جستجوی استاد راهنمای دانشگاهی

Dr. Farhad Maleki is an Assistant Professor in the Department of Computer Science at the University of Calgary, Faculty of Science. He holds a PhD in Computer Science from the University of Saskatchewan (2019). His postdoctoral research at McGill University’s Augmented Intelligence & Precision Health Laboratory focused on machine learning for medical image analysis. He has held leadership roles, including President of the Association of Postdoctoral Fellows at McGill and President of the Computer Science Graduate Council at the University of Saskatchewan. Currently, he serves on the Machine Learning Education Sub-Committee of the Society for Imaging Informatics in Medicine and as a guest editor for journals in medical data analysis. Dr. Maleki’s research spans Artificial Intelligence , Machine Learning , Biomedical Data Analysis , and Computer Vision . His work emphasizes medical applications, including tumor segmentation, clinical outcome prediction, and AI-driven diagnostics in oncology and cardiology. He also explores agricultural challenges, such as wheat head segmentation using generative models and domain adaptation. Key contributions include developing robust medical imaging tools (e.g., Rel-UNet for tumor segmentation) and frameworks for evaluating AI model reliability ( RIDGE ). His work bridges clinical needs with computational innovation, addressing issues like reproducibility, generalizability, and low-annotation learning across healthcare and agriculture domains. Dr. Maleki’s articles focus on advancing AI methods for precision health and agriculture. His recent work highlights interdisciplinary applications, such as integrating clinical and pathology data for cancer survival prediction, optimizing radiation therapy using Bayesian methods, and leveraging synthetic data for crop phenotyping. These studies emphasize practical deployment and ethical considerations in AI adoption.

• Artificial Intelligence
• Machine Learning
• Medical Imaging
• +۵ مورد دیگر

Michael Daniele is an Associate Professor at North Carolina State University, jointly appointed in the Department of Electrical & Computer Engineering and the Joint Department of Biomedical Engineering . His research focuses on bioelectronics engineering, particularly in developing microsystems for monitoring, mimicking, and augmenting biological functions. He leads the @BiointerfaceLab , exploring wearable/implantable biosensors, microphysiological systems, and process analytical technologies for biomanufacturing. Education : Ph.D. in Materials Science & Engineering (Clemson University, 2012) Bachelor's in Materials Science & Engineering (Rutgers University, 2009) Research Highlights : Developing "injury-on-a-chip" models for coagulation studies Pioneering hydrogel microneedles for diagnostic devices Advancing light-controlled peptide ligands for protein purification Collaborating with Novartis on viral vector manufacturing Award Recognition : 2024 William F. Lane Outstanding Teaching Award 2019 NSF CAREER Award 2022 University Faculty Scholar Grants & Initiatives : Co-leader of the NC-Viral Vector Initiative (2023–present) NSF-funded projects in biosensor integration and biomanufacturing His work bridges engineering and medicine, with applications in gene therapy, wearable diagnostics, and precision agriculture.

• Bioelectronics Engineering
• Wearable Biosensors
• Microphysiological Systems
• +۳ مورد دیگر

Rynson W.H. Lau is a Professor of Computer Science at City University of Hong Kong (CityU), leading research in Computer Graphics, Computer Vision, and Deep Learning. He holds an Honorary Professorship at Swansea University. Previously, he served on faculties at Durham University and The Hong Kong Polytechnic University. His work focuses on advancing graphics and vision techniques, including deep learning applications for graphics/vision problems, with publications in top venues like SIGGRAPH, CVPR, and NeurIPS. He has received the Adobe Research Gift (2023) and the Springer Nature Editorial Contribution Award (2025) for his editorial contributions to the International Journal of Computer Vision . Education: B.Sc. (First-class Honors) in Computer Systems Engineering from University of Kent Ph.D. in Computer Science from University of Cambridge Research Interests: Computer Graphics: Focused on 3D reconstruction, rendering, and real-time performance capture. Computer Vision: Specializing in saliency detection, object recognition, and low-light scene enhancement. Deep Learning: Developing generative models and diffusion-based frameworks for graphics and vision tasks. Editorial Roles: Editorial Board Member, International Journal of Computer Vision and IET Computer Vision . Guest Editor for special issues in journals like ACM Transactions on Internet Technology and IEEE Transactions on Multimedia. Teaching: 2024/25 Academic Year: CS4185: Multimedia Technologies and Applications CS4188/CS5188: Virtual Reality Technologies and Applications Research Team: Advises over 20+ students and collaborates internationally. Recent projects include AI-driven VR systems for healthcare and advanced 3D content generation using diffusion models.

• Computer Graphics
• Computer Vision
• Deep Learning
• +۳ مورد دیگر

Saeed Hassanpour is Professor of Biomedical Data Science, Epidemiology, and Computer Science at Dartmouth College, where he founded and directs the Center for Precision Health & Artificial Intelligence (CPHAI). His NIH-funded research develops novel machine learning methods for medical image analysis and clinical text mining to improve diagnosis, prognosis, and personalized therapies. He earned a PhD in Electrical Engineering/Biomedical Informatics from Stanford University, an MMath from University of Waterloo, and a BS from Sharif University of Technology. Research breakthroughs include pioneering deep learning approaches in digital pathology. He serves on NIH's Clinical Data Management and Analysis Study Section and the JAMIA Open Editorial Board. Prior to Dartmouth, he worked as a Research Engineer at Microsoft and completed postdoctoral training at Stanford's Center for Artificial Intelligence in Medicine and Imaging. Awards 2019 Agilent Early Career Professor Award for digital pathology innovations

• Machine Learning
• Precision Health
• Digital Pathology
• +۴ مورد دیگر

Dr. Jean-Philippe Couderc is a Research Assistant Professor of Medicine in the Cardiology Department at the University of Rochester Medical Center and Chief Technology Officer of iCardiac Technology Inc. He holds a PhD in Biomedical Engineering from the French National Institute of Applied Sciences (1997), an MBA in Healthcare Management from the Simon School of Business (2003), and an MS in Medical Specialties from a French institution (1994). His research focuses on quantitative electrocardiography, ventricular repolarization, and cardiac safety, with contributions to clinical study design and medical software development. He leads the Heart Research Follow-up Program Laboratory and serves on the editorial board of Annals of Non-Invasive Electrocardiology . Notable awards include the Frost & Sullivan Technology Innovation Award (2006) and the Mirowski-Moss Career Development Award (2003). His work spans federal grants, industry collaborations, and over 100 peer-reviewed articles. Research Interests: Dr. Couderc’s work integrates computational science, electrophysiology, and clinical cardiology to address challenges in cardiac safety, drug evaluation, and wearable health technologies. His lab develops novel ECG analysis tools and evaluates their application in arrhythmia monitoring, drug-induced QT prolongation, and non-invasive diagnostics. Publications: His recent work includes advancements in video-based cardiac monitoring, demographic factors in ECG patch usage, and biomarker identification for epilepsy and heart conditions. He co-authored key consensus statements on mHealth in arrhythmia management, emphasizing digital tools for heart rhythm professionals. Awards & Grants: Dr. Couderc has secured NIH and industry grants, leading projects on repolarization dynamics and cardiac resynchronization therapy. He advises on FDA drug evaluation and contributes to international clinical guidelines.

• Physiological signal processing
• Medical software design
• Quantitative electrocardiography
• +۴ مورد دیگر

Arianne Teherani, PhD, is Professor in Residence in the Department of Medicine at the University of California, San Francisco (UCSF) School of Medicine. She serves as Founding Co-Director of the UC Center for Climate, Health and Equity and Director for Program Evaluation and Education Continuous Quality Improvement at the UCSF School of Medicine. She earned her undergraduate degree in Social Ecology from the University of California, Irvine, her master's and doctorate in Education from the University of Southern California, and completed a fellowship in Higher Education at the University of British Columbia. Dr. Teherani’s research advances equity, social justice, and climate solutions in health professions education. Her work identifies and dismantles practices that perpetuate educational disparities. She leads initiatives in equitable clinical assessment, climate-health education, and sustainable healthcare training. Her scholarship focuses on educational reform, faculty development, and community-engaged learning. She has published extensively on topics including clerkship equity, professionalism, longitudinal integrated clerkships, and the integration of climate change into medical education. Her recent publications demonstrate a strong trend toward climate-health education, healthcare decarbonization, and equity in assessment. She frequently collaborates with national and UC-system-wide teams on sustainability and educational innovation. Her work emphasizes systems-level change and the translation of research into policy and practice. UCSF Faculty Sustainability Award UC Sustainability Champion Award Faculty Climate Action Champion (University of California system) Dr. Teherani mentors students, residents, fellows, and faculty in health professions education. She has led numerous educational initiatives, including the Aspiring Physicians Program and the Academic Leadership Academy, aimed at supporting underrepresented students. She has also driven continuous quality improvement in medical education through rigorous evaluation of innovative programs. Her leadership extends to national organizations including the Association of American Medical Colleges, the American Educational Research Association, and the National Academies of Science, Engineering, and Medicine. She leads the Equity and Justice in Education initiative and is deeply involved in antiracism and DEI efforts. She co-leads faculty development programs focused on sustainable healthcare and climate education across the UC system.

• Health Professions Education
• Educational Equity and Social Justice
• Climate Change and Health
• +۱۲ مورد دیگر

Professor Carl Thompson is a leading academic in applied health research at the University of Leeds' School of Healthcare within the Faculty of Medicine and Health. His roles include being a registered nurse with extensive NHS experience, from nursing assistant to NHS Trust non-executive director. Previously, he held a personal chair in health sciences at the University of York. His expertise spans clinical decision making, implementation science, and evidence-based healthcare. Research focuses include care home quality improvement, wearable technology applications, and computerised decision support systems. Notable projects include the £2m CONTACT study on Bluetooth wearables for contact tracing in care homes and the STaRQ study examining nurse staffing impacts on care quality. He collaborates internationally with institutions in Australia, the Netherlands, Canada, and the US. Education: DPhil in Social Policy (University of York, 1996), BSc Hons in Social Policy (1st class, 1993), RN qualification (York College of Nursing, 1989). Grants: Secured or collaborated on £20m+ projects from NIHR, MRC, and ESRC. Teaching: Covers medical informatics, decision making, and leadership in healthcare education. Awards: No specific awards listed, though his extensive funding and leadership roles reflect professional recognition. Leadership: Former Director of Research in the School of Healthcare and Pro Dean for Applied Health Research. His research emphasizes 'how people use information in clinical practice and policy making,' with a focus on translating evidence into practice. He advises on national funding panels (NIHR HSDR, Irish Health Research Board) and mentors PhD students in decision science and implementation research. Current initiatives include the Nurturing Innovation in Care Homes (NiCHE Leeds) collaboration and membership in the NIHR Yorkshire and Humber CLAHRC's Improvement Science theme. He actively supports implementation science through visiting professorships at the Universities of Alberta and East Anglia.

• Clinical Decision Making and Judgement
• Implementation Science
• Mixed Methods Evaluation
• +۴ مورد دیگر

Prim. Assoc. Prof. PD Dr. Walter Struhal MSc FEAN serves as Head of the Clinical Department of Neurology at University Hospital Tulln since 2017 and holds a shared leadership role at the University Clinic for Neurology (Karl Landsteiner Private University of Health Sciences) since 2019. His career bridges clinical neurology and translational research in autonomic nervous system disorders. Research Focus : Struhal specializes in autonomic dysfunction, particularly its role in Alzheimer's dementia, post-COVID-19 neurological sequelae, and neurodegenerative diseases like multiple system atrophy. His work emphasizes modern diagnostic tools such as wearable ECGs and power modulation spectrum algorithms for signal quality control. Recent collaborations include developing the NEUROGED Guidelines for neurogenic urinary/sexual symptoms and mapping autonomic education gaps in European neurology training. Scientific Contributions : As a Fellow of the European Academy of Neurology (FEAN) , he co-led international studies on ECG quality indices (PDQI/MSQI) and participated in the AFFRICATE Project analyzing autonomic impacts of cerebral vascular interventions. His 15 most recent publications (2020-2025) span stroke care economics, dysphagia management, and autonomic testing innovations, reflecting his commitment to clinical-neurological research infrastructure development. Scientific Awards : Metric-based scholarship for Austro-Mir space research Fellow of the European Academy of Neurology (FEAN)

• Neurology
• Autonomic Nervous System
• Alzheimer's Dementia
• +۴ مورد دیگر

Andrew Bishara, MD, is an Assistant Professor in Residence in the Department of Anesthesiology within the School of Medicine at the University of California, San Francisco (UCSF). He is affiliated with multiple UCSF clinical sites, including Mission Bay, Mount Zion, and Parnassus, and is actively involved in the AI Clinical Innovation Lab, Transplant Anesthesia Research Group, and POCCO (PeriOperative Cardiac Complications Observatory). His clinical practice as an anesthesiologist is deeply integrated with his research in machine learning and artificial intelligence for perioperative care. Dr. Bishara's educational background includes a BSE in Mechanical Engineering from MIT (2009), an MD from Harvard Medical School (2014), and a D.ABA. in Anesthesiology from UCSF (2019). He also completed specialized training in Medical Informatics and Artificial Intelligence through the Bakar Computational Health Sciences Institute (2020) and a Diversity, Equity, and Inclusion Champion program at UCSF (2022). His research focuses on developing and validating machine learning models to predict and prevent surgical complications such as acute kidney injury, postoperative delirium, pain, and blood loss in real time. He emphasizes creating clinically usable models and improving AI-human interfaces for seamless integration into clinical workflows. His work also explores gender-based disparities in coronary artery disease diagnosis using EHR data analytics. His recent publications demonstrate expertise in AI quality improvement, model implementation in acute care, and predictive modeling across diverse surgical and critical care domains. He co-founded Bezel Health, a company focused on healthcare quality measurement, reflecting his commitment to translating research into real-world impact. Clinical Artificial Intelligence Quality Improvement Real-time Risk Assessment in Surgery AI Integration in Anesthesia Gender Disparities in Cardiac Care Transplant Anesthesia Research Regulatory Aspects of AI in Medicine Dr. Bishara is actively engaged in advancing perioperative medicine through innovation in data science and AI, with a strong emphasis on improving patient outcomes, equity, and clinical workflow efficiency.

• Machine Learning in Healthcare
• Artificial Intelligence in Clinical Decision Support
• Perioperative Medicine
• +۱۲ مورد دیگر

Andreas Holzinger is a Professor at Graz University of Technology, with additional affiliations at Medical University Graz and University of Natural Resources and Life Sciences Vienna in Austria. He is recognized as an IFIP Fellow (2021) for his significant contributions to information processing and computer science. His work spans multiple institutions across Europe, with notable collaborations extending to the University of Alberta in Canada. Professor Holzinger's research focuses on Human-Centered AI, Explainable AI (XAI), and their practical applications across diverse domains. His work bridges theoretical AI advancements with real-world implementations in healthcare, forestry, and human-robot interaction. He has pioneered approaches in counterfactual explanations, graph neural networks, and human-in-the-loop systems that emphasize transparency and trustworthiness in AI decision-making processes. His recent publications demonstrate a strong trend toward integrating large language models with traditional AI systems while maintaining explainability. Holzinger's work consistently emphasizes the human element in AI systems, ensuring that technological advancements serve human needs rather than obscuring decision processes. His research in medical AI, smart forestry, and agricultural applications shows a commitment to solving practical problems with human-centered technological solutions. Scientific Awards: IFIP Fellow (2021) Professor Holzinger has been instrumental in establishing design guidelines for explainable AI systems, particularly through his work on post-hoc versus ante-hoc explanations. His research on Kandinsky Patterns has provided valuable experimental frameworks for pattern analysis and machine intelligence. He has secured significant research funding for projects bridging AI with practical applications in healthcare and environmental monitoring. His leadership extends to the organization of major conferences and workshops, including the CD-MAKE conference series, where he has fostered interdisciplinary collaboration between AI researchers and domain experts. His work on the CLARUS platform demonstrates practical implementations of interactive explainable AI for medical applications.

• Explainable AI
• Human-AI Interaction
• Machine Learning
• +۷ مورد دیگر

Mieke Koehoorn serves as Vice Dean, Academic Affairs, and Professor at the School of Population & Public Health within the University of British Columbia . Her academic oversight includes strategic planning, faculty development, and maintaining academic standards. She has held leadership roles such as UBC Vancouver Senator and Head of the Division of Occupational and Environmental Health. Research Interests : Dr. Koehoorn focuses on occupational health, gendered work environments, work disability, and data linkage for epidemiological studies. Her work addresses disparities in workers’ compensation, safety protocols, and health equity in digital health interventions. Article Trends : Recent publications emphasize work disability duration , gender and immigrant disparities , digital STI testing systems , and occupational hazard exposure , reflecting interdisciplinary approaches combining epidemiology, policy analysis, and social determinants of health. Awards : Canadian Institutes for Health Research Chair in Gender, Work and Health Michael Smith Health Research Scholar Award Senior Scholar Awards Administrative Contributions : She has served as Associate Director of Faculty Affairs and Research for the School of Population & Public Health and co-led the Partnership for Work, Health and Safety with WorkSafeBC.

• Occupational Health
• Workers' Compensation
• Sex and Gender Differences in Work Injury
• +۵ مورد دیگر

Kishlay Jha is an Assistant Professor at the University of Iowa's College of Engineering in the Department of Electrical and Computer Engineering. He is also a researcher at the Center for Bioinformatics and Computational Biology and the Iowa Initiative for Artificial Intelligence. PhD in Computer Science from University of Virginia (2022) Email: kishlay-jha@uiowa.edu Office: 3320 Seamans Center, Iowa City, IA 52242 Phone: (319) 467-0096 His research focuses on data science and artificial intelligence with emphasis on data mining, machine learning, and their applications in biomedical domains. He develops methodologies for transforming heterogeneous clinical, genomic, and bibliographic data into actionable knowledge for scientific advancement. Recent work includes: Semantic knowledge integration in biomedical language models Dynamic representation learning for evolving systems Hypergraph-based contrastive learning for healthcare applications Continual learning frameworks for time-sensitive domains Knowledge-guided representation learning Biomedical hypothesis generation He leads the Data Mining and Machine Learning Laboratory, where his team develops innovative tools for both biomedical discovery and general AI applications.

• Data Mining
• Machine Learning
• Natural Language Processing
• +۴ مورد دیگر

Ina Fichtner is a Professor at the Faculty of Digital Transformation of University of Applied Sciences HTWK Leipzig since 2022. Previously, she led the MINT department at the Institute for Applied Training Science (IAT) in Leipzig for 13 years (2009–2022), focusing on integrating mathematics, informatics, and natural sciences into sports research. Her work bridges computer science , biomechanics , and sports informatics , with extensive projects on athlete movement analysis, data systems (IDA), and digital tools for elite sports. PhD in Computer Science (2007) from TU Dresden and Leipzig University Diplom in Mathematics and Computer Science (2002) from Jena, Dresden, and Sheffield Her research spans data science , sports technology , and applied informatics , particularly in ski jumping , dive analysis , and athlete biomechanics . She has co-authored numerous publications in theoretical computer science and applied sports informatics , including studies on 3D body scanning , inertial sensors , and force-velocity profiling . She served as Alumni Representative and Treasurer of the Friends' Association at HTWK Leipzig, with memberships in German Mathematical Society and German Sports Science Association .

• Computer Science
• Sports Informatics
• Data Science
• +۵ مورد دیگر

Dr. Zhenghao Chen is a Lecturer in Data Science at the University of Newcastle, affiliated with the School of Information and Physical Sciences. He earned his Ph.D. from the University of Sydney in 2022, following a B.Eng. H1 degree from the same institution in 2017. Prior to his current position, Dr. Chen served as a Postdoctoral Research Fellow at the University of Sydney (2022-2024), a Research Engineer at TikTok (2024), and as a Visiting Research Scientist at Microsoft Research and Disney Research (2022-2023). Dr. Chen's educational background includes: Doctor of Philosophy, University of Sydney (2022) Bachelor of Information Technology (B.Eng. H1), University of Sydney (2017) Dr. Chen's research spans multiple domains within artificial intelligence, with particular expertise in Computer Vision, Natural Language Processing, and Machine Learning. His work in Generative AI has garnered significant recognition, with applications in both academic and industrial settings. His research interests are reflected in his Fields of Research percentages: Deep Learning (30%), Computer Vision (30%), Natural Language Processing (20%), and Multimodal Analysis and Synthesis (20%). His publications in top-tier venues like CVPR, ICCV, ECCV, and journals like IEEE TPAMI demonstrate the breadth and impact of his work. Analysis of Dr. Chen's recent publications (2022-2025) reveals a consistent focus on neural compression techniques, 3D perception, and multimodal AI systems. His work spans medical imaging (CXR bone suppression), video compression, point cloud processing, and neural surface reconstruction. A notable trend is his exploration of efficient AI systems that work well under resource constraints, as evidenced by his involvement in the EMCLR workshop. His research often bridges theoretical advances with practical applications across multiple domains. Dr. Chen has received several prestigious awards: Microsoft Research Asia StarTrack Fellowship (2025) ACM SIGMM Award for Outstanding PhD Thesis in Multimedia Computing (2024) Australia Government Research Training Program (RTP) Fellowship (2019) Google Australia Prize for Excellence in Computer Science (2017) Dr. Chen is actively involved in the academic community, serving on the Program Committee for major AI conferences including CVPR, ICCV, ECCV, SIGGRAPH, AAAI, and others. He also organizes workshops in Multimedia and ICCV conferences, and serves as a reviewer for prestigious journals. His teaching responsibilities include courses on Intelligent Visual Signal Understanding, Video Intelligence and Compression, Database and Information Management, and Computing Fundamentals at both the University of Sydney and University of Newcastle.

• Computer Vision
• Natural Language Processing
• Machine Learning
• +۳ مورد دیگر

Dr. Angela Alberga is an Associate Professor and Tier 2 University Research Chair at Concordia University's Department of Health, Kinesiology & Applied Physiology. Her research focuses on weight stigma, pediatric obesity, and health equity, with interdisciplinary applications in public health, education, and policy. BSc, Exercise Science & Psychology, Concordia University MSc & PhD, Human Kinetics, University of Ottawa Postdoctoral Fellow, University of Calgary (CIHR & Eyes High Fellowships) Dr. Alberga’s research program investigates how societal and institutional factors influence weight-related issues, including obesity, eating disorders, and psychosocial wellbeing. Her work emphasizes patient-oriented research, behavioral interventions, and evidence synthesis in population health contexts. Recent research trends include clinical practice guidelines for pediatric obesity, weight stigma reduction in healthcare, nutrition education tools for bariatric surgery, and psychosocial impacts of weight bias. Key themes span public health, behavioral epidemiology, and health equity. Canadian Diabetes Association Doctoral Award Banting CIHR Postdoctoral Fellowship Eyes High Postdoctoral Fellowship Dr. Alberga supervises graduate students in Health and Exercise Science (MSc/PhD programs) and has secured grants from CIHR, FRQ-S, and the Canadian Pediatric Research Foundation for her work on obesity and health equity.

• Pediatric Obesity
• Weight Stigma
• Health Equity
• +۷ مورد دیگر