جست‌وجوی استاد و پژوهشگر

Andrew Cathersمشاهده پروفایل

دانشیار

• Emergency Medicine
• Critical Care Transport
• Airway Management
• +۳ مورد دیگر

Andrew Cathers, MD, DRTM, is an Associate Professor at the University of Wisconsin–Madison School of Medicine and Public Health, Department of Emergency Medicine. He serves as Medical Director for UW Health Med Flight, the only air medicine program in the upper Midwest routinely deploying physicians on board. Dr. Cathers specializes in critical care transport, airway management, and resuscitation of critically ill patients. Undergraduate: Providence College Medical School: University of Connecticut School of Medicine Residency: University of Massachusetts Medical School Emergency Medicine Fellowship: UW Health Med Flight DRTM: Royal College of Surgeons of Edinburgh Dr. Cathers' research focuses on quality improvement in prehospital care, simulation training for medical professionals, and advanced rapid-response systems for critically ill patients. His clinical interests include critical care transport logistics, airway management, and resuscitation techniques during transport. He is a Fellow of the Air Medical Physician Association (FAMPA) and the Academy of Emergency Medical Services (FAEMS). Dr. Cathers has authored 15 recent articles spanning 2024-2025, covering topics such as ECMO transport protocols, simulation-based training for airway management, and quality improvement metrics in prehospital care. His work emphasizes aeromedical challenges, trauma resuscitation, and ultrasound applications in emergency settings. UW Health Physician Leadership Development Program Graduate (2024) Medical Director of the Year, Air Medical Physician Association (2023) Faculty, UK Anesthesia Trauma and Critical Care Course Examiner, DRTM Program, Royal College of Surgeons of Edinburgh

Hend Alkittawiمشاهده پروفایل

مدرس

• Computer Vision
• Image Processing
• Machine Learning
• +۱ مورد دیگر

Hend Alkittawi is a Lecturer in Computer Science at the University of Texas at San Antonio's College of Sciences. She specializes in teaching computer vision, image processing, machine learning, and precision agriculture. Her academic credentials include an M.S. in Computer Science from Texas A&M Corpus Christi and a B.S. in Electrical Engineering from the University of Jordan. Research interests span computer vision applications in precision agriculture and healthcare monitoring, with publications focusing on UAV-based crop analysis and AI-driven fall detection systems for elderly care. No awards, grants, or student mentorship details are documented. Her work demonstrates consistent application of machine learning to solve agricultural and healthcare challenges.

Peyman Najafiradمشاهده پروفایل

دانشیار

• Artificial Intelligence
• AI Security
• Machine Learning
• +۳ مورد دیگر

Peyman Najafirad is an Associate Professor in the Department of Computer Science at the University of Texas at San Antonio (UTSA), part of the College of Sciences. His academic journey includes a Ph.D. and M.S. in Electrical and Computer Engineering and Computer Science from UTSA, alongside an M.S. in Computer Engineering and Artificial Intelligence from Iran's Polytechnic, and a B.S. in Computer Science from Sharif University of Technology. His research focuses on AI security, knowledge representation, probabilistic decision-making, and reinforcement learning. Notable contributions include work on adversarial machine learning, LLM-driven cybersecurity solutions, and multimodal AI systems for remote sensing and medical imaging. Najafirad's publications address challenges in secure code generation, AI fairness, and real-time decision-making frameworks for IoT systems. His work bridges theoretical advancements with practical applications, such as vulnerability analysis in software systems, automated defense mechanisms, and explainable AI for healthcare and disaster response. Current research trends highlight innovations in AI safety, ethical algorithm design, and cross-disciplinary solutions for complex societal challenges. While no awards or grants are explicitly listed, his prolific publication record reflects sustained engagement with cutting-edge topics in computer science. His advising role and academic leadership contribute to fostering the next generation of researchers in interdisciplinary AI applications.

Alexandre Mayerمشاهده پروفایل

استاد

• Genetic Algorithms
• High-Performance Computing
• Optical Engineering
• +۷ مورد دیگر

Prof. Alexandre Mayer is a faculty member at the University of Namur, affiliated with the Department of Physics. His research focuses on interdisciplinary topics such as genetic algorithms, quantum mechanics, and optical engineering. He leads major projects like PHOENIX (2024–2029) and Bessel-CNNs (2023–2024), advancing machine learning and materials science. He has been recognized with the Quantum Project Stipend (2000) and Fenia Berz Award (2003). His work contributes to UN Sustainable Development Goals via photovoltaic innovations and materials optimization. Education: Doctor of Sciences (1998), DEA in Physics and Material Chemistry (1996), Master in Physics (1995). Research Interests: Mayer’s expertise spans computational intelligence, high-performance computing, and nanotechnology. Recent efforts include optimizing nanopyramidal absorbers and developing 2D quaternion convolutions for 3D image processing. His work intersects physics, computer science, and engineering, with applications in cosmology and historical document analysis. Grants & Activities: Principal Investigator of €5M+ projects, including PNV+ (2016–2020) and LED (2015–2019), focusing on photovoltaics and nanostructured devices. Active in conferences like SPIE Photonics Europe (2024) and workshops on quantum technologies. Labs & Affiliations: Namur Institute of Structured Matter (NISM) and Namur Institute for Complex Systems (naXys), fostering interdisciplinary research in materials science and computational physics.

John Mageeمشاهده پروفایل

دانشیار

• Computer Vision
• Human-Computer Interaction
• Assistive Technology
• +۲ مورد دیگر

John Magee is Associate Professor of Computer Science at Clark University and serves as Provost and Vice President of Academic Affairs. He holds a Ph.D. from Boston University with research focusing on computer vision, human-computer interaction, and assistive technologies that empower individuals with disabilities. His publications demonstrate strong focus on accessibility innovations, educational technologies, and computer vision applications. Recent work (2022-2024) includes affect-aware educational systems, accessibility tools like Camera Mouse, and security applications of computer vision. His research consistently addresses real-world challenges in disability access and learning technologies. Dr. Magee's work includes developing adaptive interfaces that respond to users' physical abilities and cognitive states, particularly for individuals with profound disabilities. His research extends to interdisciplinary applications combining computer vision with education, security, and healthcare domains.

Swapan K. Gayenمشاهده پروفایل

استاد

• Biomedical Imaging
• Optical Tomography
• Laser Physics
• +۳ مورد دیگر

Swapan K. Gayen is a Professor in the Department of Physics at City College of New York (CCNY), part of the City University of New York (CUNY) system. His office is located in the Center for Discovery and Innovation, room 2.380, with contact details including phone 212-650-5580 and email sgayen@ccny.cuny.edu. Professor Gayen's research centers on biomedical optics, specializing in optical tomography and spectroscopy for cancer detection in highly scattering media. His work develops time reversal optical tomography algorithms for tumor localization in breast tissue, fluorescence imaging techniques, and laser applications in biomedicine. Key focus areas include light propagation modeling in turbid media, independent component analysis for image reconstruction, and novel optical contrast agents. Analysis of his 15 most recent publications (2024-2013) reveals three dominant research thrusts: (1) Synthesis and characterization of organic laser dyes (pyrylium salts) for biomedical imaging, (2) Development of II-VI semiconductor disk lasers using ZnCdMgSe heterostructures, and (3) Advanced optical tomography methods for tumor detection. His work consistently bridges fundamental photonics with clinical breast cancer applications, emphasizing time-resolved and spectroscopic approaches. No scientific awards were documented in the provided materials. While extensive publications indicate active research, no specific information about grant funding or student advising roles was included in the source text. His laboratory work appears centered on optical instrumentation development for breast cancer imaging, though no explicit lab name or team structure was mentioned.

Elona Shatriمشاهده پروفایل

مدرس

• Optical Music Recognition
• Deep Learning
• Artificial Intelligence
• +۳ مورد دیگر

Elona Shatri is a PhD candidate at the UKRI Centre for Doctoral Training in Artificial Intelligence and Music (AIM) and a visiting lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science. She specializes in Optical Music Recognition (OMR) using Deep Learning and is a leading advocate for ethical AI practices. Her research focuses on advancing OMR techniques, including GAN-based music synthesis and dataset development (e.g., DoReMi), while addressing challenges in low-data scenarios and historical manuscripts. She teaches postgraduate courses on Machine Learning and Visual Data Analysis, blending technical rigor with creative applications. Research Interests : OMR with deep learning, ethics in AI, generative AI models, music informatics, and interdisciplinary collaborations between AI and the arts. Awards : Recipient of the Best Student Paper Award at the 2024 Knowledge Discovery in OMR conference for her work on instance segmentation. Projects : Co-lead on the UK-Qatar AI Collaboration (2024–) and the CREAATIF project examining AI in creative industries. Founded the QMUL AI and Ethics Research Group, fostering interdisciplinary dialogues on fairness, transparency, and societal impacts of AI. Labs/Teams : Centre for Digital Music (C4DM), part of Queen Mary's School of Electronic Engineering and Computer Science.

Ganesh Krishnasamyمشاهده پروفایل

مدرس

• Computer Vision
• Machine Learning
• Pattern Recognition
• +۶ مورد دیگر

Ganesh Krishnasamy is a Lecturer at the School of Information Technology, Monash University Malaysia. He holds a PhD in Electrical Engineering from the University of Malaya, with earlier degrees from Universiti Kebangsaan Malaysia (B.Eng and M.Eng in Electrical and Electronic Engineering). His research focuses on computer vision, pattern recognition, manifold learning, and semi-supervised learning, with applications in multimedia processing and understanding. He has led three research projects including 'AEinstein: Adversarial AI amongst Materials Discovery Domains' and pioneered semi-supervised action recognition in videos. His work aligns with UN Sustainable Development Goals related to innovation and infrastructure. Research Interests: Computer Vision Pattern Recognition Manifold Learning Semi-Supervised Learning Optimization Algorithms HDR Image Reconstruction Recent Projects: AEinstein Project (2024-2026): Focuses on adversarial AI in materials discovery. Research Management System (2023-2024): Aims to optimize research workflows. Semi-Supervised Image-to-Video Adaptation (2020-2023): Developed ActNetFormer and other hybrid models. Publications: Over 16 outputs since 2014, with recent emphasis on HDR imaging, sports video analysis (badminton rally detection), and optimization techniques. His work bridges theoretical machine learning with commercial applications.

Phil Cumminsمشاهده پروفایل

استاد مدعو

• Earthquake Seismology
• Tsunami Modeling
• Geophysics
• +۳ مورد دیگر

Professor Phil Cummins is an Adjunct Professor at the Research School of Earth Sciences (RSES), The Australian National University (ANU), with a PhD in Geophysics from UC Berkeley (1988). He specializes in earthquake seismology, tsunami modeling, and seismic hazard assessment, focusing on Indonesia and the Asia-Pacific region. His research addresses earthquake mechanisms, tsunami generation, and basin effects on seismic waves. He collaborates with Geoscience Australia to enhance disaster risk reduction capabilities in developing nations. Research Interests: Earthquake source characterization and fault dynamics Tsunami forecasting and warning systems Basin amplification effects in seismic zones Historical seismicity and paleoseismic studies Seismic hazard assessment for urban areas like Jakarta and Bandung Key Projects: Finite Fault inversion using W-Phase data Improving tsunami warning systems via rapid source modeling Seismic microzonation studies in Indonesia Basin structure imaging via ambient noise tomography His work integrates geodetic, seismological, and numerical modeling techniques to advance understanding of geohazards. Recent studies include analyses of the 2022 Cianjur and 2018 Lombok earthquakes in Indonesia, and the 2013 Bohol earthquake in the Philippines.

Huw Lewis-Jonesمشاهده پروفایل

دانشیار

• Animal History
• Environmental Humanities
• Photography
• +۷ مورد دیگر

Dr Huw Lewis-Jones is an Associate Professor of Environment and Culture at Falmouth University, where he joined as Senior Lecturer in 2018. An environmental historian, expedition leader, and award-winning author, he bridges academic scholarship with practical fieldwork, leading voyages to polar regions and remote locations worldwide. Based in the Institute of Photography, he teaches across disciplines including wildlife, culture, history, and creativity. PhD: Arctic, Visual Culture, Environment, Exploration (University of Cambridge, 2007) MPhil: Polar Studies, Humanities, Social Sciences (University of Cambridge, 2002) BA: Geography, Conservation, Arctic, Himalayas (University of Cambridge, 2001) Lewis-Jones's research spans Animal History, Environmental Humanities, and Visual Culture, with particular focus on Polar Regions and Photography. His work examines human relationships with wilderness through historical, visual, and cultural lenses, emphasizing fieldcraft and sustainability. As both a scholar and practitioner, he explores how visual documentation shapes our understanding of environmental change and conservation. His publications demonstrate a consistent interdisciplinary approach connecting exploration history with contemporary environmental concerns. The work shows particular strength in visual documentation of polar regions, maritime history, and the cultural significance of maps and sketchbooks. His recent focus on animal-human relationships and climate literacy represents a timely contribution to environmental humanities. Edward Stanford Award for Illustrated Book of the Year (2018) Leif Erikson Award for services to exploration and heritage (2015) Multiple international book awards including Motovun Book Awards, World Fantasy Awards, and China Nature Book Award Elected Fellow of the Royal Geographical Society (2003) Lewis-Jones supervises nine PhD students on diverse topics spanning wildlife conservation, photography, environmental humanities, and creative futures. His professional engagement extends beyond academia through expedition leadership, BBC documentary contributions, and curation of international photography exhibitions. He maintains active connections with polar research institutions including the Scott Polar Research Institute and National Maritime Museum. As both a creative adventurer and conservation advocate, Lewis-Jones operates at the intersection of academic research, public engagement, and environmental advocacy, frequently working on ships, glaciers, and remote islands to bring experiential learning to his students and audiences worldwide.

Muneer Ahmadمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Data Science
• Healthcare Informatics
• +۳ مورد دیگر

Dr. Muneer Ahmad is an experienced academic with over 22 years of international experience in teaching, research, and academic leadership within Computer Science, specializing in Artificial Intelligence, Data Science, and Healthcare Informatics. He currently serves as Senior Lecturer and Program Lead for the MSc Data Science at the University of Roehampton , UK, having previously held teaching and leadership roles in South Korea, Malaysia, Saudi Arabia, and Pakistan. Education: PhD in AI & Data Science His research is multidisciplinary and application-driven, focusing on AI for healthcare, precision agriculture, and industrial IoT. He leads large, diverse student cohorts and collaborates with academic teams to deliver inclusive education. Recognized as a Senior Fellow of Advance HE (SFHEA) , he emphasizes curriculum innovation and pedagogy. With over 100 peer-reviewed publications and £200,000+ secured funding, his work spans AI in healthcare diagnostics Smart urbanization Genomic data processing Cybersecurity Educational technology Industrial 4.0 He has supervised over 50 PhD/Master's students and serves on editorial boards of journals like Information and Bioengineering . Recent projects include AI-driven crop yield estimation, cervical cancer diagnosis, and pandemic resilience technologies.

LI Yuanxi, Kristenمشاهده پروفایل

مدرس

• Semantic Multimedia Indexing and Retrieval
• Adaptive Search Engine Design
• Link Prediction Based on Multimedia Big Data
• +۳ مورد دیگر

Dr. LI Yuanxi, Kristen is a Lecturer in the Department of Computer Science at Hong Kong Baptist University. She holds a Ph.D. in Computer Science and an M.Sc. in IT Management from the same institution. Her research focuses on semantic multimedia indexing, adaptive search engines, link prediction using big data, infectious disease modeling, inclusive education, and web usability design. Education: Ph.D. in Computer Science, Hong Kong Baptist University M.Sc. in IT Management, Hong Kong Baptist University Her research explores innovative methods for multimedia retrieval and search engine design, with applications in social media analysis and public health. She actively engages in pedagogical research to enhance teaching methodologies. Recent Workshops: Organized the 2017 Joint Design Workshop on 'Design for Sustainability (D4S)', available on YouTube. Her publications emphasize semantic technologies and ontology-driven systems to improve information retrieval effectiveness.

• Healthcare Informatics
• Population Health Management
• Artificial Intelligence in Healthcare
• +۵ مورد دیگر

Dr. Adrian Zai is an Associate Professor in the Population and Quantitative Health Sciences Department at UMass Chan Medical School and holds roles in the T.H. Chan School of Medicine and Morningside Graduate School of Biomedical Sciences. He serves as Chief Research Informatics Officer (CRIO), overseeing the Research Informatics Core and strategic informatics infrastructure. His research focuses on healthcare informatics, population health management, and implementation science, leveraging AI and decision support systems to improve patient care. Dr. Zai’s work includes developing culturally tailored AI chatbots, optimizing informed consent processes, and enhancing telehealth solutions. Education: B.A. Chemistry (Boston University), MPH Healthcare Management (Harvard), MD and PhD Pathology (Boston University). His research interests emphasize data-driven solutions for population health, including chronic disease management, pandemic response strategies, and equitable healthcare access. Notable projects include the Healthy at Home COPD intervention and studies on SARS-CoV-2 diagnostics and antigen test distribution. Dr. Zai leads teams in clinical research infrastructure and collaborates on large-scale initiatives like the National COVID Cohort Collaborative. His lab, Research Informatics, supports data science needs across UMass Chan.

Carla Teixeira Lopesمشاهده پروفایل

دانشیار

• Information Retrieval
• Human-Computer Interaction
• Health Informatics
• +۴ مورد دیگر

Carla Teixeira Lopes is an Associate Professor in the Department of Informatics Engineering at the Faculty of Engineering, University of Porto (FEUP), and a Senior Researcher at the Institute for Systems and Computer Engineering, Technology and Science (INESC TEC). Her career spans academic and research roles, blending expertise in information retrieval with human-computer interaction to enhance digital accessibility. Ph.D. in Informatics Engineering (2013), FEUP M.Sc. in Information Management (2005), FEUP B.Sc. in Informatics Engineering and Computing (1999), FEUP Her research focuses on improving online health information retrieval and leveraging linked data for cultural heritage preservation. She develops tools to optimize search behavior, readability assessment, and semantic archival systems. Recent work includes applications of large language models (e.g., Llama 3, GPT) for text simplification and entity linking. Carla’s publications reflect interdisciplinary trends in Natural language processing Health informatics Linked data architectures Archival modernization Image metadata frameworks She contributes to digital library practices and gender balance studies in informatics academia. As a Senior Researcher at INESC TEC, she bridges academic and applied research, emphasizing user-centric design and data interoperability. Her email is ctl@fe.up.pt .

Priyanka Singhمشاهده پروفایل

مدرس

• Cyber Security
• Digital Forensics
• Privacy and Security Aspects
• +۵ مورد دیگر

Dr. Priyanka Singh is a Lecturer in Cyber Security at the School of Electrical Engineering and Computer Science, University of Queensland. She holds a PhD in Image Forensics and has conducted postdoctoral research at SUNY Albany and Dartmouth College, collaborating with Prof. Hany Farid. Her research focuses on Cyber Security, Digital Forensics, Privacy, Homomorphic Encryption, and Cloud Computing applications. Key contributions include real-time child pornography detection and privacy-preserving frameworks for digital authentication. Education: PhD in Image Forensics (university unspecified), postdoctoral work at SUNY Albany and Dartmouth College. Notable collaborations include a talk invitation at MIT by Prof. Ramesh Raskar. Research Interests: Cyber Security mechanisms, Digital Forensics techniques, Privacy-Preserving algorithms, Homomorphic Encryption protocols, and Cloud Security solutions. Recent Articles: Focus on AI ethics (e.g., FakeFaceDiscriminator), privacy-preserving biometrics (e.g., IRIS-SAFE), and secure anomaly detection (e.g., SADHE). Her work spans 42 conference papers and 22 journal articles, addressing challenges like encrypted video tampering detection and federated learning resilience. She advocates for technology's societal impact through explainable AI and ethical AI use cases.