جست‌وجوی استاد و پژوهشگر

Chung Hyun Gohمشاهده پروفایل

استادیار

• Biomechanical Engineering
• Rehabilitation Robotics
• Medical Device Design
• +۳ مورد دیگر

Dr. Chung Hyun Goh is an Assistant Professor of Mechanical Engineering at the University of Texas at Tyler. He joined the university in 2015 after serving as a senior research associate at the University of Oklahoma’s Systems Realization Laboratory from 2012 to 2015. With a Ph.D. in Mechanical Engineering from Georgia Institute of Technology (2002), Dr. Goh has extensive experience in both industry and academia. His research focuses on biomechanical engineering, rehabilitation robotics, medical device design, and computational modeling. Notable projects include developing the RoboREHAB robotic training device and optimizing orthopedic implants using deep learning and finite element analysis. He has authored over 30 peer-reviewed publications and contributed to interdisciplinary design methodologies. Education: B.S., Ordnance Engineering, Korea Military Academy, Seoul, Korea, 1987 M.S.M.E., Mechanical Engineering, Oklahoma State University, 1992 Ph.D., Mechanical Engineering, Georgia Institute of Technology, 2002 Research Interests: Dr. Goh’s work integrates robotics, machine learning, and computational techniques to address challenges in rehabilitation engineering, medical device optimization, and materials science. His recent projects emphasize gait rehabilitation systems, exoskeleton design, and predictive modeling for vascular health. He also explores decision support systems for materials selection and process optimization in manufacturing. Publications: His research spans 30+ articles in journals and conferences, focusing on biomechanics, robotics, and computational methods. Key themes include finite element analysis, reinforcement learning applications in robotics, and interdisciplinary design frameworks. Advising & Grants: While no specific grants or advisees are listed, Dr. Goh’s contributions to collaborative projects suggest active involvement in interdisciplinary research teams. Labs/Teams: Though specific lab affiliations are not detailed, his work aligns with robotics and computational engineering research groups.

Alkiviadis Tsamisمشاهده پروفایل

استادیار

• Biomechanics
• Biomedical Engineering
• Materials Science
• +۵ مورد دیگر

Dr. Alkiviadis Tsamis is an Assistant Professor in the Department of Mechanical Engineering at the University of Western Macedonia (Polytechnic School). His research focuses on the mechanics and engineering of soft biological materials, integrating multi-scale experimental and computational techniques. Key areas include ECM microenvironment characterization, fiber-reinforced biomaterials, and nanofabrication technologies. Educations: PhD in Biotechnology & Bioengineering (2010), École Polytechnique Fédérale de Lausanne (EPFL) Mechanical Engineering Diploma (2004), National Technical University of Athens (NTUA) Research Interests: Mechanical behavior of soft biological materials ECM microstructure analysis Fluorescence imaging techniques Bio-inspired material design Multi-scale modeling in biomechanics Notable Research Trends (2020–2025): Recent work emphasizes nanofiber-based drug delivery systems (e.g., PCL/PLGA/HA scaffolds), smart hydrogel materials with radiative cooling properties, and fibronectin-based biosensors for 3D strain mapping. Collaborations span biomechanical modeling of vascular systems and magnetoactive collagen hydrogels. Awards: Aging Cell’s Best Paper 2017 (2017) IEEE Award for Novel Scientific Project (2004) Teaching: Courses include Engineering Statics, Biomedical Engineering, and Tissue Biomechanics at postgraduate level. Active in curriculum development for additive manufacturing and mechanical design.

• Machine Learning
• Natural Language Processing
• Healthcare Applications
• +۷ مورد دیگر

Frank Rudzicz is a Professor at the University of Toronto with appointments in the Faculty of Medicine and Department of Computer Science. His research bridges machine learning, natural language processing, and healthcare applications, with a particular focus on developing AI solutions for medical diagnostics, surgical assistance, and patient care. He leads several research initiatives in medical AI and collaborates extensively with clinicians and healthcare institutions. Rudzicz's research interests span multiple critical areas in healthcare AI. He has pioneered work in speech-based detection of neurological conditions including Alzheimer's and Parkinson's diseases, developing algorithms that analyze linguistic patterns to identify early signs of cognitive decline. His work in surgical AI has led to systems that provide real-time decision support during operations and analyze surgical performance. He also investigates ethical AI implementation in healthcare, addressing privacy concerns and developing frameworks for trustworthy clinical AI systems. More recently, his research has expanded into large language models for medical applications, focusing on privacy preservation, fairness, and explainability in clinical contexts. His publication record shows a clear evolution from foundational work in speech processing and dysarthria recognition toward increasingly sophisticated medical AI applications. Early work focused on improving speech recognition for impaired speakers, which naturally led to applications in neurological disorder detection. Over the past decade, his research has expanded to encompass broader healthcare applications, with recent work heavily featuring transformer models, multimodal data integration, and ethical considerations in medical AI deployment. His current research demonstrates strong emphasis on practical implementation challenges including model security, privacy preservation, and clinical integration of AI systems. Rudzicz has received recognition for his work, including best paper awards at major conferences like ICLR 2025. His research has been supported by numerous grants focusing on AI in healthcare, though specific grant details aren't provided in the available text. He has mentored numerous graduate students who have gone on to contribute significantly to medical AI research. As a leader in medical AI, Rudzicz contributes to major collaborative efforts including the Delphi consensus statement for digital surgery. His work frequently appears in top-tier AI and medical journals, demonstrating his ability to bridge the technical and clinical domains. Through his research group at the University of Toronto, he continues to advance the frontier of AI applications in healthcare while addressing the practical and ethical challenges of implementing these technologies in real clinical settings.

• Magnetic Resonance Imaging
• Medical Imaging
• Biomedical Engineering
• +۳ مورد دیگر

Aaron T Anderson is an Adjunct Clinical Assistant Professor in Veterinary Clinical Medicine at the University of Illinois at Urbana-Champaign. He is affiliated with the Beckman Institute for Advanced Science and Technology and the Center for Social & Behavioral Science. His research focuses on advanced imaging techniques such as magnetic resonance elastography (MRE), high-field MRI, and computational methods for medical image reconstruction. His work spans applications in neurology, oncology, and veterinary medicine, emphasizing non-invasive diagnostic tools and biomechanical analysis. Anderson’s educational background and specific degrees are not explicitly detailed in the provided text. However, his professional roles indicate expertise in biomedical engineering and clinical medicine. His research collaborations involve multidisciplinary teams exploring topics like concussion epidemiology, image reconstruction algorithms, and surgical implant compatibility with MRI. His research interests include optimizing MRI techniques for ultrahigh-field applications, developing machine learning tools for medical imaging analysis, and applying MRE to study tissue stiffness in neurological and oncological contexts. Recent work involves innovations in spatiotemporal denoising, subspace modeling, and 4D visualization tools for stereoelectroencephalography (SEEG) data. While no scientific awards are explicitly mentioned, his contributions to peer-reviewed journals and technical conferences highlight his impactful research in medical imaging. Anderson is actively involved in the Biomedical Imaging Center at the Beckman Institute, driving advancements in imaging technologies and their clinical applications.

• Cardiothoracic Surgery
• Surgical Planning
• Virtual Reality in Medicine
• +۳ مورد دیگر

Wouter Bakhuis is a Researcher at the Department of Cardiothoracic Surgery, Erasmus MC – University Medical Center Rotterdam. His work focuses on advancing surgical techniques through innovative technologies like virtual reality (VR) and 3D printing for preoperative planning. He completed his doctoral thesis in 2025, titled *Virtual reality planning in cardiothoracic surgery: From pilot to practice*, which explores the integration of VR into clinical practice. His research interests include optimizing surgical strategies for complex cases such as congenital heart defects (e.g., Double Outlet Right Ventricle) and thoracic procedures like segmentectomies. He emphasizes patient-specific planning to enhance surgical precision and outcomes. Collaborations with institutions globally highlight his contributions to minimally invasive techniques and anatomical resections. Notable research outputs address challenges in surgical planning, such as managing translobar venous drainage and refining segmentectomy approaches. His review articles underscore the transformative potential of VR in surgical training and future practice. While no scientific awards are explicitly listed, his work has garnered significant citations and reader engagement in academic platforms like Mendeley.

Mary S. Dietrichمشاهده پروفایل

استاد

• Biostatistics
• Nursing Science
• Medical Statistics
• +۷ مورد دیگر

Dr. Mary S. Dietrich is a Professor of Statistics & Measurement at Vanderbilt University School of Nursing. She holds affiliations with Biostatistics and Hearing & Speech departments. Her career began in 2006, combining statistical collaboration with academic computing and psychiatric neuroimaging expertise. She has advised Belmont University’s FNP program, fostering nursing science integration with statistical methods. Education: PhD in Statistics & Measurement (Vanderbilt), MS (Fort Hays State), BS (Bethel College) Her research focuses on advanced statistical methodologies in nursing and biomedical sciences, including group-based trajectory modeling, propensity score methods, and innovative applications in clinical trials. She actively collaborates on projects addressing lymphedema management, pediatric palliative care, and neuroimaging biomarkers for Alzheimer’s risk. Dr. Dietrich has led/co-investigated over 20 grants since 2014, including NIH-funded studies on labor disparities, cochlear implant technology, and human-animal interactions in pediatric oncology. Awards: Multiple Dean’s Awards (Vanderbilt Nursing), Hardy Wilcoxon Dissertation Award She contributes to editorial efforts advocating for evidence beyond p-value thresholds. Her work bridges statistical rigor with clinical relevance across disciplines such as audiology, oncology, and maternal health.

• Machine Learning
• Medical Imaging
• Orthopaedic Technology
• +۳ مورد دیگر

Dr. Yuan Chai is a Researcher affiliated with the Kolling Institute of Medical Research and the Faculty of Medicine and Health at the University of Sydney. He serves as President of the Australia China Scholar Network. His work focuses on integrating machine learning, medical imaging, and 3D printing to advance orthopaedic surgical techniques and personalized medical solutions. Dr. Chai holds a Ph.D. in Medicine from the Australian National University (2019) and has conducted studies at the Pennsylvania State University in 3D printing technology. Research Interests: Machine learning applications in medical imaging, surgical planning, 3D modeling for orthopaedic implants, and precision cutting tools for patella surgery. Current projects include automated landmark detection models for surgical reports, accuracy analysis in 3D pre-operative planning, and digital twin models for predicting surgical outcomes. Publications span topics like pelvic tilt measurement, customized implant design, and laser polishing of 3D-printed materials. Notable awards include a 2023 speaking role at the Australia-China Emerging Leaders' Summit and finalist recognition in the Young Australia China Alumni Award (2020). Education: PhD (Medicine, ANU, 2019), Studies at Penn State (3D Printing) Awards: 6 major recognitions including Dean’s List (2014) and Best Laboratory Paper awards (2016, 2018) Labs/Teams: Active contributor at Kolling Institute; leads Australia-China Scholar Network initiatives

• Multimodal Deep Learning
• Adaptive and Contextual AI
• Natural Language Processing
• +۳ مورد دیگر

Dr. Ruchit Agrawal is an Assistant Professor of Computer Science and Head of Computer Science Outreach at the University of Birmingham Dubai. Previously, he held roles including Postdoctoral Research Scientist at the University of Oxford, Marie-Curie Researcher at Queen Mary University of London, and AI Researcher at FBK, Italy. His research focuses on Multimodal Deep Learning, Adaptive AI, NLP, and Clinical Machine Learning. He earned a Ph.D. from Queen Mary University of London and M.S. and B.Tech degrees from IIIT Hyderabad. Education: Ph.D. in Computer Science (Queen Mary University of London), M.S. in Computer Science (IIIT Hyderabad), B.Tech. in Computer Science (IIIT Hyderabad). Research interests include AI-driven healthcare solutions, contextualized machine learning systems, and cross-lingual NLP. His work spans healthcare informatics, music informatics, and machine translation. He has collaborated on projects like MIP-Frontiers and contributed to advancements in multimodal stuttering detection and stock price prediction models. Professional roles also include software development stints at Google Summer of Code and teaching at IIIT Hyderabad. His outreach initiatives aim to promote computer science education and accessibility.

• Orthopedic Surgery
• Spine Surgery
• Minimally Invasive Surgery
• +۴ مورد دیگر

Dr. Ram Kiran Alluri is an Clinical Assistant Professor at the Keck School of Medicine, University of Southern California , specializing in Orthopaedic Spine Surgery at the USC Spine Center . His clinical focus includes cervical spine surgery , minimally invasive techniques , and robotic-assisted procedures for adult spinal deformity and complex revision surgery . Undergraduate & Medical Education: University of California Los Angeles (UCLA) Residency: Orthopaedic Surgery at USC Fellowship: Minimally Invasive & Adult Spinal Deformity at Hospital for Special Surgery Dr. Alluri's research emphasizes clinical outcomes analysis and navigational technology in spine surgery. With over 80 peer-reviewed publications and 130+ conference presentations , his work spans topics like AI in medical education , spin bias in systematic reviews , and robotic surgery efficiency . Key awards include the SMISS Young Surgeon Grant and AAOS Best Poster Award . He holds active memberships in AAOS , NASS , and AO Spine .

Wouter Wilsonمشاهده پروفایل

استادیار

• Orthopaedic Biomechanics
• Cartilage Mechanics
• Finite Element Modeling
• +۲ مورد دیگر

Wouter Wilson is a part-time Assistant Professor in the Orthopaedic Biomechanics group at TU/e, where he supervises PhD students in biomechanics and finite element modeling. His research examines cartilage mechanics, orthopedic implants, and tissue engineering solutions. He holds an MSc in Mechanical Engineering and PhD from TU/e, with previous industry experience at GKN/Fokker Landing Gear as Engineering Manager. Current research focuses on computational biomechanics of spinal interventions, biomaterial development, and implant optimization. Publications demonstrate expertise in patient-specific modeling, mechanical testing of engineered tissues, and implant performance analysis. Research consistently addresses clinical translation challenges in orthopedics through experimental and computational approaches. Currently at Sioux Technologies as Senior Group Lead while maintaining academic affiliations.

• Biomedical Engineering
• Orthopaedic Surgery
• Medical Imaging
• +۳ مورد دیگر

Riaz Khan is an Adjunct Professor at the University of Western Australia (UWA), affiliated with the School of Physics, Maths and Computing and the Department of Computer Science and Software Engineering. His research focuses on interdisciplinary applications of technology in healthcare, particularly in orthopaedic surgery, biomedical engineering, and medical imaging. He has contributed to advancements in surgical techniques, pain management, and rehabilitation technologies through collaborative projects. Key research areas include total knee arthroplasty optimization, precision bone shaping via laser ablation, smartphone-based motion tracking for post-surgical recovery, and analgesia protocols for orthopaedic patients. He has co-authored over 27 peer-reviewed publications and contributed to a Cochrane Review on patella resurfacing techniques. Dr. Khan has secured research funding, including a grant from Healthway for a smoking cessation initiative linked to hospital admissions (2009–2010). His work aligns with UN Sustainable Development Goals related to good health and well-being. Collaborations span biomedical optics, surgical innovation, and clinical outcome measurement.

Danial Roshandelمشاهده پروفایل

پژوهشگر ارشد

• Ocular Surface Disorders
• Limbal Stem Cell Transplantation
• Dry Eye Disease
• +۳ مورد دیگر

Roles & Affiliations: Danial Roshandel holds the position of Adjunct Senior Research Fellow at the University of Western Australia (UWA) Medical School and the Centre for Ophthalmology and Visual Science (affiliated with the Lions Eye Institute). His academic journey includes roles as an Assistant Professor at Shahid Beheshti University of Medical Sciences (2015–2018) and Consultant Ophthalmologist at Kamkar Hospital (2014–2015). Primary University: The University of Western Australia Medical School: UWA Medical School Research Centre: Centre for Ophthalmology and Visual Science Education: Doctor of Philosophy (PhD) in Ophthalmology, UWA (2018–2022) Specialist in Ophthalmology, Shahid Beheshti University of Medical Sciences (2010–2014) Doctor of Medicine (MD), Golestan University of Medical Sciences (2003–2010) Research Interests: Focus on ocular surface disorders, limbal stem cell transplantation, dry eye disease, and genetic eye diseases. Key areas include biobanking for congenital aniridia (2022–present), retinitis pigmentosa progression monitoring (2018–2021), and corneal neovascularization (2014–2018). Publications & Research Trends: Recent work emphasizes stem cell therapies, adaptive optics imaging, and genetic predisposition studies. Notable contributions include studies on limbal stem cell differentiation and clinical applications of induced pluripotent stem cells. Awards: University Postgraduate Award (2018) Professional Activities: Serves as a peer reviewer for Scientific Reports , Retina , and Molecular Vision . Active in professional organizations like the Iranian Society of Ophthalmology and the Islamic Republic of Iran Medical Council. Labs & Collaborations: Collaborates with the Ocular Tissue Engineering Laboratory and the Lions Eye Institute. Research networks span Australia, Iran, and international partners in adaptive optics and genetic studies.

• Robotic Surgery
• Artificial Intelligence in Surgery
• Surgical Training
• +۳ مورد دیگر

Andrew Ng serves as a Clinical Assistant Professor of Neurology (Clinician Educator) at the University of Southern California, focusing on the integration of artificial intelligence and robotics into surgical practice. His clinical educator role emphasizes advancing surgical training methodologies and performance assessment systems. His primary research interests include: Robotic surgery systems and implementation Artificial intelligence applications in surgical performance analysis Telesurgery frameworks and safety protocols Surgical training feedback mechanisms Urological and neurological surgical outcomes Objective assessment of surgical skills Analysis of his 2022-2025 publications reveals a dominant focus on AI-driven surgical performance metrics, particularly in robotic prostatectomy. His work establishes critical links between intraoperative technical skills and long-term patient outcomes, with significant contributions to nerve-sparing quantification and real-time feedback systems. The research consistently bridges computer vision, machine learning, and clinical surgical practice to develop predictive models for recovery metrics. Dr. Ng actively contributes to surgical consensus statements through organizations like the Society of Robotic Surgery, developing standardized frameworks for telesurgery implementation and surgical gesture analysis. His collaborative work spans engineering teams for AI tool development and clinical teams for surgical outcome validation, positioning him at the forefront of surgical technology translation.

• Hip and Knee Replacement
• Robotic-Assisted Surgery
• Computer-Assisted Navigation Technologies
• +۳ مورد دیگر

Daniel A. Oakes, MD, is a Professor of Clinical Orthopaedic Surgery at the Keck School of Medicine of USC and serves as Director of the USC Joint Replacement Program. With expertise in knee and hip replacement/reconstruction, he pioneered robotic total knee surgery at Keck Medical Center in 2018 and focuses on computer-assisted navigation technologies, porous metal implants, and infection prevention. Harvard Medical School graduate Mayo Clinic fellowship (recipient of Mark B. Coventry Award) Dual expertise in clinical practice and translational research His research spans robotic surgery outcomes , implant longevity , and gene therapy for bone repair (notably AAV-based delivery systems). Publications from 2000-2025 reflect evolving priorities in joint replacement, including pandemic-era surgical trends and biofilm disruption technologies. Recognized as a Top Doctor by multiple organizations, he has received teaching excellence awards and served as Joint Replacement Fellowship Director. Current work emphasizes 3D-printed scaffolds , non-cemented stems , and metal artifact reduction MRI for prosthetic evaluation.

Mamoun T. Mardiniمشاهده پروفایل

استادیار

• Data Science
• Wearables
• Health Informatics
• +۳ مورد دیگر

Mamoun T. Mardini is an Assistant Professor at the Institute on Aging , University of Florida. His research focuses on leveraging data science, wearable technologies, and machine learning to address challenges in gerontology and healthcare. Education : Ph.D. Computer Science (2018), University of North Carolina M.S. Computer Engineering (2013), American University of Sharjah B.S. Computer Engineering (2009), Jordan University of Science and Technology Research Interests : Dr. Mardini’s work emphasizes: Development of AI-driven frailty assessment tools for surgical patients Applications of smart wearables for monitoring mobility and pain in older adults Machine learning models for predicting cardiovascular outcomes and disparities Analysis of social determinants of health using real-world data Key Contributions : His studies include: Pioneering work on reducing unnecessary TEE procedures using AI Development of the ROAMM smartwatch platform for ecological momentary assessment Investigations into racial disparities in healthcare outcomes using ML Awards : No awards explicitly mentioned in the provided data. Labs/Teams : Active in the Division of Epidemiology and Data Science in Gerontology (EDGE) .