Find Academic Supervisors

• Phonetics
• Phonology
• Language Acquisition
• +7 more

Alexei Kochetov is a Professor in the Department of Linguistics at the University of Toronto, Faculty of Arts and Science. His research focuses on the interface between phonology and phonetics, particularly palatalization, assimilation, and their phonetic correlates. He has held academic positions at the University of Toronto since 2003 and previously at Simon Fraser University. Kochetov holds a PhD from the University of Toronto (2001), an MA from Pittsburg State University (1996), and a BA from Perm State University (1992). His research interests include articulatory phonetics, cross-linguistic phonological phenomena, and bilingual speech production. He has conducted studies on languages such as Russian, Japanese, Kalasha, Kannada, and Korean using methods like electropalatography (EPG), ultrasound, and acoustic analysis. Recent work explores L2 acquisition of English consonants, nasal depalatalization in French, and articulatory MRI studies of Indian languages. Kochetov has secured extensive SSHRC funding for projects on speech production, perception, and bilingualism. His articles (e.g., on French nasal depalatalization, Russian palatalization, and Korean liquids) reflect his expertise in articulatory detail and cross-linguistic comparison. Though no specific awards are listed, his contributions to phonetics are highlighted through his prolific grant activity and experimental methodologies. He supervises graduate students in phonetics/phonology and teaches courses like Advanced Phonetics and Phonetic Analysis . His research lab focuses on cutting-edge articulatory imaging and remote data collection techniques, contributing to both theoretical and applied linguistics.

Jan SijbersView profile

Professor

• Image Reconstruction
• Medical Imaging
• Quantitative MRI
• +3 more

Jan Sijbers is a Full Professor at the University of Antwerp , affiliated with the Department of Physics . He serves as Spokesperson of the imec-Vision Lab and is a co-founder of spin-offs IcoMetrix and Deltaray . His academic role includes a 10% position as Research Director at imec. Research Interests: Quantitative Magnetic Resonance Imaging (MRI), Tomographic Image Reconstruction, Medical Imaging Algorithms Editorial Roles: Senior Area Editor (IEEE Transactions on Image Processing), Associated Editor (IEEE Transactions on Computational Imaging) Teaching: Courses in Physics, Mathematics, Signal/Image Processing, and X-ray Microtomography Research Trends: His 2025 publications focus on X-ray phase contrast imaging, zebrafish models for bone disease, mesh-based CT reconstruction, and AI-driven biomedical imaging. Earlier works emphasize statistical signal processing in MRI and discrete tomography algorithms. PhD Advisees: He has supervised 68 PhD theses since 2004, with recent topics spanning edge illumination X-ray imaging, 3D knee morphology, and advanced MRI relaxometry. Laboratory Leadership: As head of imec-Vision Lab, he leads research in computational imaging, with applications in medical diagnostics and industrial X-ray systems.

• Medical Imaging
• Deep Learning
• Cardiac Ultrasound
• +7 more

Dr. Qingjie Meng is a Researcher in the Department of Computing at Imperial College London, affiliated with the Faculty of Engineering. Their work focuses on advancing AI-driven medical imaging technologies, particularly in cardiac ultrasound, fetal anomaly detection, and MRI analysis. Meng's research emphasizes privacy-preserving data solutions and generative models for healthcare applications. Research interests include deep learning for medical image synthesis, motion tracking in MRI, and real-time AI applications in ultrasound screening. Recent work explores foundational models like EchoFlow for cardiac imaging and SACB-Net for medical registration tasks. Publications highlight trends in generative AI for medical data, robust segmentation techniques, and multi-view cardiac tracking. Meng's contributions address challenges in fetal anomaly detection and respiratory motion correction in MRI scans. No awards or advising roles are explicitly listed in the provided text. Their work contributes to labs focused on biomedical AI and healthcare informatics, though specific lab affiliations are not detailed.

Alejandro Roldán AlzateView profile

Professor

• Cardiovascular Fluid Dynamics
• Medical Imaging-Based Computational Fluid Dynamics (CFD)
• Patient-Specific Surgical Planning
• +7 more

Professor Alejandro Roldán-Alzate is a faculty member in the Department of Mechanical Engineering at the University of Wisconsin-Madison, with an additional affiliation in Biomedical Engineering. He leads the UW Cardiovascular Fluid Dynamics laboratory, focusing on fluid dynamics analysis of physiological and pathological flows using medical imaging, 3D printing, and computational fluid dynamics (CFD). His research integrates 4D flow MRI, patient-specific modeling, and in vitro experiments to study cardiovascular and urological systems. Education: PhD in Mechanical Engineering, University of Wisconsin-Madison (2008) M.Eng., University of Wisconsin-Madison (2005) Bachelor of Science, Escuela de Ingeniería de Antioquia – Universidad CES (2002) Research Interests: His work bridges engineering and medicine, emphasizing cardiovascular fluid dynamics, medical image-based CFD, and 4D flow MRI applications. Key areas include hemodynamic analysis of congenital heart defects, pulmonary artery stenosis, bladder voiding mechanics, and surgical planning. His lab also develops low-cost patient-specific vascular models and explores ultrasound and MRI innovations for clinical diagnostics. Publications Trends: Recent articles highlight advancements in uro-dynamic MRI, pulmonary artery remodeling models, and 4D flow MRI for abdominal and cardiovascular applications. Focus areas include translational research, non-invasive diagnostics, and computational modeling for surgical optimization. Awards: 2013 & 2012 ISMRM Summa Cum Laude Merit Awards (twice each) 2011 Lauterbur Award in Magnetic Resonance 2005 Wang Fellowship (UW-Madison) Multiple undergraduate and early-career recognition awards Teaching & Advising: Roldán-Alzate teaches courses in biofluidics (BME/ME 505), mechanical engineering design, and graduate research. While no named advisees are listed, his lab actively engages students in CFD, imaging, and biomedical device projects. Labs & Teams: Director of the UW Cardiovascular Fluid Dynamics Lab , collaborating with clinicians and engineers on translational cardiovascular and urological research.

Adam S. GreenbergView profile

Associate Professor

• Cognitive Neuroscience
• Attention Mechanisms
• Neuroimaging
• +6 more

Dr. Adam S. Greenberg is a neuroscientist and biomedical engineer with dual appointments as Associate Professor at the Joint Department of Biomedical Engineering (Medical College of Wisconsin/Marquette University) and Secondary Appointment in the Department of Ophthalmology and Visual Sciences . He also serves as Associate Dean of Postdoctoral Education at the Medical College of Wisconsin. PhD in Psychological & Brain Sciences (Johns Hopkins University, 2010) M.S. in Biomedical Engineering (University of Alabama at Birmingham, 2001) B.S. in Biomedical Engineering (Case Western Reserve University, 1996) His research focuses on the cognitive neuroscience of attention , particularly investigating brain network dynamics using fMRI , transcranial magnetic stimulation , and computational modeling . He explores attentional mechanisms in both normal human volunteers and patient populations , including studies on age-related hearing loss , early-onset dementia , and cognitive impairments from chemotherapy ('chemobrain'). Recent publications demonstrate his work on object-based attention mechanisms , brain network dynamics , and neural correlates of cognitive decline . His scientific awards include multiple Outstanding Educator Awards from the Medical College of Wisconsin and fellowships in the Psychonomic Society . Dr. Greenberg has advised numerous graduate students and postdoctoral researchers , with a particular focus on neuroimaging studies and cognitive neuroscience research. He also plays a significant role in postdoctoral education and graduate student training through his Directorships of the Neuroimaging Journal Club and Advanced Seminar in Neuroimaging .

Mohammad Amir OwrangiView profile

Associate Professor

• Radiation Oncology
• Medical Physics
• Brachytherapy
• +3 more

Mohammad Amir Owrangi serves as Associate Professor in Radiation Oncology at Baylor College of Medicine (Houston) and University of Texas Southwestern (Dallas), with prior appointments as Assistant Professor at both institutions and the University of Toronto. His expertise bridges medical physics and clinical radiation oncology, focusing on advancing precision radiotherapy through technological innovation. His academic foundation includes a BSc and MSc in Physics and Radiation-Medicine Engineering from Shiraz University (Iran), followed by a PhD in Biomedical Engineering from The University of Western Ontario (Canada), and a CAMPEP-accredited residency in Therapeutic Radiologic Medical Physics at University of Michigan Health System. Dr. Owrangi's research centers on solving critical challenges in image-guided radiotherapy, particularly MRI-based treatment planning for gynecological cancers. His work pioneers synthetic CT generation using deep learning to eliminate CT simulation needs, optimizes brachytherapy applicators for cervical cancer, and develops metal artifact reduction techniques. Recent publications demonstrate increasing integration of AI methods to improve dosimetric accuracy and workflow efficiency in radiation therapy. Analysis of his 15 most recent publications (2017-2024) reveals three dominant research thrusts: (1) MRI-only radiotherapy workflows with synthetic CT generation using deep learning/GANs, (2) brachytherapy optimization for cervical cancer through applicator design and dosimetry, and (3) artifact reduction in multi-modal imaging. His work consistently targets clinical translation, with 70% of recent publications focusing on gynecological applications. Scientific Awards: No awards explicitly mentioned in source materials Academic advising and research grant details were not provided in available documentation. His collaborative network spans Baylor College of Medicine, UT Southwestern, University of Toronto, and international institutions including Shiraz University and University of Western Ontario, with frequent co-authorship among medical physicists and radiation oncologists. While specific laboratory infrastructure isn't detailed, his research requires advanced capabilities in MRI/CT image processing, Monte Carlo simulation, and deep learning development, suggesting access to high-performance computing resources and clinical imaging datasets at his affiliated institutions.

• Cognitive Neuroscience
• Human Memory
• Aging
• +3 more

Dr. Alexa Morcom is an Associate Professor in Cognitive Neuroscience at the School of Psychology, University of Sussex. Her research focuses on human memory, particularly how episodic memory and its neural substrates change with normal aging. She employs functional magnetic resonance imaging (fMRI) and electrophysiological techniques like event-related potentials (ERPs) to investigate memory processes. Key areas of interest include memory control mechanisms, functional compensation in aging brains, and the role of perceptual/semantic similarity in memory errors. Her work is supported by grants such as the 2019 BIAL Foundation grant (Temporal Decoding of Selective Recollection with Psychophysiology). She emphasizes reproducible research practices, publishing data and preregistering studies on platforms like OSF. Dr. Morcom teaches Cognitive Psychology and supervises undergraduate/postgraduate projects at the University of Sussex. Research highlights include demonstrating that increased frontal brain activity in older adults reflects nonspecific neural responses rather than compensation, and showing age-invariant mechanisms in associative false recognition. Her studies often involve collaborations with researchers like Knights, Henson, and Hoffman, focusing on neuroimaging meta-analyses and longitudinal aging studies. Labs/Teams: Active involvement in the Cam-CAN longitudinal study (Phase 4/5) and collaborations within the School of Psychology. Advising hours are held weekly via Zoom/in-person, emphasizing student accessibility.

Katherine E. TravisView profile

Assistant Professor

• Neuroscience
• Pediatrics
• Neuroimaging
• +3 more

Katherine E. Travis, Ph.D. is an Assistant Professor of Neuroscience in Pediatrics at Weill Cornell Medicine and Director of the Laboratory for Language Development and Recovery at the Burke Neurological Institute. She holds a B.A. in Neuroscience from Colorado College (2003) and a Ph.D. in Neuroscience from the University of California, San Diego (2011). Her postdoctoral training at Stanford University focused on translational and clinical pediatric neuroscience. Dr. Travis's research investigates therapies to promote brain, language, and cognitive development in children at-risk for learning disabilities. She employs advanced MRI techniques (e.g., diffusion and quantitative T1-mapping) to study brain development in neonates, infants, and children. Her current work explores how sensory experiences and parenting behaviors in neonatal intensive care units and home environments shape neurocognitive outcomes in preterm infants. Key achievements include a K99/R00 Pathway to Independence Award from NIH (2016) and recruitment to the Burke Neurological Institute and Weill Cornell Medicine in 2023. Her lab focuses on translational research bridging neuroimaging and clinical interventions to improve developmental outcomes. Recent publications highlight studies on pediatric melanoma risks, neuroinflammatory modulation via brain stimulation, and glucocorticoid effects in preterm brain development. Her work intersects multiple disciplines including neuroimaging, pediatric oncology, and neonatal care.

Giovanni AlbertiView profile

Professor

• Partial Differential Equations
• Inverse Problems
• Applied Harmonic Analysis
• +3 more

Giovanni Alberti is a Full Professor in Mathematical Analysis at the Department of Mathematics (DIMA) of the University of Genoa. He earned his D.Phil. at the University of Oxford and completed postdoctoral positions at École Normale Supérieure (Paris) and ETH Zurich. His research focuses on partial differential equations, applied harmonic analysis, inverse problems, and machine learning. University of Genoa MaLGa Center (Machine Learning Genoa) Mathematical Institute, Oxford Maths Department, ETH Zurich His work bridges mathematical analysis with computational methods, particularly in inverse problems , compressed sensing , and machine learning . He has developed algorithms for real-time geotechnical predictions, sparse optimization for scatterer localization, and continuous generative models. Recent publications emphasize physics-data-driven integration and low-dimensional manifolds. He received the Gioacchino Iapichino Prize (2017), Eurasian Association on Inverse Problems Young Scientist Award (2018), and an ERC Starting Grant (2021). He serves on editorial boards for journals including Inverse Problems and SIAM Journal on Imaging Sciences.

• Computer Science
• Medical Technology
• Artificial Intelligence
• +3 more

Dr. Hamit Soyel is a Research Fellow at Queen Mary University of London's School of Electronic Engineering and Computer Science, affiliated with the Dragonfly initiative. His work spans educational technology, healthcare innovation, and computer vision. His research focuses on enhancing learning through video-based methods, improving rheumatoid arthritis care via technology, and advancing facial recognition systems using geometric and algorithmic approaches. Key research themes include cognitive load optimization in educational videos, patient-clinician communication barriers in RA care, and robust image processing techniques for medical and facial analysis. His interdisciplinary approach bridges computer science with healthcare and education, aiming to develop practical technological solutions. Publications highlight trends in medical technology adoption, video instruction design, and facial expression recognition. He has contributed to patents in image enhancement and algorithms for 3D facial geometry analysis. His work reflects a commitment to both theoretical innovation and real-world applications. No scientific awards are explicitly listed, though his extensive publication record indicates recognition in his fields. He has advised no documented students but collaborates on projects involving healthcare technology and educational systems. His involvement in the Dragonfly project suggests affiliation with cross-disciplinary teams focused on interactive companions and affect-sensitive technologies. Research labs or groups are not explicitly mentioned, but his work aligns with Queen Mary's broader initiatives in AI and healthcare tech.

• Obesity
• Neuroscience
• Pediatric Medicine
• +6 more

Dr. Shan Luo is an Assistant Professor of Medicine at the University of Southern California (USC) School of Medicine, specializing in obesity research, neuroimaging, and developmental health. Her work bridges clinical medicine, behavioral neuroscience, and metabolic regulation, focusing on maternal-child health interactions and dietary impacts on brain function. Key Research Areas: Obesity, Pediatric Neuroscience, Gestational Diabetes, Dietary Sugar Effects, Functional MRI Awards: Journal of Obesity: Top Five Winning Paper (2024) AFMR: Young Investigator Award (2024) NIH NIDDK Career Development Award (2018-2022) Publications: 15+ peer-reviewed articles analyzing obesity's neural correlates, prenatal programming, and metabolic neuroscience. Her research explores how maternal obesity and gestational diabetes alter children's brain development, influencing appetite regulation and obesity risk. She investigates the neurocognitive impacts of dietary sugars, artificial sweeteners, and physical activity in pediatric populations using advanced neuroimaging techniques. Dr. Luo's scientific contributions include groundbreaking studies on hippocampal alterations in children exposed to gestational diabetes, reward processing differences between sucrose and sucralose, and socioeconomic factors modulating breastfeeding's neurodevelopmental benefits. Her work informs interventions for childhood obesity prevention.

• Neuroimaging
• Psychiatric Disorders
• Developmental Neuropsychiatry
• +7 more

Dr. Bradley Peterson is a Professor of Psychiatry & the Behavioral Sciences and Pediatrics at the Keck School of Medicine, University of Southern California, and serves as the Division Chief of Psychiatry & the Behavioral Sciences at Children’s Hospital Los Angeles (CHLA). He joined USC and CHLA in 2014 after prior roles at Columbia University and Yale University. Education: MD from University of Wisconsin Medical School (1987), Residency at Massachusetts General Hospital, Fellowships at Yale and Columbia Research Focus: Dr. Peterson specializes in neuroimaging technologies to study psychiatric disorders and therapeutic mechanisms across the lifespan. His work spans conditions like Autism, Depression, Bipolar Disorder, ADHD, Tourette syndrome, and environmental toxin impacts on brain development. Publications: Recent studies examine prenatal environmental exposures, maternal nutrition, and brain connectivity in psychiatric disorders. He employs multimodal MRI and SPECT to map developmental trajectories. Scientific Awards: Dean’s Teaching Award (USC, 2017) Blanche Ittleson Award (APA, 2012) John J. Weber Prize (Columbia, 2007) Outstanding Mentor (AACAP, 2014 & 2006) Grants & Collaborations: His research involves collaborations with institutions like CHLA and CTSI, focusing on precision medicine and developmental brain disorders. Labs: Leads the Institute for the Developing Mind at CHLA, integrating neuroimaging with behavioral science to study early brain development.

• Cardiovascular MRI
• Iron Overload
• Hemoglobinopathies
• +2 more

Dr. John C. Wood is Professor of Pediatrics, Radiology, and Biomedical Engineering at the University of Southern California's Keck School of Medicine. He directs the Cardiovascular MRI program at Children's Hospital Los Angeles and specializes in noninvasive iron quantification and congenital heart disease. His NIH-funded research explores iron overload in hemoglobinopathies, sickle cell vasculopathy, and red cell mechanics. Research interests include: MRI-based assessment of cardiac/liver iron in transfusion-dependent conditions Pathophysiology of sickle cell disease and thalassemia Neurovascular and cardiopulmonary dynamics in chronic anemias His recent articles (2023–2025) primarily investigate iron homeostasis, cerebrovascular hemodynamics in sickle cell disease, fetal cardiac MRI, and long COVID sequelae in children. Trends show a focus on translational applications of advanced MRI techniques. Awards include: RSNA Scholar (2001) Alpha Omega Alpha Honor Society (1993) Tau Beta Pi Engineering Honor Society (1982) Dr. Wood leads the NIH Early Detection of Iron Cardiomyopathy Trial and ARRA Challenge grant on sickle cell vasculopathy. He mentors trainees in the John Wood Lab, focusing on iron metabolism and cardiovascular imaging.

Larissa JansenView profile

Researcher

• Biomedical Engineering
• Medical Imaging
• Cardiovascular Biomechanics
• +3 more

Larissa Jansen is a Researcher at the Eindhoven University of Technology (TU/e) in the Biomedical Engineering department. She completed her PhD in 2024, focusing on developing novel 3D ultrasound imaging techniques for improved mechanical quantification of abdominal aortic aneurysms (AAAs). Her work addresses challenges in field of view, temporal resolution, and clinical decision-making for AAA management. She holds a BSc (2016) and MSc (2018) in Biomedical Engineering from TU/e, with an internship at the Auckland Bioengineering Institute, where she studied myocardial fiber orientations using MRI and finite element modeling. Research Interests : Medical imaging and ultrasound technology Cardiovascular biomechanics Abdominal aortic aneurysm diagnostics Image acquisition and processing Publications : Her recent work advances 3D ultrasound techniques for AAA assessment, including studies on distensibility quantification and imaging system optimization. These contributions highlight the potential of ultrasound for non-invasive mechanical characterization of blood vessels. Labs/Teams : She is affiliated with the Photoacoustics & Ultrasound Laboratory and the Eindhoven MedTech Innovation Center , collaborating on projects funded by the Dutch Research Council (NWO).

Katharina von KriegsteinView profile

Professor

• Neuroscience
• Cognitive Science
• Clinical Neuroscience
• +5 more

Katharina von Kriegstein is a Professor of Cognitive and Clinical Neuroscience at Technische Universität Dresden (since 2017). Previously, she held positions at Humboldt University Berlin (2013–2017) and led a Max Planck Research Group (2009–2018). Her research focuses on sensory processes underlying human communication, employing neuroimaging, neurostimulation, and behavioral techniques. She explores communication impairments in developmental disorders and neurological patients, particularly investigating auditory and visual thalamic dysfunction in dyslexia and autism. Her work is supported by an ERC Consolidator Grant (2015) and has contributed to understanding sensory pathway roles in speech-in-noise recognition and voice identity processing. Key findings include thalamic structural abnormalities linked to dyslexia and autism, as well as predictive coding mechanisms in auditory pathways. Education: Medical License (Approbation), 2003 Dr. med., summa cum laude, University of Göttingen (1994–2001) Philosophy studies, University of Göttingen (1995–1997) Studium generale, Leibniz-Kolleg, Tübingen (1993–1994) Key Projects: Leading Subproject A11 in CRC 940 (goal-directed behavior) Investigating thalamic roles in communication (e.g., auditory/visual speech perception) Her research integrates clinical, cognitive, and computational approaches. Recent work highlights multisensory learning benefits for auditory processing and the causal role of sensory cortices in vocabulary translation. Awards include the Max Planck Research Group (2009) and best doctoral thesis in Experimental Medicine (2002).