جست‌وجوی استاد و پژوهشگر

• Intensive Care
• Critical Care Medicine
• Artificial Intelligence in Healthcare
• +۵ مورد دیگر

Dr. Michel van Genderen serves as a Researcher in the Department of Intensive Care at Erasmus MC's Erasmus School of Medicine, Rotterdam. His work focuses on advancing critical care through innovative research in mechanical ventilation protocols, AI integration, and sustainable ICU practices. With 69 research outputs including 50 articles and 7 reviews, he actively contributes to European critical care initiatives. His research spans Intensive Care Medicine , AI applications in critical care , and environmental sustainability . Key interests include developing standardized data models for ICU networks, optimizing mechanical ventilation strategies, and implementing large language models for clinical decision support. Recent work examines green ICU initiatives from multiple stakeholder perspectives and leverages GPT-4 to improve patient understanding of radiology reports. Analysis of his 15 most recent publications reveals strong emphasis on data standardization for European ICU networks , AI-driven clinical decision tools , and sustainable critical care practices . His work consistently bridges technical innovation with practical clinical implementation, particularly in mechanical ventilation optimization and pandemic response protocols. Dr. van Genderen has supervised at least two graduate students and participates in multi-center collaborations across Europe. His research receives significant attention with news mentions and Mendeley readership. Current projects include the SWITCH study on ventilation strategies and development of the Common Data Model for Intensive Medicine Data Space in Europe. He contributes to critical care innovation through participation in European research networks focused on data interoperability and sustainable healthcare infrastructure. His work on "The green ICU" examines environmental sustainability from healthcare professional, procurement specialist, and regulatory perspectives.

• Critical Care
• Pulmonary Medicine
• Allergy and Immunology
• +۴ مورد دیگر

Dr. Craig M. Lilly is a Professor at UMass Chan Medical School, holding multiple appointments across the Department of Medicine (Pulmonary Medicine Division), Anesthesiology and Perioperative Medicine, Surgery, and Population Health Sciences. He is also affiliated with the Morningside Graduate School of Biomedical Sciences in Immunology and Microbiology Program. Education: BS in Science from University of Oregon; MD from Oregon Health Science University His research focuses on Critical Care and Pulmonary Medicine , with significant contributions to ICU Telemedicine , Point-of-Care Testing , and Medical Device Commercialization . Recent publications highlight applications of Machine Learning in critical care diagnostics and pandemic-related medical technology adoption. Scientific articles demonstrate interdisciplinary engagement in Allergy and Immunology , Public Health , and Biomedical Informatics . While no formal awards are listed, his work spans Clinical Guidelines , Quality Metrics , and Healthcare Policy development.

Saeed Sharifمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Innovative Tele-Health
• Medical Technology
• +۹ مورد دیگر

Dr Saeed Sharif is an Associate Professor in the Computer Science department at the School of Architecture, Computing and Engineering , University of East London . He leads the Intelligent Technologies Research Group and serves as Course Leader for MSc Computer Science programs. With a PhD in artificial intelligence from Brunel University London , his work bridges Artificial Intelligence , Medical Technology , and Smart Infrastructure . His research interests span Medical Image Analysis , Intelligent Diagnosis Systems , Big Data Analysis , and IoT Security . Collaborations with NHS Trusts and global institutions focus on improving healthcare systems through machine learning and biomedical signal processing. 2018-2022: £268,000 KTP project with Innovate UK Multiple Research Internship Schemes at UEL (2017-2021) European Research Centre collaboration (2015) As a technical committee member for conferences like IEEE CIT and a journal Guest Editor , he drives academic discourse. He has supervised numerous PhD students and served on examination panels, while maintaining 53+ publications in venues including IEEE Access , Applied Soft Computing , and Computer Methods and Programs in Biomedicine .

Alireza Esfahaniمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Network Security
• IoT Security
• +۵ مورد دیگر

Dr. Alireza Esfahani is a Senior Lecturer in Cyber Security at the School of Computing and Engineering (SCE) at the University of West London, where he also serves as the Course Leader for the BSc (Hons) Cyber Security and BSc (Hons) Cyber Security with Foundation Year programs. Previously, he held a lecturing position at the University of Greenwich from 2021 to 2023. He earned his PhD in Telecommunications from the University of Porto, Portugal, through the MAP-TELE doctoral program in 2017, followed by postdoctoral research at the Instituto de Telecomunicações in Portugal (2017–2019). Education: PhD in Telecommunications (University of Porto, 2017) Experience: Research Associate at SnT-CritiX (University of Luxembourg), contributing to EU cybersecurity projects SPARTA and CyberSec4Eu Affiliations: European Cyber Security Organisation (ECSO) and IEEE member Research Interests: Dr. Esfahani focuses on cybersecurity in IoT, connected vehicles, intrusion detection, machine learning applications, and semiconductor supply chain security. His work emphasizes secure authentication mechanisms, network coding security, and resilient systems design. Teaching: He teaches courses in BSc and MSc programs, including Cyber Security, Computer Science, and specialized modules in network security and secure communication protocols. Grants & Projects: Instrumental in EU-funded initiatives like SPARTA and CyberSec4Eu, focusing on cybersecurity frameworks and distributed systems. Labs/Teams: Collaborated with SnT-CritiX at the University of Luxembourg, developing cybersecurity solutions for critical infrastructure.

David McCordمشاهده پروفایل

استاد

• Clinical Psychology
• Psychological Assessment
• Suicide Risk Screening
• +۴ مورد دیگر

David M. McCord is a Professor of Clinical Psychology at Western Carolina University, based in the Department of Psychology within the College of Education and Allied Professions. He holds a Ph.D. in Clinical Psychology from the University of Alabama, along with a Master’s and Bachelor’s degree from Western Carolina University and Duke University, respectively. His research focuses on clinical psychological assessment methods, particularly the MMPI-3 and MMPI-2-RF instruments, suicide risk screening, and hierarchical-dimensional models of psychological dysfunction. He has developed tools like the M5-50 Questionnaire for personality assessment and contributed to workshops such as the 2017 SEPA MMPI-2-RF Workshop. His work emphasizes evidence-based practices, tele-assessment during crises, and translational tools for primary medical care. Education: Ph.D., University of Alabama; MA, Western Carolina University; BA, Duke University Key Projects: M5-50 Questionnaire, MMPI-3 validation studies, Multidimensional Behavioral Health Screen Affiliations: American Psychological Association, Western Carolina University Research Interests His research spans clinical assessment methodologies , including psychometric validation of instruments like the MMPI-3 and MMPI-2-RF. He explores suicide risk screening in postpartum and primary care settings, emphasizing algorithmic approaches for rapid identification. His work on personality theory includes studies on the Five-Factor Model and its applications in education and clinical practice. He advocates for integrating psychological assessment into healthcare systems through tools like the Multidimensional Behavioral Health Screen (MBHS). Recent Article Trends His recent publications (2020–2024) highlight advancements in MMPI-3 validation , suicide risk detection algorithms , and tele-assessment protocols . He also addresses critiques of restructuring clinical scales and defends their psychometric utility in forensic and medical settings. Awards and Recognition No formal awards are listed in the provided texts. Advising & Grants No specific grants or advisee information is available. His professional contributions focus on developing assessment tools and training programs. Labs & Teams He collaborates with institutions like the University of Minnesota Press and Kent State University on MMPI-related resources. His work is disseminated through workshops and online repositories like PAWS.WCU.EDU.

• Schizophrenia
• Social Cognition
• Early Psychosis Detection
• +۳ مورد دیگر

Dr. Deepa Purushothaman is a Research Fellow in the Department of Psychiatry at Yale School of Medicine, serving as the Early Detection and Assessment Coordinator (EDAC) for DMHAS Region 5 within the Specialized Treatment for Early Psychosis (STEP) program. She holds an MD in Psychiatry and a Postdoctoral Fellowship in Schizophrenia from NIMHANS, Bangalore. Her clinical focus is on general adult psychiatry, with expertise in schizophrenia spectrum disorders. Her research explores social cognitive deficits in schizophrenia, early psychosis detection, and the neurobiology of mental illness, alongside interests in the history of psychiatry and integrative therapies like yoga and Ayurveda. Education: Postdoctoral Fellowship in Schizophrenia, National Institute of Mental Health and Neurosciences (NIMHANS), 2020 MD in Psychiatry, National Institute of Mental Health and Neurosciences (NIMHANS), 2019 Research Interests: Her work spans social cognition deficits in schizophrenia, early psychosis intervention strategies, and the application of yoga and Ayurveda in mental healthcare. She has published extensively on topics such as tele-yoga efficacy, integrative treatment guidelines for schizophrenia, and the neurobiological underpinnings of delusions. Recent Contributions: Her 2025 study on fNIRS-based social disconnect analysis in psychosis and 2024 meta-analysis on yoga therapy for schizophrenia cognition highlight her focus on innovative diagnostic tools and complementary interventions. She co-developed culturally adapted counseling modules using ancient Indian texts and contributed to global treatment guidelines (INTEGRATE). Awards: Young Investigator Award from Schizophrenia Research Foundation (2018) Advisory & Collaborations: She leads the STEP program's early detection efforts and collaborates with interdisciplinary teams on projects like the 'Integrative Approach for Managing Tardive Dyskinesia.' Her lab engages in translational research bridging neuroimaging, epigenetics, and clinical outcomes. Labs/Teams: Active in the STEP program and associated with the Whisk Cup Streamline initiative, focusing on early psychosis intervention and integrative care models.

Femke van Beekمشاهده پروفایل

استادیار

• Soft Robotics
• Haptic Perception
• Human-Computer Interaction
• +۵ مورد دیگر

Femke van Beek is an Assistant Professor in the Robotics section of the Department of Mechanical Engineering at Eindhoven University of Technology. Her research focuses on integrating soft robotics with haptic perception to develop autonomous robots with tactile sensing capabilities, particularly for agricultural applications within the 4TU Green Sensors project . She employs VR/AR experiments to study human haptic perception and design bio-inspired sensors. Academic Background : PhD in Psychonomics and Cognitive Psychology (Vrije Universiteit Amsterdam), MSc in Sensory Biology and Biomechanics (Wageningen University), and BSc in Biology (Wageningen University). Her research spans soft robotics , haptic feedback , and human-in-the-loop engineering , emphasizing practical sensor design and robotic movement optimization. Recent work includes open-source platforms for real-time control of soft robots and studies on vibrotactile vs. auditory feedback in tele-operation. Scientific Awards : Eurohaptics Society PhD Award (2017)

Hisham Mohammedمشاهده پروفایل

مدرس ارشد

• Evidence-based orthodontics
• Smile analysis
• Artificial intelligence in orthodontics
• +۴ مورد دیگر

Dr. Hisham Mohammed is a Senior Lecturer & Discipline Lead in Orthodontics at the University of Queensland's School of Dentistry. He holds a dental degree from Future University, a Master's in Orthodontics (Distinction) from the University of Dundee, and a PhD from the University of Otago. He is a Specialty Member of the Royal Colleges of Surgeons of England and Glasgow. His research focuses on evidence-based orthodontics, AI applications, smile analysis, and miniscrew implant outcomes. Dr. Mohammed has attracted significant research funding and received the Sir John Walsh Research Award. His work spans clinical trials, systematic reviews, and algorithm development for smile analysis. Education: PhD in Orthodontics, University of Otago (2022) Master of Orthodontics, University of Dundee (Distinction) Dental Degree, Future University His research interests emphasize translating clinical evidence into practice, particularly through AI-driven diagnostics and patient adherence strategies. He has pioneered studies on malocclusion's impact on smile aesthetics and developed algorithms for automated smile detection. Dr. Mohammed's work on tele-orthodontics and sensor technologies addresses modern challenges in patient compliance and remote monitoring. He has published 27+ journal articles, 4 conference papers, and a PhD thesis. His awards include the Sir John Walsh Research Award, recognizing contributions to orthodontic science. Awards: Sir John Walsh Research Award Specialty Membership (Royal Colleges of Surgeons, England/Glasgow) Dr. Mohammed supervises higher degree research students and is actively involved in advancing orthodontic education and clinical practice through interdisciplinary collaborations.

Mohamad Eidمشاهده پروفایل

دانشیار

• Haptics
• Multi-modal Human-Computer Interaction
• Affective Haptics
• +۷ مورد دیگر

Mohamad Eid is an Associate Professor of Electrical and Computer Engineering at New York University Abu Dhabi (NYUAD), with a Global Network Associate Professor appointment at NYU Tandon School of Engineering. He leads the Applied Interactive Multimedia Laboratory (AIMLab), focusing on cutting-edge research in haptics and multimodal interaction. His research interests include haptics, affective haptics, EEG-based neurohaptics, soft haptics, biofeedback technologies, and human-computer interaction. He explores how tactile feedback can enhance virtual and augmented reality, assistive technologies, and medical simulation. His recent publications demonstrate strong activity in IEEE Transactions on Haptics, ACM TOMM, and other top venues, with work spanning vibrotactile alarms, mid-air haptics, emotion communication via touch, and haptic dental simulation. His research integrates engineering, neuroscience, and multimedia to create immersive and affective user experiences. Best Paper Award, ICBAE 2016 Best Paper Award, DS-RT 2008 ACM Multimedia 2009 Grand Challenge Most Entertaining Award Mohamad Eid advises students through capstone projects in computer science and biology and has contributed to educational initiatives such as robotic handwriting assistance for Arabic script. He holds multiple patents in haptic feedback systems and is an active editor for IEEE Transactions on Haptics. His work is supported by grants and has been featured in media outlets like Wired and The National. He leads the Applied Interactive Multimedia Laboratory (AIMLab), a multidisciplinary research group developing innovative haptic and interactive systems for healthcare, education, and entertainment.

• Air Quality Analysis
• Microdata Analysis
• Urban Pollution Modeling
• +۶ مورد دیگر

Yves Rybarczyk serves as Professor of Microdata Analysis at Dalarna University's Department of Data and Information Management. His academic profile spans computer science, environmental science, and healthcare technology applications, reflecting a highly interdisciplinary research approach. Currently teaching User-centered Design (GIK348), Data Warehousing (AIK232), and Bachelor's thesis in Microdata Analysis (GMI2C8), he maintains active engagement in both undergraduate education and research supervision. Professor Rybarczyk's research focuses primarily on air quality analysis, urban pollution modeling, and machine learning applications for environmental monitoring. His work demonstrates particular expertise in analyzing PM2.5 effects on urban environments, biosphere-atmosphere interactions, and the application of digital twin technology in home care settings. His research methodology frequently employs causal analysis, convergent cross mapping, and ensemble deep learning approaches to address complex environmental challenges. Analysis of his recent publication record reveals a strong trend toward interdisciplinary environmental data science, with approximately 60% of his work focusing on air quality and pollution modeling, 25% on healthcare technology applications including tele-rehabilitation systems, and 15% on broader data science applications. His publications appear in high-impact journals across multiple disciplines including environmental science, computer science, and public health, demonstrating his ability to bridge academic domains through data-driven approaches. While specific grant information isn't detailed in the available text, Professor Rybarczyk's collaborative publication pattern suggests involvement in international research projects, particularly with colleagues from South American institutions as evidenced by multiple studies focused on Quito, Ecuador. His research appears to receive support for environmental monitoring initiatives and digital health technology development.

Eric Dionneمشاهده پروفایل

دانشیار

• Educational Assessment
• Medical Education
• Adult Education
• +۶ مورد دیگر

Eric Dionne is an Associate Professor at the Faculty of Education , University of Ottawa, with a joint affiliation as a researcher in the Department of Innovation in Medical Education (DIEM) , Faculty of Medicine. He is also a Senior Researcher at the Institut du savoir Montfort - Recherche since 2014. Education : Ph.D. and M.A. in Measurement and Evaluation from Université de Montréal (2008), Certificate in Administration from Télé-Université (1996), and B.Sc. in Science Teaching from Université du Québec (1994). His research focuses on assessment theory , Rasch modeling , and data collection tools for evaluating educational outcomes in health sciences and continuing education. He emphasizes psychometric validation and simulation-based learning. The articles show his work spans medical education , test theory , and pedagogical methodology . Key trends include formative assessment , data adaptation errors , and technology integration in educational evaluation. Scientific Awards : Senior Researcher, Institut du savoir Montfort - Recherche (2014–present) He teaches graduate courses in program evaluation , data collection instruments , and measurement theory . His collaborative work with CAPSAF and IRHM highlights interdisciplinary research in healthcare education and assessment.

Somayyeh Azimiمشاهده پروفایل

پژوهشگر ارشد

• Oral Health
• Telehealth
• Special Care Dentistry
• +۶ مورد دیگر

Dr. Somayyeh Azimi is an Honorary Research Fellow at the School of Allied Health, University of Western Australia (UWA). She holds a PhD in Oral Cancer from UWA, focusing on head and neck cancer risk factors. Her roles include researcher at North Metropolitan Health Services, TKI, and the Clinical Research Centre at NMHS Mental Health. She has led projects on tele-dental screening in the ORIGINS Project and evaluated dental hospitalizations for children with intellectual disabilities and autism. Education: PhD: Oral Cancer (University of Western Australia) Research Interests: Oral health disparities, telehealth applications in dentistry, mental health accessibility, special care dentistry, and aging populations’ health. Her work addresses global health equity through projects like remote dental screening and oral health plans for acquired brain injury patients. Grants & Projects: Lead Investigator: Tele-screening for tooth decay in early childhood during the pandemic (WA Health Department, 2021) Labs/Teams: Affiliated with the International Research Collaborative - Oral Health and Equity, a global leader in addressing oral health disparities. Collaborates with CSIRO, TKI, and Brightwater Care Group on multidisciplinary projects.

Abdourrahmane ATTOمشاهده پروفایل

استاد

• Deep Learning
• Multi-Fractality
• Stochastic Modeling
• +۴ مورد دیگر

Abdourrahmane ATTO is a Professor at Polytech Annecy-Chambéry, part of Savoie Mont-Blanc University. His research focuses on advanced machine learning techniques, including deep learning theory, stochastic modeling of multi-fractal processes, and time series analysis of images. He specializes in applications such as SAR image processing, environmental monitoring, and geohazard prediction. His work integrates neural networks, wavelet analysis, and explainable AI methods. Research Themes: Deep Learning Theories (Analysis, Explainability) Multi-Fractality and Stochastic Modeling Time Series of Images & Video Analysis Convolutional Neural Networks SAR and InSAR Image Processing Key Contributions: Developed timed-image representations for action recognition in video sequences. Advanced fractional Brownian field models for texture synthesis and analysis. Created the ISSLIDE dataset for landslide detection using machine learning. Pioneered explainable AI methods for hydrological forecasting and SAR image classification. Labs & Affiliations: Active member of LISTIC laboratory, focusing on interdisciplinary research in signal processing and computer science.

• Autonomous Systems
• Robotics
• Computer Vision
• +۳ مورد دیگر

Daniel Duberg is a Researcher and PhD candidate at the Division of Robotics, Perception and Learning (RPL) within the School of Electrical Engineering and Computer Science at Kungliga Tekniska Högskolan (KTH). His research focuses on autonomous exploration and real-time 3D mapping using unmanned aerial vehicles (UAVs), emphasizing onboard processing for indoor environments. He has contributed to frameworks like UFOMap, which address dynamic environments and efficient data structures. His work integrates probabilistic modeling, sensor fusion, and real-time algorithms to enhance UAV navigation and decision-making. Notable projects include dynamic-aware mapping (DUFOMap) and exploration strategies guided by formal methods like Signal Temporal Logic. Duberg teaches engineering courses in robotics and collaborates on open-source tools for autonomous systems. His research trends emphasize scalability, robustness in uncertain conditions, and adaptive planning for long-term autonomy. He has published widely on exploration algorithms, volumetric mapping, and UAV navigation challenges, with applications in both static and dynamic environments. Duberg’s academic contributions span over a decade, with early work on tele-operation safety and recent advancements in semantic mapping and multi-sensor fusion. His research bridges theoretical foundations with practical implementations for deployable robotic systems.

Jarutas Andritschمشاهده پروفایل

مدرس

• Artificial Intelligence
• Healthcare Technology
• Data Science
• +۴ مورد دیگر

Jarutas Andritsch is a Lecturer in Computing at Solent University, affiliated with the Science and Engineering Research Group and Solent Computing and AI. She holds a PhD from the University of Southampton (2014). Her research focuses on leveraging AI and data science for healthcare enhancement, including projects like MSTAC (COVID-19 chest X-ray classification), an AI-driven chest X-ray screening initiative funded by the Global Challenges Research Fund, and tele-rehabilitation systems for osteoarthritis patients. She also explores data analytics in healthcare and education, such as flooding incident monitoring via Twitter data and inclusive programming pedagogy. Education initiatives include enhancing student performance through collaborative learning approaches, inquiry-based methods for non-STEM students, and content co-creation for novice programmers. She serves on a consultancy committee for the Royal College of Radiologists in Thailand, advising on AI procedures. Her work spans AI applications in cybersecurity (e.g., phishing detection via digital twins), healthcare analytics (cardiovascular ICU prediction), and fitness technology (personalized feedback via computer vision). Notable contributions include peer-reviewed publications on AI-driven healthcare solutions and education strategies, reflecting her dual focus on technological innovation and inclusive pedagogical practices. She actively collaborates on interdisciplinary projects, blending machine learning, computer vision, and educational theory to address real-world challenges.