جست‌وجوی استاد و پژوهشگر

• Algorithm development
• Data analytics
• Time-series data analysis
• +۶ مورد دیگر

Emran Ali is a Graduate Researcher (Ph.D. candidate) and Part-Time Lecturer at Deakin University's School of Information Technology within the Faculty of Science, Engineering and Built Environment. He holds concurrent faculty appointments at Hajee Mohammad Danesh Science & Technology University (HSTU) in Bangladesh where he teaches computer science courses while on study leave. His academic journey includes a Master of Science (Research) in Information Technology from Deakin University (2022) and a Bachelor of Science in Computer Science and Engineering from HSTU. Doctor of Philosophy (Ph.D.) in Information Technology, Deakin University (2023–present) Doctor of Philosophy (Ph.D.) in Machine Learning, Coventry University (Cotutelle program, 2023–present) Master of Science (Research) in Information Technology, Deakin University (2020–2022) Bachelor of Science in Computer Science and Engineering, HSTU Bangladesh (2007–2012) Ali's research focuses on algorithm development and applied machine learning in health informatics, specializing in biosignal processing for neurological and sleep disorder detection. His work integrates time-series data analysis with explainable AI techniques to develop clinical decision support systems. Current projects include ML/DL modeling of sleep-stage transitions in aging populations and causal relationship analysis in sleep disorders using EEG data. Analysis of his 10 recent publications reveals strong concentration in biomedical ML applications (60%), particularly EEG-based neurological disorder detection and mental health diagnostics. Secondary focus areas include environmental monitoring systems (20%) and foundational computer science (20%). His work consistently employs ensemble methods and feature optimization techniques across diverse datasets, with increasing emphasis on real-world clinical applicability in recent publications. Deakin University Post-graduate Research Scholarship (DUPRS) through Cotutelle program with Coventry University National Fellowship from Bangladesh Ministry of Science and Technology (2020) Best Presentation Award at Deakin School of IT Conference (2021) AWS AI/ML Scholarships (2023, 2024) Next Generation Tech Booster Scholarship (2024) Ali provides research supervision at HSTU while serving as a Graduate Research Teaching Fellow at Deakin University for Machine Learning and Data Analytics units. His industry collaborations include projects with Monash University, Alfred Health, and AETMOS Australia focused on health informatics applications. Current funding includes AWS-sponsored nanodegrees and Deakin University research scholarships supporting his sleep disorder research. His technical work integrates cloud-based AI/ML platforms (AWS, Azure) with biosignal processing pipelines, utilizing collaborations across Australian healthcare institutions to validate clinical applications. Recent projects emphasize explainability in deep learning models for medical diagnostics, particularly in resource-constrained environments relevant to Bangladesh healthcare contexts.

• eHealth
• mHealth
• Medical Imaging Analysis
• +۴ مورد دیگر

Constantinos S. Pattichis is a Professor of Computer Science and Director of the Biomedical Engineering Research Centre at the University of Cyprus. He also leads the HealthXR Group at CYENS Centre of Excellence and serves as a technical leader on high-impact EU-funded projects, including the EU Digital Covid Certificate Platform and the national eHealth4U initiative. His research focuses on eHealth, mHealth, medical imaging, and AI-driven healthcare solutions. **Education**: Ph.D., Electronic Engineering, University of London (1992) MSc, Neurology, University of Newcastle Upon Tyne (1991) MSc, Biomedical Engineering, University of Texas at Austin (1984) BSc, Electrical Engineering, University of New Brunswick (1983) Technician Engineer, Higher Technical Institute, Cyprus (1979) **Research Interests**: eHealth systems, mHealth interventions using Extended Reality (XR), medical image analysis (MRI, ultrasound), biosignal analysis, and explainable AI for clinical decision support. His work addresses challenges in stroke risk assessment, multiple sclerosis progression, and telemedicine accessibility. **Awards & Roles**: Fellow of IEEE, IET, IAMBE, and EAMBES. He has managed over €20M in EU grants, edited multiple books on mHealth and biomedical imaging, and serves on editorial boards of journals like IEEE Journal of Biomedical and Health Informatics. He has published ~409 peer-reviewed works (150 journals, 259 conferences) with an h-index of 54. **Grants & Projects**: Led projects such as the EU Digital Covid Certificate Platform, eHealth4U (national eHealth ecosystem), and the IPMT Excellence Centre. Active in standardizing cross-border eHealth services via EU CEF programs. **Labs & Teams**: Directs the eHealth Lab at the University of Cyprus and collaborates with CYENS on HealthXR innovations. His work includes developing VR tools for dementia care, teleconsultation apps, and AI-driven diagnostic systems.

Arminda Guerra Lopesمشاهده پروفایل

استاد

• Human-Computer Interaction
• Social Informatics
• Interaction Design
• +۴ مورد دیگر

Arminda Guerra Lopes is a Professor at the Polytechnic Institute of Castelo Branco, Portugal, with 25 years of academic service. She holds a PhD in Human-Computer Interaction from Leeds Metropolitan University (UK) and maintains a research fellowship at the Interactive Technologies Institute (ITI/LARSyS) in Portugal. Her institutional leadership includes roles as School Vice Director and President of scientific/pedagogical boards. Her research focuses on human-centered technology design, with expertise in: Social informatics and collaborative systems Human-Work Interaction Design (HWID) Creativity support tools Quality-of-life technologies AI-human interaction paradigms She maintains active international collaborations across Europe and Asia. Recent publications (2017-2023) demonstrate strong focus on AI interactions, workplace systems, and accessibility solutions, with recurring themes of pilot implementation studies, artistic interfaces, and wellbeing technologies. Her work frequently employs mixed-methods approaches bridging technical development with human behavioral analysis. Dr. Guerra leads research teams exploring affective computing, augmented reality navigation, and game-based learning, with projects involving multisensory installations, gesture recognition systems, and community information platforms.

• Artificial Intelligence
• Machine Learning
• Biomedical Engineering
• +۱ مورد دیگر

Dr. Sahil Sharma is a Research Fellow at the School of Computing, Engineering and Intelligent Systems, Ulster University, Derry~Londonderry campus. His interdisciplinary research bridges artificial intelligence, biomedical engineering, and agricultural science, with significant contributions to medical diagnostics and sustainable agricultural practices through advanced computational techniques. Sharma's primary research domains include artificial intelligence (particularly deep learning and large language models), biomedical engineering (focusing on cardiac biomarker detection and medical data analysis), and agricultural science (specializing in plant biostimulants and sustainable farming). His work demonstrates consistent innovation in applying machine learning to solve real-world problems across healthcare and agriculture, with recent emphasis on explainable AI for medical visualization and anime recommendation systems. Analysis of Sharma's 15 most recent publications (2023-2025) reveals a dominant trend toward AI-driven healthcare solutions, including cardiac troponin I detection assays, XAI-based medical data visualization, and synthetic data generation for diagnostics. Parallel work explores agricultural applications through deep learning-based crop monitoring systems. His research outputs show strong translational impact, with significant citations (h-index 86) and practical implementations referenced in patents, particularly in the biomedical domain where his 2012 agricultural paper accumulated 85 Scopus citations.

• Computer Science
• Machine Learning
• IoT
• +۷ مورد دیگر

Ali Hassan is a researcher affiliated with the National University of Sciences and Technology (NUST), School of Electrical Engineering and Computer Science, Department of Computer and Software Engineering. His work spans multiple domains in computer science, engineering, and applied mathematics, focusing on areas such as machine learning, IoT, energy systems, and medical informatics. His research explores: Reinforcement learning applications for battlefield information systems IoT antenna design and performance evaluation Optimization of second-life battery systems in electric vehicles Transformers for real-time vehicle collision avoidance Image hashing techniques using visual attention models Neural network-based phasor estimation for power grids Biomedical sensor systems for non-invasive health monitoring Mathematical modeling of viral dynamics Recent publications demonstrate his emphasis on interdisciplinary approaches combining AI, signal processing, and sustainability. He has collaborated with institutions across Pakistan, France, Saudi Arabia, and the USA, with a focus on practical implementations in cybersecurity, energy optimization, and healthcare technology.

• Internet of Things
• Assisted Living Environments
• Smart Sensors
• +۱۲ مورد دیگر

Mariana Catela Jacob Rodrigues is an Assistant Professor in the Department of Applied Digital Technologies at Iscte – University Institute of Lisbon and an Associate Researcher at the Institute of Telecommunications – IUL, where she works within the Instrumentation and Measurements Group. She holds a PhD in Information Technologies and Systems from Iscte, completed in 2024, following a Master’s and Bachelor’s degree in Telecommunications and Computer Engineering from the same institution. Her research interests span a multidisciplinary range of topics, including: Internet of Things (IoT) Assisted Living Environments Smart Sensors and Wearable Devices Cardiorespiratory and Physiological Monitoring Environmental and Air Quality Monitoring Artificial Intelligence in Healthcare Mobile Application Development Virtual Reality in Rehabilitation The analysis of her recent publications reveals a strong focus on the integration of sensor technologies and AI for health and environmental applications. Her work frequently involves the development and evaluation of unobtrusive monitoring systems in ambient assisted living contexts, with specific attention to indoor localization, fall detection, and the impact of environmental stimuli—such as lighting and music—on autonomic nervous system responses. Much of her research is published in IEEE conferences and journals related to instrumentation, sensors, and medical measurements. Her scientific achievements include: Best Student Paper Award at the IEEE International Symposium on Medical Measurements and Applications (2022) ISTA Top Talent 2018-2019 (awarded in 2020) Best Student Paper Award at the 2nd International Symposium on Sensing and Instrumentation in IoT Era (2019) Mariana Rodrigues is actively involved in academic service and outreach. She has served on the organizing committees of multiple scientific events, including the International Symposium on Sensing and Instrumentation in IoT Era and several summer schools on Smart Systems for Ambient Assisted Living. She currently holds leadership positions in IEEE, serving as Chair of the IEEE Women in Engineering (WIE) Affinity Group and the IEEE Instrumentation and Measurement Society Chapter at Iscte. She has also contributed to science communication through events like the ISCTE Summer School on “Healthy and Sustainable Environment.”

• Malaria Control
• Public Health
• Tropical Medicine
• +۳ مورد دیگر

Carlos Chaccour is a researcher specializing in global health, particularly focused on malaria control and drug repurposing. His work integrates clinical trials, field epidemiology, and innovative technologies like AI-driven cough monitoring systems. He collaborates on large-scale studies such as BOHEMIA, investigating ivermectin's role in malaria vector control and collateral health benefits. His research spans tropical disease epidemiology, environmental health, and public health policy, emphasizing One Health approaches to combat neglected tropical diseases. Key research areas include: Evaluation of ivermectin's efficacy and safety in malaria and other parasitic infections Development of digital health tools for respiratory disease surveillance Impact assessment of air pollution on respiratory illnesses Health equity in malaria-endemic regions, especially in Mozambique and Venezuela His studies frequently employ randomized controlled trials, cohort designs, and advanced analytical techniques like MALDI-TOF MS for biomarker discovery. He advocates for evidence-based policy changes to address gaps in global health interventions, particularly in resource-limited settings.

Saturnino Luz Filhoمشاهده پروفایل

استاد

• Medical Informatics
• Machine Learning
• Digital Biomarkers
• +۵ مورد دیگر

Professor Saturnino Luz Filho is a Professor of Digital Biomarkers and Precision Medicine at the University of Edinburgh , affiliated with the Centre for Medical Informatics within the College of Medicine and Veterinary Medicine . With a background in computer science (PhD, MSc, BSc), he develops machine learning and signal processing techniques for behavioral analysis in healthcare, particularly focusing on digital biomarkers for neurodegenerative diseases. Current research spans Alzheimer's disease, speech analytics, and global health applications Created the ADReSS Challenge for standardized dementia detection Collaborates with institutions in Taiwan, Norway, and Bulgaria His recent publications emphasize speech-based diagnostics , low-cost health monitoring , and multilingual validation of biomarkers. He supervises PhD students working on cognitive robotics and communication analytics, and leads projects funded by the Sony Research Award Programme and Leverhulme Fund . Professor Luz Filho is also active in open science initiatives , healthcare AI standardization , and community-based health technology deployment. His lab's work on Active Data Representation (ADR) and VOCALDIA models has advanced scalable diagnostics in both high-income and low-income settings.

• Blockchain Technology
• Edge Computing
• Federated Learning
• +۴ مورد دیگر

Pubudu N. Pathirana is a Professor at the University of Melbourne's College of Engineering, specializing in Blockchain Technology, Edge Computing, Federated Learning, and Machine Learning for Healthcare . His work bridges theoretical advancements with practical applications in smart cities, cyber-physical systems, and medical diagnostics. Education : PhD in Electrical Engineering, Monash University His research focuses on privacy-preserving machine learning and blockchain integration with edge networks , demonstrated through collaborations with Dinh C. Nguyen, Minh K. Quan, and Bipasha Kashyap. Key contributions include quantum-enhanced models for acoustic classification and federated learning frameworks for IoT environments. Recent publications (2025) highlight advancements in spatio-temporal traffic modeling , adaptive privacy clipping , and secure client aggregation . Earlier work (2021-2024) explored applications in Covid-19 detection , Friedreich Ataxia severity classification , and entropy-based cerebellar ataxia analysis . He mentors students like Ali Reza Sattarzadeh and Kanishka Ranaweera, with grants supporting projects on blockchain-enhanced federated learning and quantum-inspired edge computing . His lab collaborates with institutions such as Monash University and the Florey Institute of Neuroscience.

Ayman Gh.مشاهده پروفایل

پژوهشگر ارشد

• Bioinformatics
• Computational Biology
• Preference Learning
• +۵ مورد دیگر

Ayman Gh. serves as a Postdoctoral Research Fellow at the Australian National University's Biological Data Science Institute (BDSI) and concurrently as a Visitor Scientist at CSIRO Bioprediction, Agriculture and Food Division, Crops Integrated Analytics. His academic foundation includes a 2022 PhD in Advanced Machine Learning from the University of Technology Sydney (UTS) and prior Biomedical Engineering degrees from Cairo University, Egypt. Education: PhD in Advanced Machine Learning, School of Computer Science, Faculty of Engineering and Information Technology, University of Technology Sydney (UTS), Australia (2022) Master of Biomedical Engineering, Faculty of Engineering, Cairo University, Egypt Bachelor of Biomedical Engineering, Faculty of Engineering, Cairo University, Egypt Research Focus: Gh.'s work centers on neural network applications for BioSignal processing, Bioinformatics, and Preference Learning. His expertise spans computational genomics, brain-computer interfaces, and novel machine learning algorithms, addressing complex challenges in biomedical image processing and neural decoding through deep learning architectures. Publication Analysis: His 2012-2024 publications reveal an evolution from ECoG-based finger movement decoding to advanced image generation techniques. Consistently leveraging neural networks, his research bridges biomedical engineering and computer vision, with increasing emphasis on generative models and robust computational solutions for biological data. Scientific Recognition: No specific awards or fellowships are documented in the provided materials. Mentorship: Registered for research student supervision though no advisees are listed, with no grant funding details disclosed in the available information. Collaborative Infrastructure: Operates within ANU's Biological Data Science Institute while maintaining active collaboration with CSIRO's Bioprediction team in agricultural analytics.

Vaidotas Marozasمشاهده پروفایل

استاد

• Digital Signal Processing
• Machine Learning Algorithms
• Wearable Medical Devices
• +۲ مورد دیگر

Prof. Dr. Vaidotas Marozas is affiliated with the Kaunas University of Technology (KTU) , serving as a Professor in the Faculty of Electrical and Electronics Engineering , Department of Electronic Engineering. He is currently the Director of the Institute of Biomedical Engineering and leads the Biosignal Analytics Laboratory . His research focuses on digital signal processing, machine learning applications, wearable medical devices, and cardiovascular disease monitoring technologies. Institute of Biomedical Engineering - Director Biosignal Analytics Laboratory - Head Projects: SV/115, SV/116, SV3/116 - Chief Researcher He can be contacted at vaidotas.marozas@ktu.lt . Professional profiles: Google Scholar , ORCID , Scopus ID 8319694900, ResearcherID T-4499-2017.

Johannes C. Eichstaedtمشاهده پروفایل

استادیار

• Computational Social Science
• Psychological Text Analysis
• Artificial Intelligence in Mental Health
• +۴ مورد دیگر

Johannes C. Eichstaedt is an Assistant Professor of Psychology at Stanford University and the Shriram Faculty Fellow at the Institute for Human-Centered Artificial Intelligence (HAI). He leads the Computational Psychology and Well-Being Lab, focusing on leveraging large language models (LLMs) and computational methods for mental health applications. His work integrates social media analysis, NLP, and AI ethics to address public health challenges like the opioid crisis and psychological well-being monitoring. Educations: PhD in Psychology (University of Pennsylvania, 2017), MAPP in Positive Psychology (UPenn, 2011), MS in Particle Physics (University of Chicago, 2010), BSc in Physics & Philosophy (King's College London, 2009). Research Interests: Computational social science, psychological text analysis, AI-driven mental health interventions, and the ethical deployment of LLMs. His lab pioneered methods to measure population-level psychological states via platforms like Twitter and Reddit, enabling unobtrusive monitoring of public health trends. Recent work emphasizes safe LLM integration into therapy and policy-making. Awards: Shriram Faculty Fellowship (Stanford HAI). His work has informed policy through spatial-temporal analyses of social disruptions and opioid mortality predictions. The lab’s READI framework provides guidelines for AI mental health deployment. Grants & Advising: No specific grants/advising listed, but his lab actively collaborates with global institutions via the World Well-Being Project consortium. His research bridges computer science, psychology, and public health, emphasizing 'AI for good' applications. Labs & Teams: Directs the Stanford Computational Psychology and Well-Being Lab, co-founded the World Well-Being Project (now a global big data psychology consortium). Active in developing tools like TherapyTrainer (AI-based therapist training) and PsychAdapter (personality-adaptive LLMs).

Ralf Seepoldمشاهده پروفایل

استاد

• Biomedical Engineering
• Biosignal Processing & Analytics
• Sleep Disorders and Sleep Medicine
• +۷ مورد دیگر

Prof. Ralf Seepold is a Professor in the Faculty of Computer Science at Konstanz University of Applied Sciences, leading the Professorship of Ubiquitous Computing. He serves as the contact person for the Automotive and Information Technology degree programs and the newly established Intelligent Mobility Systems program since 2022. His primary affiliations include the Department of Ubiquitous Computing, focusing on interdisciplinary research in healthcare technology and smart systems. Prof. Seepold's research expertise spans biomedical engineering, biosignal processing (ECG, ballistocardiogram), sleep medicine (sleep disorders, sleep apnea detection), telemedicine, and ambient assisted living solutions. His work integrates wearable sensors, machine learning, and IoT technologies to develop non-invasive healthcare systems for home and clinical environments. Notable contributions include: Development of smart sleep monitoring systems using accelerometer-based sensors AI-driven diagnostics for sleep disorders and stress analysis Hybrid energy harvesting systems for medical wearables Conceptual frameworks for E-health platforms and digital CBT-I tools His academic memberships include IEEE Senior Member (Engineering in Medicine and Biology Society), German Society for Sleep Research & Medicine (DGSM), and Smart Home & Living Baden-Württemberg.

• Software Engineering
• Gamification
• Agile Methodologies
• +۵ مورد دیگر

Murat Yilmaz is an Associate Professor at the Department of Computer Engineering , Faculty of Engineering , Gazi University , Turkey. With over 14 years of industrial experience in software development, including roles at Huawei Research Centre and HAVELSAN A.Ş., he bridges academic research with practical software methodologies. Research Focus : Gamification in software engineering, agile transformations, virtual reality (VR) for training, and human-computer interaction. Industrial Collaboration : Partners include Huawei, HAVELSAN A.Ş., Kreatin Studios, and Portakal Technologies. Expertise : Software architecture, empirical research, motivational models, and digital governance in the metaverse. His recent publications explore gamification in sleep health, bias in AI systems, metaverse applications, and microservices decomposition. He employs explainable AI and VR for software process improvement, with a strong emphasis on productivity, fairness, and efficiency in development teams.

Roozbeh Ghaffariمشاهده پروفایل

عضو هیئت علمی

• Soft materials
• Conformal bioelectronics
• Advanced microfluidic systems
• +۴ مورد دیگر

Roozbeh Ghaffari is a Research Associate Professor of Biomedical Engineering at Northwestern University, serving as Director of Translational Research at the Center for Biointegrated Electronics. He holds a PhD from Harvard-MIT’s Health Sciences and Technology program, with prior degrees from MIT. His research focuses on soft bioelectronics, micro/nano-scale systems, and wearable biosensors, particularly for applications in health monitoring and clinical diagnostics. Prof. Ghaffari co-founded MC10 Inc., where he developed groundbreaking wearable technologies like the BioStamp® and My UV PatchTM. His work has been recognized with awards including MIT Technology Review's Top 35 Innovators Under 35 (2013) and the MIT100K Grand Prize (2008). His research interests span conformal bioelectronics, microfluidic systems, and auditory neuroscience, with a focus on translating these innovations into clinical tools. Key achievements include skin-interfaced microfluidic platforms for sweat analysis, wearable systems for real-time health monitoring, and bio-integrated devices for neuromuscular function assessment. His lab emphasizes interdisciplinary collaboration, combining materials science, engineering, and clinical medicine to address unmet healthcare needs. Education: PhD in Biomedical Engineering, Harvard-MIT (2008) MEng in Bio-Electrical Engineering, MIT (2003) B.S. in Electrical Engineering, MIT (2001) Awards: Helen Carr Peake PhD Research Prize (2008) Harvard Business School Social Enterprise Grand Prize (2008) TEDx Gateway Talk (2016) Lab Focus: Biointegrated Electronics Lab at Northwestern, developing wearable systems for disease monitoring and diagnostics.