Prof. Dr. Dennis Säring is a faculty member at the University of Applied Sciences Wedel , specifically affiliated with the School of Engineering. His academic and research activities focus on Deep Learning , Medical Image Analysis , and applications of Artificial Intelligence in healthcare and biomedical imaging. He has led seminars on Deep Learning topics and supervised student projects in Autonomous Driving at Audi's AADC 2018 competition. Research Highlights : Cardiovascular imaging, forensic age estimation via MRI, neural network-based bone segmentation, and cerebrovascular aneurysm analysis. Technical Expertise : Cardiac MRI, 3D/4D image processing, parametric mapping, and spatiotemporal data fusion. His recent publications (2018-2023) emphasize 3D MR segmentation for age assessment, CMR strain analysis in athletes, and T1/T2 mapping for myocarditis. Key collaborations include institutions like the University Medical Center Hamburg-Eppendorf and Wedler Hochschulbund, with funding for autonomous vehicle research. While no explicit scientific awards are listed, his work spans clinical cardiology, forensic radiology, and AI-driven medical diagnostics.
Massimo Mischi is a Full Professor at the Faculty of Electrical Engineering of the Eindhoven University of Technology (TU/e) and chairs the Signal Processing Systems (SPS) Division , the largest division at TU/e with over 250 researchers. He founded the Biomedical Diagnostics (BM/d) Lab in 2012, which now includes 180 researchers and clinical/industrial advisors, focusing on biomedical signal processing for diagnostics and monitoring.
Jeremy Dahl is a Professor of Radiology (Pediatric Radiology) at Stanford University School of Medicine. He directs the Ultrasound Imaging & Instrumentation Lab and serves as Director of Research Academic Affairs in the Department of Radiology since 2020. He holds multiple affiliations across Stanford including Bio-X, the Cardiovascular Institute, Wu Tsai Human Performance Alliance, Maternal & Child Health Research Institute, Stanford Cancer Institute, and Wu Tsai Neurosciences Institute. Dr. Dahl received his B.S. in Electrical Engineering from the University of Cincinnati (1999) and Ph.D. in Biomedical Engineering from Duke University (2004). His research focuses on developing ultrasonic beamforming and image reconstruction methods for diagnostic imaging applications, particularly techniques that generate high-quality images in difficult-to-image patients. His laboratory specializes in B-mode and Doppler imaging techniques that utilize additional information from ultrasonic wavefields to improve image quality and develop real-time imaging systems for clinical applications including cardiac, liver, and fetal imaging. Dr. Dahl's research has led to significant advancements in ultrasound molecular imaging platforms, sound speed estimation, aberration correction, and reverberation noise suppression. His work often bridges engineering innovation with clinical applications for cancer detection and other diseases. His recent publications demonstrate strong focus on machine learning applications in ultrasound, distributed aberration correction, and molecular imaging techniques. Fellow, American Institute of Ultrasound in Medicine (2021) Senior Member, Institute of Electrical and Electronics Engineers (2020) Distinguished Investigator Award, The Academy for Radiology & Biomedical Imaging Research (2018) Outstanding Paper Award, IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society (2011) Dr. Dahl serves in editorial roles for major journals including IEEE Transactions on Medical Imaging (2017-2024) and IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control (2013-Present). His laboratory has successfully translated numerous innovations into clinical applications, with multiple patents including recent developments in pulsed focused ultrasound therapy and speed of sound quantification.
Daniel Razansky is a Full Professor at the Department of Information Technology and Electrical Engineering, ETH Zurich, leading the Professorship for Biomedical Imaging. His research spans engineering, physics, biology, and medicine, focusing on developing advanced in vivo imaging tools like optoacoustic tomography and ultrasound neuromodulation. His recent work emphasizes multi-scale functional and molecular imaging , with applications in neuroscience , Alzheimer’s disease , and stroke diagnostics . Collaborations include National Tsing Hua University and the EU Horizon consortium SWEEPICS. Current projects target hybrid imaging systems (e.g., MRI-MSOT) and image-guided neuromodulation. Scientific awards include the IPPA James Smith Prize for his contributions. His lab has secured significant grants, including a $2.5M NIH award and SNSF funding. He mentors PhD students like Quanyu Zhou and Eva Remlova, who have received accolades for their research. The Razansky Lab at ETH Zurich’s Preclinical Imaging Center explores medical microrobotics , dynamic fluid flow imaging , and neuroimaging techniques , aiming to bridge engineering with clinical applications.
Dr. James Ashton-Miller is a prominent faculty member in the Department of Mechanical Engineering at the University of Michigan, where he directs the Biomechanics Research Laboratory. He serves as a Center Member of the University of Michigan Injury Prevention Center and maintains affiliations with the Institute of Gerontology. His interdisciplinary work bridges engineering principles with medical applications, focusing on injury prevention across sports medicine, obstetrics, and geriatrics. Dr. Ashton-Miller's educational background includes: PhD from the University of Oslo, Oslo, Norway (1978-1983) MSME from M.I.T., Cambridge, MA, U.S.A (1972-1974) B.SC. (Hons) from the University of Newcastle-upon-Tyne, Newcastle-upon-Tyne, England (1967-1972) His research focuses on the biomechanics of injury prevention across multiple critical domains. In sports medicine, he has demonstrated that some ACL injuries are overuse injuries resulting from too many sub-maximal loading cycles that prevent healing of collagen damage. In women's health, his work on childbirth injuries addresses conditions that affect more women than breast cancer. His research on fall-related injuries in older adults reveals the dual threat of physical and cognitive factors. He also investigates sciatica, disc degeneration, and develops new medical devices for screening, diagnosis and treatment. Dr. Ashton-Miller's recent publications show a strong trend toward developing practical clinical applications from fundamental biomechanical research, with emphasis on advanced imaging methods, wearable sensors, and computational modeling for pelvic floor function assessment. His work consistently aims to translate engineering insights into clinical solutions for injury prevention. His research insights have earned him numerous national and international research awards, though specific awards aren't detailed in the available information. His work involves close collaboration with clinicians and surgeons who meet weekly to discuss progress and next steps. Dr. Ashton-Miller is deeply committed to mentoring, working with NIH K-series fellows along with 1-2 post-doctoral fellows, 3-5 PhD students, 2-4 M.S. students, 4-5 undergraduate students, and 2-4 young clinicians. His research is generously supported by the National Institutes of Health, National Science Foundation, National Basketball Association, Fortune 500 companies, and startup companies including Procter & Gamble and Hologic, Inc. He directs the Biomechanics Research Laboratory and co-leads the Pelvic Floor Research Group, where his teams develop new medical devices to improve screening, diagnosis, and treatment of various biomechanical conditions. These laboratories maintain strong clinical connections, ensuring research remains grounded in real-world medical challenges.
Dr. Daniel Keeser is a Research Fellow and Research Group Leader at the Department of Psychiatry and Psychotherapy of the University of Munich (LMU) and affiliated with the NeuroImaging Core Unit Munich (NICUM). His work focuses on clinical deep phenotyping and multimodal neuroimaging, integrating advanced MRI, EEG, and non-invasive brain stimulation methods to study severe mental and neurological disorders. Research Interests: Elucidating neurobiological mechanisms of schizophrenia, major depressive disorder, and Alzheimer's disease through multimodal neuroimaging and neuromodulation. His recent publications highlight methodologies like resting-state fMRI, diffusion tensor imaging, and transcranial magnetic stimulation combined with MRI, emphasizing personalized treatment strategies. Collaborative affiliations include the University Hospital of LMU Munich and the Clinical Deep Phenotyping (CDP) Working Group. Affiliations: NeuroImaging Core Unit Munich (NICUM) Department of Psychiatry and Psychotherapy, University of Munich (LMU)
Srinivas Sridhar is a University Distinguished Professor of Physics, Biomedical Engineering, and Chemical Engineering at Northeastern University, with a secondary appointment as Lecturer on Radiation Oncology at Harvard Medical School. He previously served as Vice Provost for Research at Northeastern University (2004–2008), overseeing its research portfolio. As an elected Fellow of the American Physical Society and the American Institute of Medical and Biological Engineering, his research spans nanomedicine, neurotechnology, drug delivery, and quantitative MRI, with over 450 publications and patents. He founded the Nanomedicine Innovation Center and directs major NIH/NSF programs like CaNCURE and IGERT, focusing on undergraduate and graduate training in nanomedicine, particularly for underrepresented communities. His research interests include Nanomedicine Neurotechnology Quantitative MRI Drug Delivery Systems Metamaterials and Nanophotonics Quantum Chaos Superconductivity . Recent work involves machine learning-enhanced diagnostics for glaucoma, engineered nanoparticles for BRCA-deficient cancers, and portable neuro-ophthalmic devices. His publications from 2025–2017 reflect interdisciplinary applications in oncology, neurology, and materials science, with a focus on therapeutic and diagnostic innovation. Scientific accolades include the 2016 Biomedical Engineering Society Diversity Award University Distinguished Professorship . As an educator and entrepreneur, he has trained over 120 researchers, developed first-of-their-kind nanomedicine courses, and founded companies commercializing technologies like QUTE-CE MRI. His lab leads projects on cancer nanomedicine, quantitative imaging, and nanoscale magnetism, supported by grants from NIH, NSF, DoD, and private foundations.
Mohamed Farhat is a Senior Scientist at EPFL's School of Engineering, Department of Mechanical Engineering, where he leads the Research Group on Cavitation and Interface Phenomena. He serves as PhD Director, Lecturer, and Member of EPFL Doctoral Committee (Mechanics), while also representing EPFL at CLUSER association and coordinating activities at the Société Hydrotechnique de France (SHF). His research expertise spans Cavitation & Multiphase flows, Flow Induced Noise & Vibration, Fluid-Structure Interaction, Flow control, Flow instabilities in hydro turbines and pumps, Condition monitoring of Hydraulic Machines, Hemodynamics, and Advanced Instrumentation in Fluid Dynamics. Farhat's work uniquely bridges fundamental fluid mechanics with practical applications across hydropower, marine propulsion, healthcare, and water management sectors. Analysis of his recent publications reveals strong focus on cavitation bubble dynamics, with particular emphasis on measurement techniques for collapsing bubbles, vortex shedding control, hydrodynamic monitoring of hydraulic machinery, and biomedical applications of cavitation phenomena. His work increasingly integrates advanced imaging techniques with computational modeling to understand complex multiphase flow phenomena. 2021: Life Sciences Book Award of the International Academy of Astronautics 2019: 1st Prize Winner of Scientific Image Contest (Swiss National Science Foundation) 2020: EPFL-Rhyming Prize (Best PhD thesis in Fluid Mechanics) 2018: EPFL-EDME Prize (Best PhD thesis in Mechanics) 2015: Edmund Optics Educational Award 2014: APS-DFD Gallery of Fluid Motion Award Farhat has successfully supervised numerous PhD students including Ali Amini, Philippe Ausoni, and Outi Supponen, with research spanning from fundamental bubble dynamics to practical hydraulic machinery applications. His Cavitation Research Group maintains strong collaborations with industry partners in hydropower and medical device sectors. Current research directions include advanced instrumentation for cavitation monitoring, condition-based maintenance of hydraulic machinery, and biomedical applications of cavitation phenomena in therapeutic ultrasound and drug delivery.
Professor Sungheon Gene Kim holds a faculty position at the Weill Cornell Medicine Graduate School of Medical Sciences within the Department of Radiology . His research focuses on quantitative MRI methodology for oncological applications , particularly in breast cancer and head and neck cancer . Kim's lab develops advanced dynamic contrast-enhanced MRI (DCE-MRI) and diffusion MRI (dMRI) techniques to assess tumor microenvironment and treatment response . Key research areas include: Tumor vascular properties via 3D UTE-GRASP MRI Cellular microstructural analysis through POMACE framework Adipose-tissue cancer interaction via MR spectroscopic imaging His lab has received continuous funding from the National Cancer Institute (R01CA219964, UG3/UH3CA228699, R01CA160620). Recent publications demonstrate technical advancements in ultrafast MRI reconstruction , deep learning-enhanced perfusion analysis , and multi-parametric tumor characterization . Collaborations with the National Institutes of Health Quantitative Imaging Network have produced novel cellular water exchange rate measurements that correlate with patient survival outcomes .
Alexandros Kontogiannis is a research fellow at the University of Cambridge, Department of Engineering, specializing in fluid dynamics and applied mathematics. His work combines Bayesian inference, machine learning, and physics-informed algorithms to solve inverse problems in magnetic resonance velocimetry (MRV) and fluid-structure interaction. EPSRC National Fellow in Fluid Dynamics Member of Energy, Fluids and Turbomachinery Division Research Focus: Development of digital twin frameworks that integrate MRV data with Navier-Stokes equations to reconstruct flowfields, infer rheological parameters in non-Newtonian fluids, and estimate hidden quantities like pressure and wall shear stress. Key innovations include: Physics-informed compressed sensing for sparse MRV data Simultaneous boundary shape and flowfield estimation Bayesian turbulence model parameter learning Scientific Awards: ASME Fluids Engineering Division Graduate Student Scholar (2021) Technical Chamber of Greece (TEE) Award (2018) Limmat Foundation Academic Excellence (2017) Mentzelopoulos Scholarship for international studies (2017) Greek State Scholarships Foundation Award (2012) Key Contributions: Algorithms for 3D flow reconstruction with adaptive discretization, viscous signed distance field regularization, and multi-objective aerodynamic shape optimization. His methodologies enable 27x reductions in MRI scanning time while maintaining diagnostic accuracy.
Vikram Kodibagkar is a Professor in the School of Biological and Health Systems Engineering at Arizona State University, with additional affiliations to the School of Medicine and Advanced Medical Engineering. He leads the Prognostic Bioengineering (ProBE) Lab, conducting cutting-edge research in cellular and molecular imaging, magnetic resonance physics, and biomedical engineering. Education: Ph.D. in Physics, Washington University, St. Louis (2002) M.Sc. in Physics, Indian Institute of Technology-Mumbai (1997) B.Sc. in Physics, University of Mumbai, India (1995) Research Focus: Professor Kodibagkar's research centers on developing advanced imaging technologies for medical applications. His work encompasses cellular and molecular imaging , multimodality probe development , and magnetic resonance oximetry . A key focus is the development of novel contrast agents and imaging techniques for detecting hypoxia in tumors and brain injuries. His lab also works on compressed sensing accelerated magnetic resonance spectroscopic imaging (MRSI) and functional imaging of implants . The ProBE Lab emphasizes comprehensive understanding of both theory and practical techniques to train the next generation of imaging leaders. Current research activities include developing non-invasive methods for real-time monitoring of engineered cells and tissues, investigating tumor oxygenation dynamics, and creating novel MRI nanosensors for various medical applications. Research Funding and Grants: Professor Kodibagkar has secured significant funding from major organizations including: National Institutes of Health (NIH) - Multiple R01 grants National Science Foundation (NSF) - CAREER Award US Department of Defense (DOD) DARPA/BTO Flinn Foundation Texas Higher Education Coordinating Board Teaching and Mentorship: He teaches various courses including BME 350 Signals & Systems for Bioengineers, BME 465/565 Magnetic Resonance Imaging, and supervises honors theses and research projects. His teaching spans undergraduate to doctoral levels, focusing on biomedical engineering and imaging technologies. Laboratory and Team: Professor Kodibagkar directs the Prognostic Bioengineering (ProBE) Lab at Arizona State University. The lab conducts interdisciplinary research combining engineering, physics, and medicine to develop next-generation imaging technologies for clinical applications.
Pratip K. Bhattacharya, Ph.D. , is an Associate Professor in the Department of Cancer Systems Imaging and the Department of Imaging Physics at The University of Texas MD Anderson Cancer Center, with a joint appointment in the Graduate School of Biomedical Sciences at The University of Texas Health Science Center. He is a principal investigator leading the Bhattacharya Laboratory, dedicated to advancing magnetic resonance imaging (MRI) through hyperpolarization techniques for applications in cancer and cardiovascular diseases. His research focuses on developing real-time metabolic and molecular imaging methods using hyperpolarized 13 C and 15 N-labeled compounds and silicon nanoparticles. These innovative probes significantly enhance MRI sensitivity, enabling non-invasive assessment of tissue metabolism and targeted imaging. His lab's work spans three primary areas: real-time metabolic MR imaging, targeted molecular MR imaging with functionalized silicon nanoparticles, and high-resolution MR metabolomics. These efforts are aimed at improving disease diagnosis and therapy monitoring. Analysis of his recent publications reveals a strong and consistent focus on hyperpolarized MRI, particularly using silicon particles and metabolic tracers like succinate, to visualize cancer metabolism and cardiovascular conditions in vivo. His research integrates physics, chemistry, and biomedical engineering to create novel imaging tools with direct clinical translational potential. PHIP Hyperpolarization Dynamic Nuclear Polarization (DNP) Hyperpolarized Silicon Nanoparticles Real-Time Metabolic Imaging Cancer and Cardiovascular Imaging Theranostic Applications Dr. Bhattacharya actively mentors graduate students and postdoctoral fellows, including Saleh Ramezani, Jose Enriquez, Dontrey Bourgeois, and Kang-Lin Hsieh. He collaborates closely with physician-scientists, radiologists, and oncologists to ensure his imaging science innovations address critical clinical needs. His laboratory is supported by grant funding, facilitating the development of cutting-edge imaging technologies. The Bhattacharya Laboratory is a key component of the Division of Diagnostic Imaging at MD Anderson, fostering a collaborative environment for interdisciplinary research. The lab focuses on translating fundamental discoveries in hyperpolarization physics into practical tools for improving cancer care.
Dr. Alexander Kabanov is the Mescal S. Ferguson Distinguished Professor at the University of North Carolina School of Pharmacy and a member of the UNC Lineberger Comprehensive Cancer Center. He directs the Center for Nanotechnology in Drug Delivery and co-directs the Carolina Institute for Nanomedicine at UNC-Chapel Hill. Previously, he was a Parke-Davis Professor and Director of the Center for Drug Delivery and Nanomedicine at the University of Nebraska Medical Center (1994–2012). Education : PhD in Chemical Kinetics and Catalysis (1987, Moscow State University), DSc in USSR. Research Interests focus on nanomedicine and drug delivery systems , including: Polymeric micelles for cancer therapy Polyion complexes for CNS delivery Nanogels for protein/peptide delivery Magnetic nanoparticle actuation PEGylation alternatives Exosome-based therapeutics His scientific impact includes over 240 peer-reviewed articles (H-index 73), 100 patents, and $110M+ in cumulative research funding. Key article themes span nanocarrier design, tumor microenvironment targeting, and clinical translation of polymeric micelle technology. Notable awards include: AAAS Fellow (2021) NSF Career Award (1995) UNMC Scientist Laureate (2009) Lenin Komsomol Prize (1988) Dr. Kabanov co-founded Supratek Pharma and established the Nanomedicine and Drug Delivery Symposium series . His work led to SP1049C , a first-in-man polymeric micelle drug for cancer now in Phase II clinical trials.
Markus Haltmeier is a Professor in the Department of Mathematics at the University of Innsbruck. His research focuses on inverse problems, image reconstruction, and deep learning with applications in medical imaging, photoacoustics, and computational mathematics. He leads a group dedicated to advancing theoretical and practical solutions for challenges in non-destructive testing and medical diagnostics. His work integrates mathematical analysis with machine learning, addressing issues such as high-resolution imaging in scattering media and automated segmentation of cardiac structures. Key research areas include regularization techniques for inverse problems, self-supervised learning approaches for limited data scenarios, and computational methods for photoacoustic tomography. His contributions span both theoretical developments (e.g., inversion formulas for Radon transforms) and applied solutions (e.g., algorithms for cylinder liner wear assessment and myocardial infarct segmentation). Publications highlight advancements in neural network-based regularization, 3D medical image synthesis, and unsupervised learning frameworks for segmentation and registration. His research emphasizes bridging the gap between mathematical theory and real-world applications in healthcare and engineering.
Dr. Heidi Baseler is a Senior Lecturer in Imaging Sciences at the Hull York Medical School and the Department of Psychology , University of York . She serves as INSPIRE Programme Lead for undergraduate research and contributes to research governance and public/patient involvement in research through committees like the York Neuroimaging Centre Research Governance Committee and Involvement@York . Education : AB in Biology/Psychology from Dartmouth College (1986), PhD in Vision Science from University of California, Berkeley (1995) Career : Research Fellow at Stanford, Smith-Kettlewell Eye Research Institute, and University of York; Lecturer in Imaging Sciences at Hull York Medical School (2012-2021) Her research focuses on neural mechanisms for central/peripheral vision processing, cortical responses to sensory loss (e.g., AMD, deafness), and neuroprotective strategies like photobiomodulation. Techniques include structural and functional MRI , magnetic resonance spectroscopy , multifocal EEG , and electroretinography . Key findings include cortical reorganization in macular degeneration and superior visual performance in deaf adults. Recent article trends highlight: Neuroimaging biomarkers for AMD progression Cross-modal plasticity in deaf individuals Long-term effects of sensory deprivation on brain structure Photobiomodulation for neurodegeneration Functional connectivity in face-selective regions Contrast perception dynamics across aging Scientific awards include: Exceptional Contribution to Student Experience Finalist , Hull York Medical School (2024) Pursuing Excellence Award , Hull York Medical School (2023) Vice-Chancellor's Teaching Award , University of York (2020) Multiple Teacher of Excellence Finalist recognitions (2016-2018) She teaches undergraduate medical students in Foundations of Medicine and Neurological Diseases , and supervises MSc Cognitive Neuroscience projects. Collaborations span institutions like University of Hull , University of Lille , and University of Regensburg . Current students include Sharyfah Alasiri (PhD, Biomedical Sciences) and Erin English (PhD, Psychology) at the University of York.
