• Rehabilitation Engineering
• +3 more

Kathleen Sienko, Ph.D., is the Arthur F. Thurnau Professor in the Department of Mechanical and Biomedical Engineering at the University of Michigan's College of Engineering. Her research focuses on sensory augmentation technologies, rehabilitation engineering, and global health medical device design, with an emphasis on task-shifting solutions for low-resource settings. She also contributes significantly to engineering education, particularly in contextual design methodologies and stakeholder engagement strategies. Her work integrates biomechanics principles with wearable sensor systems to address challenges in balance disorders, vestibular rehabilitation, and maternal health. Notable projects include developing a contraceptive implant insertion device for low-income countries and systems for automatic balance evaluation using IMUs. Sienko emphasizes interdisciplinary collaboration, cultural sensitivity in design, and the intentional use of prototypes to engage stakeholders effectively. Key Research Themes: Biomechanics, Medical Device Design, Human Factors, Global Health Engineering Design Philosophy: Contextualized solutions prioritizing user needs, sustainability, and scalability Education Focus: Training students in culturally adaptive design processes through immersive global health projects Her publications span machine learning applications for fetal movement detection, gait analysis frameworks for vestibular disorders, and pedagogical strategies for engineering design education. Sienko's work bridges clinical needs with engineering innovation, often involving collaborations across medical, mechanical, and biomedical disciplines.

• Seismology
• Geophysics
• Earthquake Hazard Assessment
• +3 more

Ms Amy Woodward is a Research Postgraduate (mapped to Researcher academic rank) at the Department of Earth Science & Engineering within Imperial College London 's Faculty of Engineering . Her work focuses on seismology, particularly slow slip events and seismic hazards at the Hikurangi margin in Aotearoa New Zealand, with additional contributions to seismicity studies in the Main Ethiopian Rift and Abaya geothermal field. Recent research includes the creation of a high-density seismic network catalog for the Hikurangi Margin and analysis of crustal structure in Lake Abaya. Publications span topics from subduction zones to rift basin geodynamics, with presentations at AGU Fall Meetings in 2023 and 2020. Supervised by Dr Ian Bastow, Dr Rebecca Bell, and Dr Bill Fry, she is funded by the NERC Science and Solutions for a Changing Planet Doctoral Training Partnership (SSCP DTP) and GNS Science.

William ArthurView profile

Lecturer

• Computer Security
• Computer Architecture
• Compilers
• +5 more

William Arthur is a Lecturer in the Department of Electrical Engineering and Computer Science at the University of Michigan. He currently teaches EECS 183: Elementary Programming Concepts , with teaching experience dating back to Fall 2014. His office hours are held remotely during the Winter semester, and he has also served as visiting faculty at Addis Ababa Institute of Technology in Ethiopia for the course ECEG 66514. His research interests span computer security , computer architecture , compilers , system security , network security , hardware/software co-design , software engineering and test , and engineering education . Publications focus on control-flow integrity, security bug detection, and network attack modeling, primarily using C++ as a teaching language in EECS 183. Key publications address Hardware-based control-data isolation (2016) Control-flow management in security contexts (2015) Scalable security profiling tools (2013) DDOS attack analysis in phase space (2011) These works emphasize secure computing frameworks and vulnerability mitigation strategies. Contact: warthur@umich.edu

• Ophthalmology
• Glaucoma Research
• Epidemiology
• +3 more

Anne L. Coleman, MD, PhD, serves as a Clinical Professor in the Department of Surgery at Charles R. Drew University of Medicine and Science. Her extensive research portfolio focuses on ophthalmology, particularly glaucoma epidemiology, vision impairment in aging populations, and health disparities. Her research interests span Ophthalmology , Glaucoma Progression , Vision Epidemiology , Public Health Surveillance , and Health Disparities . She employs population-based studies, Medicare claims analysis, and advanced imaging techniques to investigate structural-functional relationships in glaucoma, social determinants of eye disease, and comorbidities associated with vision impairment. Her work frequently addresses racial/ethnic disparities in glaucoma diagnosis and treatment. Recent publications (2024-2025) demonstrate her leadership in analyzing large datasets (All of Us, IRIS Registry, Medicare claims) to study glaucoma progression patterns, associations with systemic conditions (dementia, hip fractures), and social determinants of keratoconus. Her methodological approaches integrate optical coherence tomography, Bayesian hierarchical modeling, and epidemiological frameworks. As Principal Investigator on multiple NIH-funded studies including the Ocular Hypertension Treatment Study (OHTS), she has significantly contributed to understanding glaucoma incidence and treatment outcomes. Her work bridges clinical ophthalmology with public health, emphasizing equitable access to eye care and evidence-based surveillance systems for vision impairment.

Yan LuView profile

Assistant Professor

• Machine Learning
• Deep Learning
• Artificial Intelligence
• +5 more

Dr. Yan Lu is an Assistant Professor of Computer Science at Christopher Newport University (CNU), part of the School of Engineering and Computing. She joined CNU in Fall 2023 and holds a Ph.D. in Computational Modeling and Simulation from Old Dominion University (2020), an M.Sc. in Computer Science from Virginia Commonwealth University (2009), an M.Sc. in Circuit and System from the Chinese Academy of Sciences (2007), and a B.A. in Computer Science from Beijing Jiaotong University (2004). Her research focuses on Deep Learning and Machine Learning applications in Remote Sensing Image Processing, Trustworthy AI, and AI robustness. Notable projects include refugee tent extraction using satellite imagery (featured in IEEE Spectrum ) and malware classification via deep residual networks. She has held roles as Research Assistant Professor at Old Dominion University’s VMASC and Research Scientist at Virginia Commonwealth Cyber Initiative (VCCI). Dr. Lu’s work has been recognized with awards such as the 2019 Gene Newman Award and the Air Force Research Lab’s VFRP award (2020–present). Her teaching spans Machine Learning, Data Science, and Image Processing. She actively contributes to IEEE and ACM’s SIGSIM.