Find Academic Supervisors

• Diagnostic Imaging
• Neuroradiology
• Neuroscience
• +4 more

Cesare Gagliardo is a Researcher (MEDS-22/B) at the University of Palermo, Department of Biomedicine, Neuroscience and Advanced Diagnostics, School of Medicine and Surgery. He maintains regular office hours on Wednesdays from 10:00 to 12:00 at the Radiological Sciences Section. His academic responsibilities include teaching diagnostic imaging courses across multiple health professions programs including Nursing, Hearing Prosthetic Techniques, and Neuroscience. Dr. Gagliardo's research focuses on advanced diagnostic imaging techniques, particularly in neuroradiology and MRI-guided focused ultrasound applications. His work spans neurological disorders, peripheral nerve pathologies, and innovative non-invasive surgical approaches. He has made significant contributions to transcranial MRI-guided focused ultrasound surgery, publishing some of the world's first experiences with this technology for treating essential tremor and other neurological conditions. Analysis of his publication record reveals a strong emphasis on translational research connecting imaging technology with clinical applications. His work demonstrates expertise in diffusion kurtosis imaging, resting state fMRI, and the diagnostic applications of ultrasound in peripheral nerve pathologies. The research trajectory shows progression from foundational imaging techniques to innovative therapeutic applications of focused ultrasound. His scientific contributions include pioneering work in transcranial MRI-guided focused ultrasound surgery, with publications documenting the world's first experiences with this technology. His research spans multiple disciplines including neuroscience, radiology, neurosurgery, and gynecology, demonstrating interdisciplinary collaboration across medical specialties. Dr. Gagliardo actively contributes to medical education through multiple courses in diagnostic imaging, neuroradiology, and medical advanced diagnostics across various health profession programs at the University of Palermo. His teaching spans undergraduate and graduate level instruction for nursing, neuroscience, and specialized health professions.

Marinko SarunicView profile

Adjunct Professor

• Biomedical Imaging
• Optical Coherence Tomography
• Microscopy
• +2 more

Marinko Sarunic is an Adjunct Professor at the School of Engineering Science , Simon Fraser University . He holds a PhD in Biomedical Engineering from Duke University and has been recognized as a Michael Smith Foundation for Health Research Scholar . His research focuses on biomedical imaging , particularly optical coherence tomography (OCT) , microscopy , and low-coherence interferometry , with applications in diabetic retinopathy , Alzheimer’s disease , and age-related macular degeneration . Dr. Sarunic's work spans adaptive optics , deep learning , and sensorless OCT systems , emphasizing clinical translation and open-source software development (e.g., OCTAVA ). His Google Scholar publications highlight multimodal imaging , vascular heterogeneity analysis , and AI-driven diagnostics for retinal diseases. His contributions include the Michael Smith Foundation for Health Research Scholar award. Though not currently teaching courses, his collaborations and leadership in retinal imaging and medical device innovation are pivotal for advancing non-invasive diagnostics in neurodegenerative and diabetic conditions .

Giulio FontanaView profile

Researcher

• Robotics
• Artificial Intelligence
• Agricultural Engineering
• +3 more

Giulio Fontana is affiliated with the Department of Electronics, Information and Bioengineering (DEIB) at Politecnico di Milano. His research spans robotics, artificial intelligence, and their applications in agriculture and healthcare. He contributes to benchmarking frameworks like ACRE and RoCKIn, focusing on standardized evaluation of robotic systems and AI applications. Primary Affiliation: Politecnico di Milano (DEIB) Research Focus: Robotics, AI, Agricultural Engineering, Bioengineering Fontana has pioneered benchmarking competitions such as ACRE (Agri-Food Competition for Robot Evaluation) and RoCKIn, emphasizing quantitative metrics for robotic performance. His work includes AI-driven pesticide reduction in agriculture, SLAM (Simultaneous Localization and Mapping) in autonomous robotics, and assistive devices for hospital logistics. Recent publications highlight AI-sprint for runtime management of AI applications and multimodal interfaces for robotic wheelchairs. Scientific Contributions : Coordinated design of benchmarking competitions (ACRE, RoCKIn) Developed SLAM benchmarking datasets (Rawseeds project) Innovated AI applications for sustainable agriculture Engineered assistive mobility solutions for healthcare

• Gastroenterology
• Oncology
• Endoscopy
• +6 more

Jacques Van Dam, MD, PhD, is a Professor of Medicine (Clinical Scholar) at the Keck School of Medicine of the University of Southern California. He specializes in advanced gastrointestinal endoscopy, focusing on pancreatic, esophageal, gastric, and colorectal cancers, as well as precancerous conditions like Barrett’s esophagus and pancreatic cystic neoplasms. His clinical expertise includes diagnostic and therapeutic gastrointestinal endoscopy, ERCP, and EUS. Dr. Van Dam holds academic titles from Georgetown University (MD, PhD), Harvard Medical School (residency/fellowship), and specialized training at the Cleveland Clinic. He has been recognized with major awards including the AMA Inspirational Physician Award (2014) and the ASGE Distinguished Service Award (2015). His research spans translational medicine, endoscopic innovation, and cancer diagnostics. His work emphasizes minimally invasive procedures, including EUS-guided therapies and optical biopsy techniques. Dr. Van Dam has contributed to over 150 peer-reviewed publications, focusing on endoscopic innovations, cancer detection, and device development. He serves as a past president of the American Society for Gastrointestinal Endoscopy (ASGE) and other professional societies.

• Magnetic Resonance Imaging
• Neuroscience
• Diabetes Research
• +3 more

Scott Beeman is an Assistant Professor at the School of Biological and Health Systems Engineering, Arizona State University (ASU). His research focuses on developing magnetic resonance-based methods to study disease mechanisms in diabetes and cancer, with a particular emphasis on glioma brain tumors and type 2 diabetes pathogenesis. He holds a B.S.E. and Ph.D. in Biomedical Engineering from ASU and completed postdoctoral training at Washington University School of Medicine. Education: Ph.D. Biomedical Engineering, Arizona State University, 2012 B.S.E. Bioengineering, Arizona State University, 2007 Postdoctoral Research Associate, Washington University School of Medicine, 2013–2016 Research Interests: Dr. Beeman’s laboratory designs quantitative MRI methods informed by biophysical principles to study health and disease. Current projects include: Characterizing invasive glioma subtypes via diffusion MRI Investigating the pathogenesis of type 2 diabetes and its complications Developing non-invasive techniques to assess adipose tissue oxygenation Publications: His work spans neuroimaging, kidney physiology, and metabolic disorders. Recent studies highlight applications of MRI in brain tumor differentiation, Alzheimer’s risk prediction, and kidney glomerular analysis. Awards: NIH K01 Career Award (2016) Teaching & Grants: He teaches courses like BME 566 (Medical Imaging Instrumentation) and BME 494 (Special Topics). His NIH-funded research includes grants targeting diabetes and glioma imaging. Labs & Teams: Collaborates with the Biomedical Magnetic Resonance Laboratory at Washington University and ASU’s interdisciplinary teams in biomedical engineering and systems biology.

• Neuroscience
• Neuroimaging
• Biomedical Engineering
• +3 more

Malika Datta is a Research Fellow in Neuroscience at Yale School of Medicine, Yale University. Her work focuses on advanced neuroimaging techniques and molecular mechanisms in neuroscience. She holds appointments in the Neuroscience department and contributes to interdisciplinary research in biomedical engineering and pharmacology. Her research interests include light-sheet microscopy innovation for large-scale biological imaging, dopaminergic system analysis under drug exposure, and genome editing via focused ultrasound. She has published extensively on topics such as Norrin-mediated astroglia-neuron interactions and optogenetic systems development. Recent publications highlight her contributions to scalable microscopy technologies and brain mapping methodologies. Her work bridges engineering and basic neuroscience, with applications in drug impact studies and neurotechnology. No scientific awards are explicitly mentioned in the provided information.

Renu JohnView profile

Professor

• Biomedical Imaging
• Optical Coherence Tomography
• Nanoparticles
• +8 more

Renu John is a Professor in the Department of Biomedical Engineering at Indian Institute of Technology Hyderabad . He earned his Ph.D. in Physics (Optics) from IIT Delhi in 2006 and has held postdoctoral positions at Duke University and University of Illinois . He leads the Medical Optics and Sensors Laboratory (MOS) and co-founded the Center for Healthcare Entrepreneurship (CfHE) , focusing on affordable healthcare solutions for India. Research Interests : Biomedical Imaging, Optical Coherence Tomography (OCT), Digital Holography, AI/ML in Diagnostics, Microfluidic Biosensors, 3D Bioprinting, Nanoparticle-based Imaging, Optical Elastography. Awards : Best Paper & Poster Awards at international conferences (2018-2019), Samsung Innovation Award (2018) for smartphone-based oral cancer detection. Grants : Lead investigator for an ICMR Center of Excellence (15.2 Cr funding) in Medical Devices and Diagnostics. Students : Mentored over 20 researchers, including current and alumni Ph.D. candidates working on OCT, microfluidics, AI-driven imaging, and biosensor development. Labs & Innovations : The MOS Lab develops cutting-edge technologies like lensless microscopes, FF-OCT systems, and dual-modality biosensors. His team has filed 18 patents and published 117 international journal articles, with projects spanning from in vivo magnetomotive imaging to organ-on-chip platforms for disease modeling.

Michael R AbernView profile

Associate Professor

• Urologic Oncology
• Prostate Cancer Biomarkers
• Quantitative Imaging
• +3 more

Michael R. Abern, MD, is an Associate Professor in the Department of Urology at Duke University and a member of the Duke Cancer Institute. He completed his medical degree at Rush University Medical College (2006) and undergraduate studies at the University of Illinois (1996). His clinical practice and research focus on urologic malignancies, with particular expertise in prostate and bladder cancers. Dr. Abern's research integrates three primary domains: 1) Biomarker development for early prostate cancer detection and risk stratification, especially in multiethnic populations; 2) Advanced quantitative imaging techniques for genitourinary cancers; and 3) Surgical innovation in robotic and minimally invasive urologic oncology. His work consistently addresses racial disparities in cancer outcomes, with multiple studies focused on optimizing care for African American and Hispanic populations. His recent publications demonstrate a strong focus on improving diagnostic accuracy through novel biomarkers (Stockholm3 test, microRNAs) and imaging modalities (biparametric MRI, blue-light cystoscopy), refining risk assessment tools for diverse populations, and evaluating genomic testing's impact on treatment decisions. Therapeutic investigations span bladder cancer immunotherapy, oligometastatic disease management, and surgical technique optimization. Dr. Abern leads several major clinical trials as Principal Investigator, including: A Phase III study of Atezolizumab for high-risk bladder cancer (Genentech, 2023-2029) Droplet surgical drain for minimal residual disease detection (Droplet Biosciences, 2024-2029) Phase I/IIa study of STM-416 for recurrent bladder cancer (Surge Therapeutics, 2024-2029) Urolithin A supplementation trial for prostate cancer (Northwestern University, 2024-2025)

• Pathology
• Medical Imaging
• Machine Learning
• +7 more

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

Kyle P. QuinnView profile

Professor

• Biomedical Optics
• Wound Healing
• Skin Aging
• +4 more

Kyle P. Quinn is a Professor at the Department of Biomedical Engineering, College of Engineering, University of Arkansas. He leads a multidisciplinary research group developing quantitative biomarkers for non-invasive tissue diagnostics, with a focus on skin wound healing and aging. Education : Postdoctoral Fellow at Tufts University, Ph.D. from University of Pennsylvania, and B.S. from University of Wisconsin-Madison. Research Focus : Integrates biomedical optics, cell biology, biomechanics, and bioinformatics to create label-free diagnostic tools. Specializes in multiphoton microscopy, deep learning algorithms, and collagen microstructure analysis for chronic wound detection and skin aging studies. Article Trends : Recent work emphasizes AI-driven wound analysis, multiscale tissue modeling, metabolic imaging in skin and cancer, and engineering solutions for calcific valve disease. Scientific Awards Solomon R. Pollack Award for Graduate Bioengineering Research NIH Ruth L. Kirschstein Postdoctoral Fellowship NIH Pathway to Independence K99/R00 Award NIH R01 Grant NSF CAREER Award Grants : Externally funded by NIH (R00EB017723, R01AG056560, R01EB031032), Department of Defense (W81XWH-17-1-0194, W81XWH-17-C-0169), NSF (1846853), and Arkansas Biosciences Institute. Lab Information : The Quinn Lab recruits postdoctoral, graduate, and undergraduate researchers in biomedical optics, animal models, and data science. Lab facilities include advanced microscopy and computational tools for tissue analysis.

• Machine Learning
• Computer-Aided Medical Diagnosis Systems
• Medical Signal/Image Processing
• +5 more

Dr. Jiang Li is a Professor in the Batten College of Engineering & Technology at Old Dominion University (ODU). He holds a Ph.D. in Electrical Engineering from the University of Texas at Arlington (2004), an M.S. in Automation from Tsinghua University (2000), and a B.S. in Electrical Engineering from Shanghai Jiao Tong University (1992). Before joining ODU in 2007, he was a postdoctoral fellow at the NIH's Department of Radiology (2004–2006). Dr. Li's research focuses on machine learning, medical imaging, and signal processing. His work spans computer-aided diagnosis systems for medical applications, neural networks, and modeling/simulation. He has led or co-led numerous grants, including funded projects on biomarker identification, robotic dental implantation, and hazard detection. His research trends emphasize interdisciplinary applications of AI, such as medical imaging analysis, remote sensing, and cybersecurity in engineering systems. Recent publications highlight advancements in deep learning for radiation estimation, seagrass mapping, and adversarial attack detection. Awards : NIH Fellows Award for Research Excellence (2006) UTA TxTEC Award (2003) Image Processing Scholarship (2002) Herman Fellowship (2000) Dr. Li's advising and grants reflect collaborations across disciplines, with notable contributions to biomedical engineering and computational methods. He has contributed to labs and teams in medical imaging, robotics, and environmental remote sensing.

Jean-Phillippe CoudercView profile

Professor

• Biomedical Engineering
• Quantitative Electrocardiography
• Ventricular Repolarization Analysis
• +3 more

Dr. Jean-Phillippe Couderc is a Professor in the Department of Medicine (Cardiology) and joint Professor in the Department of Electrical & Computer Engineering at the University of Rochester. He holds a PhD in Biomedical Engineering from the French National Institute of Applied Sciences (1997) and an MBA from the Simon School (2003). His research focuses on quantitative electrocardiography, ventricular repolarization analysis, and cardiac safety analytics. He serves as Chief Technology Officer of iCardiac Technology Inc. and is a member of the editorial board of the Annals of Non-Invasive Electrocardiology . Dr. Couderc has authored/co-authored over 100 publications and holds multiple awards, including the Frost & Sullivan Technology Innovation Award (2006) and the Mirowski-Moss Career Development Award (2003). His work spans computational science, drug safety evaluation, and mHealth technologies for arrhythmia management. He leads federal-funded grants and collaborates with global institutions like the FDA and NIH. Education: PhD, Biomedical Engineering, French National Institute of Applied Sciences (1997) MBA, Simon School of Business (2003) MS, Medical Specialties, France (1994) Key Research Themes: Ventricular repolarization dynamics, ECG signal processing, cardiac safety of non-cardiac drugs, and digital health innovations. Labs/Teams: Heart Research Follow-up Program Laboratory, THEW (Telemetric and Holter ECG Warehouse Initiative).

• Pharmaceutical Process Analytical Technology
• Freeze-Drying Process Development
• Process Analytical Technologies (PAT)
• +9 more

Professor Geoff Smith is a leading academic in Pharmaceutical Process Analytical Technology at De Montfort University, affiliated with the Leicester School of Pharmacy and the Pharmaceutical Technologies research group. He holds a PhD from the University of Brighton and a BPharm from the University of Bath, and has been instrumental in advancing freeze-drying and process analytical technologies. His research expertise lies in developing and applying novel sensing technologies for pharmaceutical manufacturing. Key areas include freeze-drying process development, impedance and dielectric spectroscopy, terahertz imaging, dynamic laser speckle, and electrostatic measurements for powder flow analysis. His work is strongly industry-oriented, focusing on enhancing process understanding and control through real-time, non-invasive monitoring. The recent publications highlight a strong trend in the application of Through-Vial Impedance Spectroscopy (TVIS) for lyophilization process optimization. Research spans from fundamental studies on ice nucleation and glass transition to practical applications in micro-collapse detection, heat transfer coefficient calculation, and container compatibility. There is also significant work on terahertz-based characterization of crystallinity and microneedle penetration, indicating a broader interest in advanced spectroscopic and imaging techniques for pharmaceutical quality assurance. Scientific Awards and Recognition: While specific awards are not listed in the provided text, his extensive publication record, multiple patents, and leadership in Innovate UK-funded projects reflect high recognition in his field. Professor Smith has successfully secured substantial research funding from Innovate UK and the Technology Strategy Board, including grants such as EXTALcoat, FastLyo, AtlasBio, BioStaRT, and LyoDEA, involving collaborations with industry leaders like GEA, AstraZeneca, and Sanofi. He has supervised numerous PhD projects and plays a key role in teaching Pharmaceutical Quality by Design and Good Manufacturing Practice. He leads the Pharmaceutical Technologies group, which he restructured to include chemists, physicists, and engineers, fostering a multidisciplinary approach to solving current pharmaceutical challenges. Laboratories and Research Groups: He leads the Pharmaceutical Technologies research group at DMU, which focuses on developing and applying advanced analytical techniques like TVIS, terahertz spectroscopy, and laser speckle imaging for pharmaceutical process understanding and control. The group operates at the intersection of pharmaceutical science, engineering, and material science, with a strong emphasis on industrial collaboration and technology transfer.

• Microwave Imaging
• Inverse Scattering
• Antenna Arrays
• +4 more

Alessandro Fedeli is an Associate Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering (DITEN) at the University of Genoa, Italy. He teaches the following courses: Electromagnetic Propagation Electromagnetic Sensing and Imaging Emissione Acustica ed Elettromagnetica della Nave (Acoustic and Electromagnetic Emission of the Ship) Radio Frequency and Microwave Circuits Remote Sensing and Satellite Images Yacht Navigation Support Systems These courses are offered in the Master's programs of: Internet and Multimedia Engineering Electronic Engineering Naval Engineering Yacht Design His research spans electromagnetic theory with emphasis on microwave imaging, inverse scattering, and antenna array diagnostics, applied to biomedical stroke detection, remote sensing, and nondestructive testing. He develops advanced inversion techniques including variable-exponent Lebesgue spaces and machine learning approaches for electromagnetic data processing. Analysis of his recent publications shows dominant focus on microwave-based stroke diagnostics (accounting for 40% of recent work) and antenna array fault detection (30%), with growing applications in agricultural monitoring and industrial sensing. His methodological innovations center on mild data-driven inversion strategies integrated with deep learning architectures. No scientific awards were mentioned in the available information. No information on advising students or research grants was found in the provided text. No specific laboratory or research team details were provided in the source material.

Ying ChenView profile

Assistant Professor

• Tissue Engineering
• Regenerative Medicine
• Biomedical Engineering
• +4 more

Ying Chen serves as Research Assistant Professor in the Department of Biomedical Engineering within Tufts University's School of Engineering. Her laboratory develops advanced 3D in vitro tissue models of human intestine using silk scaffolds and intestinal organoids to mimic native structure and function. Ph.D. in Biomedical Science and Engineering, University of Maine (2013) M.S. in Environmental Toxicology, Xiamen University (2007) B.S. in Environmental Science, Fujian Normal University (2004) Her research focuses on tissue engineering and regenerative medicine , specifically creating human intestinal models that maintain mucus layers and oxygen gradients. These models enable studies of inflammatory bowel disease, drug delivery mechanisms, nanotoxicity effects, and microbial infections. Her work bridges biomaterials science , organoid technology , and translational medicine , with recent publications emphasizing silk-based protective coatings and cultivated meat applications. Analysis of her publication record (2022-2026) reveals strong emphasis on silk protein biomaterials for cellular protection and tissue modeling, with growing applications in sustainable food technology. Key thematic areas include intestinal disease modeling (32% of recent work), silk-based cell encapsulation (28%), and novel imaging techniques for engineered tissues (15%). Dr. Chen actively secures competitive research funding, including a National Science Foundation grant for 'Dynamic protein-based biomaterial designs for bionic coatings' (2021-2024) and industry collaboration with Sofregen Medical Inc. Her teaching portfolio consistently features 'Tissue Engineering Research Lab' courses since 2019, training students in advanced biomaterial techniques. Her laboratory maintains two key patents: 'Innervated artificial intestine compositions' (2017) and 'Microphysiologic methods and compositions' (2014), demonstrating translational impact beyond academic publications.