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Weitao WangView profile

Assistant Professor

• Head and Neck Oncology
• Facial Plastic and Reconstructive Surgery
• Skull Base Surgery
• +4 more

Dr. Weitao Wang serves as an Assistant Professor in the Department of Otolaryngology at the University of Rochester School of Medicine and Dentistry. Board-certified in both Otolaryngology-Head and Neck Surgery and Facial Plastic and Reconstructive Surgery, he practices clinically at UR Medicine and the Wilmot Cancer Institute in Rochester, NY, specializing in complex head and neck reconstruction and facial plastic procedures. Medical Degree: University of Virginia School of Medicine Residency: Otolaryngology-Head and Neck Surgery, University of Rochester Medical Center (2015-2019) Fellowship: Facial Plastic and Reconstructive Surgery, The Institute for Rehabilitation and Research (2019-2020) His research focuses on advancing head and neck reconstruction through tissue engineering (particularly bone/cartilage grafting) and optimizing surgical education via point-of-view video technology. Clinical investigations prioritize patient-reported outcomes in facial plastic surgery to enhance functional recovery and satisfaction metrics. Current work bridges engineering solutions with complex defect reconstruction. Recent publications (2020-2025) demonstrate concentrated expertise in microvascular free tissue transfer, virtual surgical planning for craniofacial defects, and innovative skull base/orbital reconstruction techniques. His work consistently addresses oncologic safety while improving functional outcomes in head and neck cancer patients, with increasing emphasis on cost-effective surgical training methodologies. Robert Joynt Kindness Award 2021 Leslie Bernstein Resident Research Grant: Optimizing bone allograft in craniofacial defect reconstruction Wallace K. Dyer Clinical Investigation Grant: Cost-effective surgeon POV video in otolaryngology training Dr. Wang secures competitive funding from the American Academy of Facial Plastic and Reconstructive Surgery to advance surgical education and reconstruction techniques. His clinical mentorship emphasizes multidisciplinary collaboration, particularly in head and neck oncology cases where tumor resection requires immediate reconstruction. Current projects integrate virtual planning with intraoperative navigation to optimize complex defect repair. He operates within the Facial Plastic and Reconstructive Surgery division at the University of Rochester, collaborating with Wilmot Cancer Institute's head and neck oncology team. His practice incorporates virtual surgical planning technology and microvascular reconstruction expertise, with active participation in multidisciplinary tumor boards for complex craniofacial cases.

Mostafa MohammadiView profile

Assistant Professor

• Neurorehabilitation Robotics
• Human-Computer Interaction
• Telerehabilitation Technologies
• +5 more

Mostafa Mohammadi is an Assistant Professor at the Department of Health Science and Technology, Aalborg University, affiliated with the Faculty of Medicine and Center for Rehabilitation Robotics. His research focuses on neurorehabilitation robotics, human-computer interaction, and telerehabilitation technologies for individuals with disabilities. Ph.D. in Biomedical Engineering (Aalborg University, 2018-2022) M.Sc. in Biomedical Engineering (Polytechnic University of Milan, 2015-2017) B.Sc. in Mechanical Engineering (Sharif University of Technology, 2011-2015) His work spans exoskeleton design, assistive robotics, and innovative interfaces like tongue-computer interfacing. Recent projects include the eMotivo digital health solution funded by Innovation Fund Denmark and intelligent tendon-driven exoskeletons for severe disabilities. Research outputs (33 total) emphasize adaptive robotics, motor impairment solutions, and wearable technologies. Collaborations span robotics, biomedical engineering, and clinical disciplines. Teaching includes courses in rehabilitation robotics, human-computer interaction, and digital systems for biomedical engineering. Scientific activities align with UN Sustainable Development Goals for quality education and reduced inequalities. Notable contributions include advancements in myoelectric interfaces and neurorehabilitation technologies.

Alan KuntzView profile

Assistant Professor

• Robot Motion Planning
• Autonomous Systems
• Robot Design Optimization
• +4 more

Alan Kuntz is an Assistant Professor at the University of Utah's Kahlert School of Computing (KSoC) and a core member of the Robotics Center. He leads the interdisciplinary Kuntz Research Lab, focusing on robotics and computational methods with medical applications, particularly in healthcare and surgery. His work spans robot motion planning, autonomous systems, and robot design optimization. Education: Ph.D. in Computer Science from the University of North Carolina at Chapel Hill, with research in the Computational Robotics Research Group. Previously a postdoctoral scholar at Vanderbilt University's Medical Engineering and Discovery Lab. Research interests include surgical robotics, continuum robots, needle steering, and medical device design. Recent projects include autonomous needle navigation, continuum lung staplers, and metamaterial-based robots. His team has published extensively on topics like kinematic modeling, uncertainty quantification, and medical intervention systems. Notable awards include the 2022 IEEE Access Best Video Award for his group's work, and mentoring over 15 students through the University of Utah's Undergraduate Research Opportunities Program. The Kuntz Lab actively collaborates on clinical applications, presenting at top conferences like IROS, Hamlyn Symposium, and ISMR. Labs/Teams: Directs the Kuntz Research Lab, known for its innovative medical robotics projects. The lab's work has been featured in Forbes and other media outlets for breakthroughs like in vivo needle steering demonstrations.

James StewartView profile

Professor

• Computer-assisted surgery
• Image processing
• Computer graphics
• +3 more

James Stewart is a Professor at Queen's University's School of Computing. His research focuses on biomedical computing and surgical navigation systems. Education: Ph.D. in Computer Science from Cornell University (1992) Location: Office Goodwin 732 Contact: Phone 613 533-3156 Research Interests Professor Stewart's work bridges computer graphics, image processing, and medical applications. Key areas include: Computer-assisted surgical navigation 3D medical visualization Geospatial data representation Robust geometric computation Human-computer interaction in clinical settings Medical imaging uncertainty analysis Scientific Awards Best Poster Award (2013) for 'Image-guided Osteochondral Autologous Autografting of the Ankle' Publications His publications span multiple domains including: Computer graphics algorithms Medical imaging techniques Geospatial visualization Biomedical engineering applications Surgical navigation systems Robust geometric computation

• Artificial Intelligence
• Machine Learning
• Medical Education Technology
• +7 more

Andrew R. Jamieson is an Assistant Professor in the Lyda Hill Department of Bioinformatics at UT Southwestern Medical Center, where he leads a research team focused on developing advanced AI systems for medical education and clinical performance assessment. He was appointed in 2019 and serves as Principal Investigator of the Jamieson Group. Institution: UT Southwestern Medical Center School: School of Health Professions Department: Lyda Hill Department of Bioinformatics Academic Rank: Assistant Professor Dr. Jamieson earned his B.A. in Physics with honors (2006) and Ph.D. in Medical Physics (2012) from the University of Chicago. His early work in computer-aided diagnosis laid the foundation for his career in AI and machine learning. Education: University of Chicago (B.A., Ph.D.) Prior Experience: GE Healthcare, Big Data Analytics Startup (First Data Scientist) Dr. Jamieson's research lies at the intersection of artificial intelligence, medical education, and bioinformatics. His team leverages multimodal data—including video, audio, and text—from the UTSW Simulation Center to train frontier AI models for automated assessment of medical student performance. His work in computational image analysis spans label-free live-cell imaging, spatial biology, and highly multiplexed immunofluorescence, with applications in cancer biology and diagnostics. He has also made significant contributions to public health through the development of the UTSW COVID-19 forecast model. The most recent publications reflect a strong trend toward AI-driven medical education tools, particularly using large language models and multimodal AI for OSCE assessment. Earlier works focus on deep learning in medical imaging, dimensionality reduction, and computer-aided diagnosis in mammography. The research consistently emphasizes interpretability, automation, and clinical translation. Scientific recognition includes being featured on the cover of Cell Systems (July 2021) for work on melanoma cell analysis. His team's development of the first automatic AI grading system for medical student OSCE notes in 2023 marks a major innovation in educational assessment. Featured on cover of Cell Systems (2021) Developed UTSW COVID-19 forecast model Pioneered AI grading system for OSCE notes (2023) Dr. Jamieson is actively involved in mentoring and graduate education. He serves as Course Director for the Master’s in Health Informatics program and contributes to nanocourses at the Clinical Informatics Center. His team includes multiple advisees and collaborators working on NLP, LLMs, and AI/ML in healthcare. He is expanding his group and seeking researchers in AI, data science, and software development. His leadership in the Bioinformatics Core Facility (2018–2021) and ongoing collaborations with pathologists and radiation oncologists demonstrate strong interdisciplinary grant and project engagement. Course Director: Master’s in Health Informatics Mentor to multiple graduate students and researchers Collaborations: Pathology, Radiation Oncology, Surgery, Clinical Informatics The Jamieson Group is a dynamic, interdisciplinary research team at the forefront of applying cutting-edge AI to medical education and clinical data analysis. The lab focuses on natural language processing, multimodal learning, and computer vision, with strong ties to the UTSW Simulation Center and Clinical Informatics Center. The team develops custom pipelines for spatial biology and imaging data and is actively expanding to meet growing research demands.

Peter KazanzidesView profile

Research Professor

• Robotics
• Medical Robotics
• Augmented Reality
• +4 more

Peter Kazanzides is a Research Professor in the Department of Computer Science at the Whiting School of Engineering, Johns Hopkins University, where he joined the faculty in 2002. His research focuses on robotics, medical robotics, augmented reality, and computer-assisted interventions with primary applications in computer-integrated surgery. His educational background includes multiple degrees from Brown University: ScB (1983) in Electrical Engineering AB (1983) in Computer Science ScM (1985) in Electrical Engineering ScM (1987) in Applied Mathematics PhD (1988) in Electrical Engineering Kazanzides is a member of the Robotics, Vision, and Graphics research group and directs the Sensing, Manipulation, and Real-Time Systems (SMARTS) laboratory. His work spans surgical robotics, mixed reality, and systems engineering, with emphasis on computer-assisted surgery in extreme environments including minimally invasive surgery, microsurgery, and space teleoperation. The SMARTS lab develops real-time sensing systems, augmented/mixed reality interfaces using head-mounted displays, high-performance motor control, and sensor fusion technologies, with strong focus on system integration and open-source platforms like the da Vinci Research Kit (dVRK). Analysis of his recent publications (2024-2025) reveals dominant trends in surgical robotics autonomy, augmented reality navigation, force estimation, and digital twin technologies. Key themes include AI-driven task automation, haptic feedback enhancement, real-time instrument segmentation, and simulation environments for surgical training, primarily leveraging the da Vinci Research Kit framework. As director of the SMARTS lab within the Laboratory for Computational Sensing and Robotics (LCSR), Kazanzides leads a collaborative ecosystem including the Computer Integrated Interventional Systems (CIIS) Lab, Advanced Medical Instrumentation and Robotics (AMIRO) Lab, Dynamical Systems and Controls Lab (DSCL), Computer Aided Medical Procedures (CAMP) Lab, Medical UltraSound Imaging & Intervention Collaboration (MUSiiC) Lab, and Photoacoustic & ULtrasonic Systems Engineering (PULSE) Lab. His lab maintains responsibility for the development and support of the open-source da Vinci Research Kit, a critical resource for surgical robotics research worldwide.

Steven RamanView profile

Clinical Professor

• MRI Imaging of Prostate Cancer
• Liver and Kidney Cancer Imaging
• Gynecological Cancers Imaging
• +7 more

Dr. Steven Raman is a Clinical Professor in the Department of Radiological Sciences at the David Geffen School of Medicine, University of California, Los Angeles (UCLA). He serves as Director of Prostate MR Imaging and Interventions, Director of the UCLA Prostate MR Imaging Research Group, Director of the Abdominal Imaging Fellowship at UCLA, and Co-director of the Fibroid Treatment Program. Dr. Raman is an expert in Abdominal and Pelvic imaging (CT, MRI, Ultrasound and X-Ray) and interventional radiology, particularly in tumor ablation and Fibroid Treatment. Dr. Raman received his MD from Keck School of Medicine of the USC in 1993. He completed his Internship in Internal Medicine at Pacific Presbyterian Medical Center in 1994, Residency in Radiological Sciences at UCSD School of Medicine in 1998, and Fellowship in Abdominal Imaging at UCLA Department of Radiology in 1999. He is board certified in Diagnostic Radiology by the American Board of Radiology since 1998. His research focuses on MRI Imaging of Prostate, Liver, Kidney and Gynecological Cancers, Thermal Ablation techniques including microwave, cryo, HIFU and Irreversible Electroporation, and the application of Artificial Intelligence in Radiogenomics. His clinical expertise spans advanced imaging techniques with minimally invasive treatments for various cancers and conditions, with particular emphasis on prostate cancer diagnosis and treatment. Dr. Raman's publication record demonstrates a strong focus on cancer imaging and treatment across multiple organ systems. His work consistently bridges advanced imaging techniques with clinical applications, particularly in prostate cancer where he has contributed significantly to MR-guided biopsy techniques, image-pathology correlation, and surgical planning. His recent work increasingly incorporates AI applications for cancer detection. Super Doctors® Southern California, 2023-2025 Top Doctors, Los Angeles Magazine, 2021 Best Doctor, 2021 Super Doctors® Southern California, 2017-2021 Leading Physicians of the World, 2021 As Director of the Abdominal Imaging Fellowship at UCLA, Dr. Raman mentors radiology fellows in advanced imaging techniques and interventional procedures. His research group focuses on developing AI to better detect aggressive prostate cancer, with recent funding of $3 million for this purpose. His clinical work at the Westwood Imaging Center focuses on minimally invasive treatments for prostate cancer, liver diseases, and fibroid treatment, with particular expertise in image-guided thermal ablation therapies. Dr. Raman leads comprehensive clinical programs including the UCLA Uterine Fibroid Program and Fibroid Treatment Program, providing state-of-the-art care for women with uterine fibroids. His work on percutaneous image-guided thermal ablation for metastatic gynecologic cancers has been recognized as safe and effective therapy, demonstrating his commitment to advancing minimally invasive treatment options.

• Vascular Biology
• Atherosclerosis
• Arterial Stiffness
• +2 more

Dr. Stella Daskalopoulou is a Senior Scientist at the Research Institute of the McGill University Health Centre (RI-MUHC) and a Professor in the Department of Medicine at McGill University's Faculty of Medicine and Health Sciences. She specializes in translational cardiovascular research with a focus on vascular health, atherosclerosis, and hypertension management. Senior Scientist, RI-MUHC Glen site Professor, Department of Medicine, McGill University Member, Cardiovascular Health Across the Lifespan Program Research Focus: Her work integrates biomedical technology with clinical investigation to identify early vascular impairment markers. Key areas include: Arterial stiffness and hemodynamic assessment Adiponectin signaling pathways in atherosclerosis Sex-specific cardiovascular risk stratification Biomarker discovery for plaque instability Pregnancy-related vascular complications Machine learning applications in plaque classification Scientific Engagement: Dr. Daskalopoulou contributes to hypertension guideline development (2024 ESC Guidelines) and explores environmental impacts on vascular health (household pollution studies). Her recent publications emphasize: Deep learning for plaque characterization Sex hormone receptor pathways in atherosclerosis Adipokine interactions with HDL metabolism Clinical decision tools for preeclampsia prediction Laboratory: Leads the Vascular Health Unit at RI-MUHC, combining histopathology, immunophenotyping, and advanced imaging for translational research.

X. Lucas LuView profile

Professor

• Biomechanical Engineering
• Osteoarthritis
• Cartilage Biomechanics
• +3 more

X. Lucas Lu is a Professor in the Department of Mechanical Engineering at the University of Delaware. His research focuses on biomechanical engineering, specifically investigating osteoarthritis and cartilage biomechanics. He holds a PhD in Biomedical Engineering from Columbia University. Research Interests: Prevention and treatment of post-traumatic osteoarthritis Mechanical forces' role in cartilage and bone cell signaling Advanced techniques: nanotechnology, proteomics, computational modeling Specific projects: statin therapy for osteoarthritis prevention, calcium signaling in chondrocytes, resveratrol treatments, temporomandibular joint biomechanics, post-surgery rehabilitation protocols, and tumor cell detection with nano-materials Publications emphasize global education policy, teacher effectiveness, and health systems in developing regions, though these appear unrelated to his stated biomedical engineering focus. Collaborates with graduate student Annie Porter on undergraduate research initiatives. Labs/Teams: Active in biomechanics research labs at the University of Delaware, mentoring students in interdisciplinary projects combining engineering and clinical applications.

Antonio PlazaView profile

Professor

• Hyperspectral Image Analysis
• Remote Sensing
• High-Performance Computing
• +4 more

Antonio Plaza is a Full Professor at the University of Extremadura, Spain, and Head of the Hyperspectral Computing Laboratory. With over 600 publications, he is a leading expert in hyperspectral data processing and parallel computing of remote sensing data. He serves as IEEE Fellow and has received numerous accolades, including the 2019 Excellent Teaching Award and multiple Highly Cited Researcher recognitions. Research Interests : His work bridges Hyperspectral Image Analysis , Medical Imaging , and High-Performance Computing . Recent projects focus on 3D anatomical modeling, AI-driven surgical tools, and deep learning applications for aortic dissection segmentation. Scientific Awards : 2019 Highly Cited Researcher (Geosciences) 2015 IEEE Fellow 2019 Excellent Teaching Award 2018 Highly Cited Researcher (Cross-Field) 2002 Best PhD Dissertation, University of Extremadura Editorial Leadership : Served as Editor-in-Chief of IEEE Transactions on Geoscience and Remote Sensing (2013–2017) and held multiple committee roles in IEEE GRSS. His articles reflect a shift from remote sensing to medical imaging, with a focus on Aortic Dissection Segmentation , Skull Reconstruction , and AI-driven Medical Tools .

• robotic tactile sensing
• learning objects by touch
• soft and flexible robot design
• +1 more

Dr. Hongbin Liu is a Senior Lecturer at the Department of Informatics, King’s College London, UK, affiliated with the Centre for Robotics Research. His work focuses on robotic tactile sensing, soft robot design, and haptic exploration. Research Interests: Robotic tactile sensing Learning objects by touch Soft and flexible robot design Modelling of soft interactions Dr. Liu’s recent publications highlight advancements in robotics and sensor technology , particularly in tactile perception, medical device design, and continuum robot navigation. His work integrates Bayesian classifiers for autonomous object recognition, polymer-based optical waveguides for triaxial tactile sensors, and deep learning for medical diagnostics. Collaborations span institutions like Imperial College London, The University of Hong Kong, and Medical University of Vienna. Professional Affiliation: King’s College London Department of Informatics Centre for Robotics Research (research group)

Jonathan MamouView profile

Professor

• Quantitative Ultrasound Imaging
• Biomedical Engineering
• Medical Imaging
• +5 more

Jonathan Mamou is a Professor of Electrical Engineering in Radiology at Weill Cornell Medical College since 2024. His research focuses on quantitative ultrasound imaging, biomedical engineering, medical imaging, and acoustic microscopy. Ph.D., University of Illinois (2005) M.S., University of Illinois (2002) B.S., Telecom Paris (2000) His research bridges electrical engineering and radiology, developing advanced ultrasound techniques for medical diagnostics. Key areas include quantitative acoustic microscopy , biomechanical tissue analysis , and machine learning in ultrasound imaging . Recent work spans prostate cancer detection , placental microstructure characterization , and myopia-related scleral changes . His publications (2025–2023) highlight innovations in high-frequency ultrasound for ophthalmology, quantitative imaging for cancer diagnostics, and quantum-driven resolution enhancement in acoustic microscopy. Grants from the Melanoma Research Alliance , National Institute of Biomedical Imaging & Bioengineering , and Stand Up To Cancer support his work on pancreatic cancer screening , interstitial lung diseases , and radiotherapy toxicity assessment .

Dimitris MaroulisView profile

Professor

• Data Acquisition
• Real-Time Systems
• Pattern Recognition
• +6 more

Dimitris Maroulis is a Professor at the Department of Informatics and Telecommunications, University of Athens, leading the Real-Time Systems and Image Analysis Lab (RTS-image). With over 20 years of experience in data acquisition and real-time systems, and 15 years in image/signal analysis, he collaborates extensively with Greek and European hospitals in biomedical informatics. He has led 5 R&D projects and authored 150+ papers with 1400+ citations. University of Athens: Professor (2000–present) Meudon Observatory: Research Fellow (3 years) & Long-term Collaborator (10+ years) Research Interests focus on real-time systems , image/signal processing , and biomedical applications . Key areas include automated segmentation of proteomic images, noise removal methods, and stereo image coding. His 15 most recent publications (2003–2012) span 3D imaging , medical image analysis , and biomedical informatics , with sub-fields like autostereoscopic displays, wavelet-based coding, and computer-aided diagnosis. Awards : Best Paper Award (2012: Integral Image Analysis) Projects include European and national R&D initiatives in image analysis and real-time systems. Labs : RTS-image Lab develops methodologies for biomedical and proteomic applications.

• Biomechanics
• Biomedical Engineering
• Computational Modeling
• +6 more

Lindsey Westover, PhD, PEng, serves as an Associate Professor in the Department of Mechanical Engineering and Associate Dean in the Faculty of Engineering at the University of Alberta. Her research and teaching activities are centered in the Biomedical Engineering program, with her laboratory located in the Donadeo Innovation Centre for Engineering (13-224, 9211 116 St, Edmonton, AB T6G 2H5). She maintains an active research profile while contributing to academic leadership through her deanship. Her educational background includes: 2018: Postdoctoral Fellowship in Rehabilitation Medicine, University of Alberta 2016: Ph.D. in Mechanical Engineering, University of Alberta 2011: M.Sc. in Mechanical Engineering, University of Calgary 2007: B.Sc. in Mechanical Engineering, University of Calgary Dr. Westover's research program spans biomechanics and biomedical engineering with emphasis on noninvasive assessment of biological structures, vibration analysis for percutaneous implants, joint biomechanics (ligaments and cartilage), spinal deformity analysis through asymmetry metrics, mechanical testing of biological tissues, and computational modeling of biological systems. Her work integrates laboratory experiments, computational methods, and in vivo studies to develop innovative diagnostic and therapeutic approaches. Analysis of her 15 most recent publications (2018-2020) reveals consistent focus on bone mechanics, implant stability, and symmetry analysis across orthopedics, audiology, and dentistry. Key themes include osseointegration evaluation using ASIST technology, pelvic/spinal deformity quantification, and computational modeling of biological structures. Her work appears in high-impact journals spanning engineering and clinical disciplines, demonstrating strong interdisciplinary collaboration. Scientific recognition includes: Nomination for Ear and Hearing 2018 Editor's Award for bone conduction device research Dr. Westover mentors graduate students through co-authorship on numerous publications and teaches core mechanical engineering courses including MEC E 451 (Vibrations and Sound), MEC E 390 (Numerical Methods), and MEC E 200 (Introduction to Mechanical Engineering). Her research is supported by collaborative grants with clinical partners and engineering colleagues. She leads biomechanics research within the Department of Mechanical Engineering, collaborating extensively with the Faculty of Rehabilitation Medicine and surgical departments. Her laboratory develops advanced testing systems like ASIST for implant stability evaluation across hearing devices and dental applications, while her computational work informs clinical approaches to scoliosis management and fracture reconstruction.

• Ultrasound
• Radiology
• Doppler Ultrasound
• +3 more

Edward G. Grant, MD, serves as a Clinical Professor of Radiology (Part-Time) at the University of Southern California (USC), where he was Chair of the Department of Radiology from 2002 to 2019. Prior to USC, he chaired the Imaging Department at Greater Los Angeles VA Healthcare System and held professorial and vice-chair positions at UCLA. His career spans over three decades in academic radiology with a focus on clinical ultrasound innovation and leadership. Dr. Grant is an internationally recognized authority in ultrasound, having pioneered neonatal cranial sonography early in his career. His research encompasses Doppler ultrasound for vascular disease diagnosis, clinical investigation of ultrasound contrast agents, PACS, and advancements in thyroid and liver imaging. He has authored four books and numerous peer-reviewed articles, establishing himself as a leading figure in diagnostic radiology. Analysis of his 15 most recent publications (2021-2025) reveals a strong emphasis on contrast-enhanced ultrasound applications across multiple organ systems, particularly in thyroid nodule characterization (TI-RADS), liver disease quantification, and renal transplant evaluation. His work also addresses emerging areas like AI integration in ultrasound reporting and environmental impacts on fetal development through the MADRES cohort study. His notable awards include: Pasadena Magazine Top Doctor (2011) Dr. Grant has served as an examiner for the American Board of Radiology for 13 consecutive years and remains an active lecturer at national and international conferences. While the provided text does not detail specific grants or student advising, his extensive publication record and leadership roles indicate significant contributions to radiology education and clinical practice advancement.