جست‌وجوی استاد و پژوهشگر

• Ophthalmology
• Retinal Diseases
• Medical Imaging
• +۳ مورد دیگر

Tyra Lange serves as a Casual Academic in the College of Science and Engineering and maintains affiliation with the Medical Device Research Institute. Holding a PhD, she conducts interdisciplinary research at the intersection of ophthalmology and biomedical engineering with particular focus on retinal pathology diagnostics. Her research centers on retinal diseases including detachment and vitreous disorders, utilizing Optical Coherence Tomography combined with computational approaches like graph theory and shape analysis . She develops automated diagnostic systems for peripheral retinal pathologies, bridging engineering innovation with clinical ophthalmology needs. Her work demonstrates consistent application of quantitative imaging analysis to solve diagnostic challenges in eye diseases. Analysis of her publication timeline (2020-2023) reveals progressive refinement of OCT-based diagnostic methodologies, with increasing emphasis on peripheral retinal analysis and machine learning applications. Her research consistently addresses the critical clinical need for early detection of retinal detachment precursors through advanced imaging interpretation. As part of the Medical Device Research Institute, Dr. Lange contributes to interdisciplinary teams developing next-generation ophthalmic diagnostic technologies, with current work focusing on translating computational models into clinically viable tools for retinal pathology assessment.

• Obstetrics
• Gynecology
• Preeclampsia Research
• +۴ مورد دیگر

Anna-Karin Wikström is a Professor of Obstetrics and Gynecology and Senior Physician at the Department of Women's and Children's Health, Uppsala University. She previously served as Professor of Obstetrics and Gynecology at Karolinska Institutet from 2016-2017. Her extensive clinical experience spans over two decades in obstetrics and gynecology, with specialized expertise in high-risk pregnancies. Her educational background includes medical studies at Karolinska Institutet (1985-1991), becoming a specialist in obstetrics and gynecology in 2001, earning her PhD from Uppsala University in 2006, and completing a post-doc at Karolinska Institutet's Clinical Epidemiology Unit (2009-2011). She became an associate professor at Uppsala University in 2011 before advancing to full professor in 2017. Professor Wikström's research primarily focuses on preeclampsia, where she leads major initiatives including IMPACT (a national study on preeclampsia prediction) and UP-MOST (a biobank for preeclampsia research). Her work spans cardiovascular effects of preeclampsia, brain imaging studies in affected women, and register-based epidemiological research. Beyond preeclampsia, her research interests include pregnancy in women with congenital heart disease, myasthenia gravis, and other chronic conditions. Her extensive publication record demonstrates expertise in maternal-fetal medicine with particular emphasis on prediction models for adverse pregnancy outcomes and understanding long-term health implications. Her recent publications reveal a strong focus on neurological consequences of hypertensive disorders in pregnancy, maternal physical activity effects on fetal outcomes, and innovative screening approaches for pregnancy complications. The research frequently utilizes large Swedish population-based registers, contributing significantly to evidence-based obstetric care in the Nordic region. Professor Wikström actively contributes to clinical research that directly impacts patient care, particularly in preeclampsia screening and prevention. Her work often takes a Nordic perspective, informing regional guidelines and practices. She collaborates extensively across disciplines including cardiology, neurology, and epidemiology to advance understanding of pregnancy complications and their long-term consequences.

• Audio-Visual Speech Recognition
• Machine Learning
• Signal Processing
• +۹ مورد دیگر

Satoru Hayamizu is a Professor at Waseda University 's Green Computing Systems Research Organization , with a career spanning over four decades. His research focuses on Audio-Visual Speech Recognition , Machine Learning , and Medical Informatics , as evidenced by 126 publications and an h-index of 18. Education: The University of Tokyo (PhD in Mechanical Engineering) Prior affiliations: Gifu University (2002-), National Institute of Advanced Industrial Science and Technology (1981-2001) Research Interests include: Audio-visual speech recognition with sparse representation and DNN techniques Development of low-cost CNN-based road condition detection systems Swallowing function evaluation using acoustic and image processing Human behavior analysis for service operation estimation Research Trends reveal consistent work in multimodal signal processing (2006-2024), deep learning applications (2012-2024), and medical diagnostic systems (2006-2017). His publications show integration of sparsity modeling (2012-2021), industrial equipment diagnostics (2018-2021), and social impact technologies (2013-2024). Research Projects funded by Japan Society for the Promotion of Science include: Swallowing timing estimation (2018-2021) Multimodal silent speech recognition (2016-2020) ICT-based piano learning systems (2013-2016) Keyword display mechanisms (2010-2012) Labs & Collaborations include partnerships with Satoshi Tamura (co-author on 12+ papers), Hidekazu Fukai , and Chiyomi Miyajima . His work bridges academic research and industrial applications , particularly in manufacturing AI (2024 book) and Timor-Leste infrastructure monitoring.

Mian M. Hamayunمشاهده پروفایل

دانشیار

• Computer Science
• Transaction Level Modeling (TLM)
• MPSoC Simulation
• +۱۵ مورد دیگر

Mian M. Hamayun is an Associate Professor of Computer Science and Head of Subject Group at the University of Birmingham Dubai campus, part of the College of Engineering and Physical Sciences. He holds a PhD in System Modelling, Simulation & Virtualization from the University of Grenoble Alpes, France, and has academic qualifications from Joseph Fourier University and COMSATS Institute of Information Technology, Pakistan. PhD in System Modelling, Simulation & Virtualization, University of Grenoble Alpes, 2013 MS in Informatics (Parallel & Distributed Systems), Joseph Fourier University, 2009 MSE in Software Engineering (Gold Medalist), COMSATS, 2005 PGCHE, University of Birmingham, 2021 FHEA and SFHEA, University of Birmingham (2021, 2024) His research spans Transaction Level Modeling (TLM) , MPSoC simulation , cloud computing , virtualization , Internet of Things/Vehicles , edge AI , and TinyML . He focuses on performance estimation, binary translation, and system-level simulation for embedded and distributed systems. The recent publications reflect a strong trend in IoT and vehicular networks , secure telemedicine , cloud orchestration , and embedded system simulation . His work integrates virtualization with security, real-time constraints, and machine learning on edge devices. Senior Fellow of the Higher Education Academy (SFHEA), 2024 Fellow of the Higher Education Academy (FHEA), 2021 Dr. Hamayun has supervised multiple research students and contributed to projects involving fatigue detection, person re-identification, retinal image analysis, and secure surgery frameworks. He has taught core computer science courses including Operating Systems, Networks, Data Structures, Algorithms, and Functional Programming at both undergraduate and postgraduate levels. His prior roles include Assistant Professor at NUST SEECS, R&D Engineer in France, and Lecturer at IUT1. He leads research in virtual prototyping and edge intelligence at the Dubai campus, contributing to smart city and cognitive systems initiatives. His lab work involves hybrid simulation environments, secure automotive platforms, and distributed IoT systems.

• Cybersecurity
• Internet of Things (IoT)
• Artificial Intelligence (AI)
• +۱۲ مورد دیگر

Jawad Ahmad is a Lecturer in the School of Computing, Engineering and the Built Environment at Edinburgh Napier University . His work is closely associated with the Centre for Cybersecurity, IoT and Cyberphysical Systems and the Centre for Distributed Computing, Networking and Security , where he contributes to cutting-edge research in secure and intelligent systems. His research interests are centered on cybersecurity , artificial intelligence , and Internet of Things (IoT) technologies. He focuses on developing advanced intrusion detection systems, privacy-preserving frameworks using federated learning and homomorphic encryption, and secure data transmission mechanisms leveraging chaos-based and quantum-inspired encryption. His interdisciplinary work extends to healthcare, smart agriculture, and environmental monitoring, demonstrating the broad applicability of his research. The analysis of his recent publications reveals a strong trend toward AI-driven security solutions, particularly using deep learning models like transformers and attention mechanisms for network intrusion detection. He also explores the integration of machine learning with blockchain and distributed ledgers for trusted threat intelligence sharing. His work consistently emphasizes real-world deployment, performance optimization, and resilience against cyber threats in industrial and healthcare settings. Funded Research Projects: Data Sharing in Highly Secure Environments (Innovate UK, £273,181) PhD Studentship on Homomorphic Encryption (6G Health Institute GmbH, £35,082) TrustShare: Privacy-Preserving Threat Intelligence Sharing (Innovate UK, £31,386) Cyber Hunt: Automated Cyberthreat Hunting (Norway Research Council, £37,500) AI Dashboard for COVID-19 Sentiment Analysis (Chief Scientists Office, £135,104) Dr Ahmad actively supervises postgraduate research, currently serving as Director of Studies for Hisham Ali and as second supervisor for other PhD candidates. He is involved in multiple collaborative research teams focusing on cybersecurity, AI, and IoT, often working with Prof Bill Buchanan and other leading researchers in the field. His research is published in high-impact journals such as IEEE Access , Frontiers in Computational Neuroscience , and Sensors , and presented at international conferences.

Furat Al-Obaidyمشاهده پروفایل

مدرس

• Machine Learning
• Intelligent Systems
• VLSI Circuits
• +۷ مورد دیگر

Furat Al-Obaidy is a Lecturer in the Department of Electrical and Computer Engineering at the University of Michigan-Dearborn's College of Engineering and Computer Science. His expertise spans machine learning, intelligent systems, VLSI circuits, multi-core systems, FPGA architecture, and deep learning applications. PhD in Electrical & Computer Engineering from Ryerson University (2021) MSc in Electrical & Computer Engineering from Ryerson University (2016) MSc in Control & Instrumentation Engineering from University of Technology, Baghdad (1999) BSc in Control & Systems Engineering from University of Technology, Baghdad (1996) His research focuses on power-aware computing systems, thermal imaging for IC testing, hybrid cache architectures, and AI-driven network optimization. He has published extensively on topics including GPGPU power management, 3D NoC routing, and wireless sensor networks. His recent publications highlight applications of neural networks in cache optimization, FPGA architecture, and thermal imaging for hardware diagnostics. Earlier work includes control system simulations for wind turbines and power factor analysis in electrical circuits. Ryerson Graduate Development Award (2021) Ontario Graduate Scholarship Award (OGS) (2020) Ryerson Graduate Fellowship (2018) Graduate Research Excellence Award (2017) Queen Elizabeth II Graduate Scholarship in Science and Technology (2017)

Aamir Younis Rajaمشاهده پروفایل

استادیار

• Medical Physics
• Radiation Physics
• Medical Imaging Physics
• +۸ مورد دیگر

Dr. Aamir Younis Raja is an Assistant Professor in the Physics Department at Khalifa University, UAE, where he co-founded the Medical Physics wing and co-developed the accredited M.Sc program in medical physics. He has held academic roles including Senior Research Fellow at the University of Otago, Visiting Research Fellow at the University of Canterbury, and Visiting Academic Teaching Staff at ARA Institute of Canterbury. His research focuses on radiation physics , medical imaging physics , and spectral photon-counting CT applications in bone/cartilage health , metal implant characterization , cancer imaging , atherosclerosis , and arthritis . Education: PhD in Medical Physics (University of Canterbury, 2013), M.Sc in Applied Physics (UET Pakistan, 2006), B.Sc in Physics & Mathematics (University of the Punjab, 2004) Dr. Raja’s work combines nanoparticle technology with low-dose multi-energy CT to identify non-toxic contrast agents, develops machine learning-based radiation monitoring tools , and pioneers AI-driven artefact reduction in CT imaging. His projects include collaborations with international institutions on material decomposition algorithms and biomedical applications of spectral CT. Notable scientific recognition includes being a Fellow of the Union for International Cancer Control and securing the Khalifa University Faculty Startup Grant . He has supervised over 20 thesis students across University of Otago, University of Canterbury, and Khalifa University, including PhD candidates working on material reconstruction software , parametric color imaging , and machine learning for CT artefact reduction .

Ahalya Ravendranمشاهده پروفایل

پژوهشگر ارشد

• Computer Vision
• Artificial Intelligence
• Robotics
• +۳ مورد دیگر

Dr. Ahalya Ravendran is a Research Fellow at Data61 , Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia. Her work focuses on advancing computer vision , artificial intelligence , and distributed sensing for robotics, particularly in light-constrained environments. She previously held a postdoctoral position at the University of Sydney in collaboration with SCION, a New Zealand Crown Research Institute. PhD in Engineering and Information Technology (2023), University of Sydney Master's (Thailand), Bachelor's in Mechatronics Engineering (Sri Lanka) Her research spans robotic vision , 3D reconstruction , and burst imaging techniques. Recent publications highlight applications in low-light navigation , deep learning domain adaptation , and AI for forestry innovations . Scientific accolades include: IEEE Young Professional Fellowship (2023) Career Advancement Award (University of Sydney, 2023) Engineering and Information Technologies Research Scholarship (2019-2023) Dr. Ravendran actively advocates for women in technology as a WomenTechMaker Ambassador . Her interdisciplinary approach connects robotics , climate innovations , and sustainable technology .

• Artificial Intelligence
• Machine Learning
• Bayesian Statistics
• +۶ مورد دیگر

Hugo Lewi Hammer er professor ved Oslo Metropolitan University, tilhørende Faculty of Technology, Art and Design og Department of Information Technology – Mathematical Modeling . Hans forskning fokuserer på forbedring av pålitelighet og transparens i maskinlæring, forsterkende læring og dyb læringsmodeller gjennom metodikk innen modelltolkning, usikkerhetskvantifisering, robust statistikk og kausal inferens. Hans nylige arbeid inkluderer: AI-drevet optimering i assistert reproduksjonsteknologi (embryoutvalg og sædcelleanalyse) Medisinsk bildebehandling (polypdeteksjon, meibomkertutgang) Neural nettverkstolkning og usikkerhetsmodellering i EEG-analyse Biomekanisk prediksjon av muskelutmatting Hans publikasjoner viser mangfoldige anvendelser av AI i medisin og teknologi, med spesialvekt på: Explainable AI (XAI) i diagnostikk og behandling Usikkerhetskvantifisering i dyb læring Automatisering av medisinske prosedyrer (ICSI, embryoanalyse) Stokastisk simulering og kausal inferens Hammer er engasjert i forskningsgruppene Applied Artificial Intelligence og Mathematical Modeling og har publisert over 130 vitenskapelige artikler og 7 forskningsrapporter.

Patrizia Saviمشاهده پروفایل

دانشیار

• GNSS Reflectometry
• Microwave Characterization of Materials
• Graphene Nanoplatelets
• +۳ مورد دیگر

Patrizia Savi is a Tenured Associate Professor at the Polytechnic University of Turin within the Department of Electronics and Telecommunications. She actively participates in the Power Electronics Innovation Center (PEIC) and serves as a Senior Member of IEEE and the International Union of Radio Science . Teaching: She has been the Titolare del corso for 'Campi Elettromagnetici' (Electromagnetic Fields) since 2019-2021 at the Polytechnic University of Turin. Key Collaborations: Works with researchers across Italy and international institutions on projects involving GNSS-R for environmental monitoring. Research Interests: Her work focuses on GNSS Reflectometry for soil moisture retrieval, carbon-based composites (graphene, biochar, nanotubes) for microwave applications, and graphene tunable devices including biosensors. She also explores electromagnetic shielding using sustainable materials. Recent Publication Trends: Recent work emphasizes machine learning integration with GNSS-R data, biochar composite shielding in construction materials, and graphene-based biosensors for glucose and HRP detection. Key applications span climate action , environmental monitoring , and medical diagnostics . Scientific Awards: IEEE Fellow (2016-) IEEE Senior Member (2016-) International Union of Radio Science Senior Member (2024-) Advising: Supervises PhD students Simone Gaetano Ballaera and Fabio Peinetti , focusing on graphene sensors and tunable devices.

• Trauma Surgery
• Acute Care Surgery
• Surgical Critical Care
• +۴ مورد دیگر

Jennifer Cone serves as Associate Professor in the Department of Surgery-Trauma and Acute Care at the University of Chicago. Her clinical practice focuses on trauma surgery, acute care, and critical care with additional expertise in general surgical procedures. She maintains active roles in surgical education, international training initiatives, and trauma center operations at UChicago Trauma Center. Education and Training: BA in Biology, The Johns Hopkins University (2003) MHS in Biochemistry and Molecular Biology, Johns Hopkins Bloomberg School of Public Health (2006) MD, Tulane University School of Medicine (2011) General Surgery Residency, Tulane University (2016) Trauma/Surgical Critical Care Fellowship, Los Angeles County/University of Southern California (2017) Dr. Cone's research centers on trauma outcomes with specialized focus on firearm violence prevention, pediatric injury patterns, and trauma system optimization. Her work integrates machine learning for community violence prediction, obesity impacts on trauma outcomes, and hepatic trauma management. Recent publications demonstrate strong emphasis on translational research connecting clinical practice with public health interventions, particularly through the Firearm Violence Vulnerability Index project and multi-institutional hepatic trauma studies. Her international work includes advanced trauma life support training in Cambodia and Myanmar. Dr. Cone actively contributes to surgical education through the Division of Trauma & Acute Care Surgery, mentoring residents and fellows in trauma resuscitation techniques. Her scholarly output shows consistent growth with 15 publications since 2017, including high-impact work in the Journal of Trauma and Acute Care Surgery and Journal of the American College of Surgeons . She collaborates extensively with trauma networks including the Multi-Institutional Trial Liver Study Group and UChicago's Military-Civilian Trauma Team Training Site. Her clinical work supports the UChicago Trauma Center's community violence recovery programs, emphasizing patient-centered care and evidence-based surgical interventions. Current projects focus on optimizing trauma scoring systems and developing machine learning tools for community violence risk assessment.

Robert Hsuمشاهده پروفایل

استاد

• Parallel and Distributed Computing
• Cloud Computing
• Big Data Analytics
• +۴ مورد دیگر

Robert Hsu is Chair Professor and Dean of the College of Information and Electrical Engineering at Asia University, Taiwan, and holds concurrent appointments as Professor at National Chung Cheng University. He serves as President of the Taiwan Association of Cloud Computing and Research Consultant at China Medical University Hospital. His research spans parallel and distributed computing , cloud and edge systems , AI , and medical applications , with over 350 publications in top venues like IEEE TPDS, IEEE TSC, and ACM TOMM. Editor-in-Chief of International Journal of Grid and High Performance Computing Founding Editor-in-Chief of International Journal of Big Data Intelligence Advisory roles in 10+ journals including IEEE Transactions on Cloud Computing His research focuses on cloud-edge collaboration , AI for medical imaging , IoT security , and big data analytics . Key projects include federated learning frameworks for multi-institutional healthcare, optimization techniques for UAV-assisted MEC, and blockchain-based security solutions. His 15 most recent articles highlight advancements in malware detection, resource orchestration in edge environments, and lightweight AI models for retail and rural applications. Scientific accolades include: Stanford University's World's Top 2% Scientists (2020-2023) Best Paper Awards at IEEE ICEIB 2023 and SysCom 2021 Over 25 grants from Ministry of Science and Technology and Ministry of Education Leadership roles as IEEE TCCLD Chair and Steering Committee member He has supervised 30+ PhD/Master's students , including Shih-Chang Chen (2010), Tai-Lung Chen (2010), and Nithin Melala Eshwarappa (2020). His laboratory focuses on edge computing , cloud systems , and AI-driven solutions for healthcare and urban infrastructure.

• Pathology
• Medical Imaging
• Machine Learning
• +۷ مورد دیگر

Bri Jackson is a Lecturer in the Department of Foreign Language at Virginia Commonwealth University. While his formal academic role is in language education, his research focuses on advanced computational methods in pathology, including machine learning applications for cancer diagnosis, virtual immunohistochemistry, and digital pathology tools. His work spans histopathological analysis, immuno-oncology, and biomedical imaging. Jackson's research has led to the development of innovative algorithms for virtual diagnostic companion tools, foundation models for whole slide image analysis, and benchmarks for cervical cytology classification. His publications emphasize precision oncology, including biomarker multiplexing, molecular response prediction, and AI-driven histopathological interpretation. Key areas include non-small cell lung cancer, esophageal adenocarcinoma, and splenic involvement in pancreatic cancer prognosis. He has also explored educational challenges in pathology residency programs during the pandemic, viral epidemiology, and rare congenital disorders involving multiple organ systems. Jackson's work bridges computational biology with clinical diagnostics, though no scientific awards or student advisement details are mentioned in the available data.

• Computer Vision
• Pattern Recognition
• Machine Learning
• +۷ مورد دیگر

Prof. Dr.-Ing. Joachim Denzler is a Professor leading the Chair for Digital Image Processing (Lehrstuhl für Digitale Bildverarbeitung) at Friedrich-Schiller-Universität Jena. His research spans computer vision, machine learning, medical imaging, and remote sensing applications across diverse domains including biomedical analysis, environmental monitoring, and facial recognition systems. His research interests focus on explainable AI, causal discovery, physics-informed neural networks, and bias mitigation in deep learning models. He has made significant contributions to fine-grained classification, concept activation vectors, and privacy-preserving techniques in facial recognition. His work often bridges theoretical computer vision with practical applications in medical diagnostics, environmental science, and infrastructure monitoring. His recent publications demonstrate a strong trend toward causal discovery methods, physics-informed neural networks, and addressing bias in machine learning systems. His work spans both theoretical advancements in model interpretability and practical applications in medical imaging, environmental monitoring, and infrastructure safety. The interdisciplinary nature of his research is evident from collaborations with ecologists, neuroscientists, and civil engineers. Best Paper Award at International Conference on Pattern Recognition (ICPR) 2024 Prof. Denzler actively mentors numerous PhD students and postdoctoral researchers, with frequent co-authors including Maha Shadaydeh, Niklas Penzel, Gideon Stein, and Tim Büchner appearing as first authors on significant publications. His laboratory has secured research funding across multiple domains including medical imaging, environmental monitoring, and AI safety. His work on CausalRivers represents a major contribution to benchmarking causal discovery methods with real-world time series data. The Chair for Digital Image Processing maintains strong industry and clinical partnerships, particularly in medical imaging applications for facial palsy analysis and neonatal care. Prof. Denzler's team has developed novel techniques for dam deformation monitoring using remote sensing data and created advanced methods for analyzing plant diversity effects on ecosystem functioning.

Anaïs Rameauمشاهده پروفایل

دانشیار

• Voice Disorders
• Swallowing Disorders (Dysphagia)
• Artificial Intelligence in Medicine
• +۵ مورد دیگر

Anaïs Rameau, MD MPhil is an attending laryngologist and Associate Professor of Otolaryngology at Weill Cornell Medical College. She serves as the Chief of Dysphagia at the Sean Parker Institute for the Voice and founded the Laryngology Innovation Lab , focusing on transdisciplinary collaborations with engineers and social scientists. Her work bridges clinical expertise in Swallowing disorders Voice restoration Airway rehabilitation Artificial intelligence diagnostics Education: M.Phil., Cambridge University (2017) M.D., McGill University (2010) M.Sc., London School of Economics (2005) B.A., Cornell University (2004) M.S., Weill Cornell Medical College (2022) Research focus: Outcomes studies for dysphagia interventions, AI-driven diagnostic tools, and preventative measures for aspiration in dementia patients. She leads NIH-funded projects including Bridge2AI-Voice consortium Mobile app for gender-affirming voice training Low-cost endoscopy simulators Scientific contributions: First otolaryngology recipient of Paul B. Beeson Award Co-developed AI frameworks for vocal fold pathology classification Advocated for improved telehealth equity in laryngology Authored consensus statements on high-resolution manometry Developed open-source medical device protocols Pioneered cough airflow analysis post-injection laryngoplasty Global impact: Maintains active collaboration with the University of Zimbabwe's Otolaryngology Department while advancing equitable AI development practices.