The Winkler Lab is based in New York City at the Magnetic Resonance Imaging Research Institute (MRIRI) of Weill Cornell Medicine and NewYork-Presbyterian Hospital. Dr. Simone Winkler is a Stanford University-trained, National Institutes of Health (NIH)-funded biomedical researcher studying three primary topics: (1) hardware development for MR engineering applications, (2) neurodegenerative disease diagnosis and the mapping of brain connectivity, and (3) high-impact work at the interface of multi-physics and medicine, in the form of fundamental clinical and biological training in pediatric MRI.
Associated Lab Members
Professor Simone Angela Winkler graduated from the J. Kepler University of Linz, Austria, having majored in mechatronics with distinction and in less than minimum time. She pursued her graduate studies in electrical engineering at the École Polytechnique Montréal, Canada, where she specialized in radiofrequency (RF)/microwave engineering, funded by two fellowships (DOC fellowship/Austrian Academy of Science; first rank in the competition for a PhD fellowship from the FQRNT Québec). For her research during her MS.c. and Ph.D. degrees, she received many scientific awards and scholarships. During her postdoctoral work at McGill University, she developed a microwave near-field imaging system for breast cancer detection. She committed to a postdoctoral fellow position at Stanford University in ultra-high-field magnetic resonance imaging engineering (funded by a National Sciences and Engineering Research Council of Canada (NSERC) research fellowship from 2012-2014).
Mina Chookhachizadeh Moghadam received her Ph.D. in computer science from the University of California, Irvine, in 2020. Her main area of research is developing machine learning (ML) and deep learning algorithms with applications in healthcare, medical devices, and predictive medicine. During her graduate studies, she extensively worked in multidisciplinary projects to develop innovative ML platforms for patients' physiological monitoring and early prediction of hypotensive events in intensive care units (ICU)s. She has also worked as an intern at Edward Lifesciences Co. and fostered collaboration with anesthesiologists and researchers at Cleveland Clinics, to increase the impact of her research on real-world field applications.
Elizaveta Motovilova received her B.Sc. and M.Sc. with a major in applied mathematics and physics from the Moscow Institute of Physics and Technology in 2012 and 2014, respectively. She received her Ph.D. from the Singapore University of Technology and Design (SUTD) in 2019. During her studies at SUTD, she was awarded the Institute of Electrical and Electronics Engineers (IEEE) MTT-S Microwave Engineering for Medical Applications Fellowship for research on the sensitivity improvement of radiofrequency (RF) coils for magnetic resonance imaging (MRI). From 2019 to 2020, she was a postdoctoral research fellow at SUTD, where she continued her work on MRI radiofrequency (RF) coils with a focus on frequency tuning mechanisms. Her main research interests include design and development of MRI RF coils, metamaterials and resonators for RF coil sensitivity improvement, ultra-high field MRI engineering and safety.
Dr. Robb has been in the field of magnetic resonance imaging (MRI) hardware since graduate school at the University of Aberdeen in 1990 under Professors David Lurie and James Hutchison. His Ph.D. thesis, “Field-Cycled Proton Electron Double Resonance Imaging of Dissolved Oxygen,” gave him wonderful hardware training and an appreciation for physiology and metabolism. He learned to build MR systems from basic components. He was a research assistant professor of radiology at Dartmouth College from 1997-1999, working for Professor Harold Swartz on 1.1GHz ESR spectroscopic hardware. Fraser's career has been heavily focused on commercial MRI coil design since starting with USA Instruments/General Electric (GE) Healthcare in 2000 (resulting in more than 40 patents approved or in process on MRI coils). Much of that time was spent building phased arrays for body, musculoskeletal and neurology imaging (1.5 tesla (T), 3.0T, 8Ch, 32Ch, 64Ch etc.) working within GE Healthcare’s Center of Excellence for Coil Development. He is pioneering advanced prototyping and simulation methods for MRI coils, and developed a strategy leading to the Air Technology MRI Coil revolution. He was recognized internally as one of GE’s most prolific recent inventors, driving the strategy leading to development of Air Coil Technology. He has an Honorary Professorship from the University of Sheffield, and is greatly honored to contribute to the amazing work of the Winkler Lab.
Isabelle Saniour was born in Mina, Lebanon in 1991. She received a master’s degree in sensors, measurement and instrumentation from the Pierre and Marie Curie University in partnership with École supérieure de physique et de chimie industrielles de la Ville de Paris (ESPCI, Paris), France, in 2013. She received her Ph.D. in physics from Lyon 1 University in 2017. From 2018 to 2019, she was involved in research on superconducting radiofrequency coils at University of Paris-Sud in Orsay, France. Her main research interests include the development of radiofrequency coils and hardware and the assessment of specific absorption rate for magnetic resonance engineering applications.
Shadeeb Hossain has an educational background in electrical, electronics, and computer (EEC) engineering and is currently a doctoral candidate in the Department of Electrical Engineering, University of Texas at San Antonio (graduation year:2022). He graduated with a master of science in electrical engineering from Central Michigan University in 2018. He is a registered Engineer-In-Training (Texas Board of Professional Engineers and Land Surveyors), and a Certified Cloud Practitioner (Amazon CCP). His area of expertise includes: (i) Electromagnetism, (ii) Optical Property analysis (iii) Material property analysis (iv) Finite Element Analysis.
Frida Galaviz Huerta was born in Zacatecas, Mexico in 2000 and is pursuing an undergraduate degree at New York University. Frida studies psychology with a triple minor in linguistics, chemistry, and child/adolescent mental studies (CAMS) and is interested in neuroscience research related to infants and adolescents. She graduated in May 2022 and hopes to pursue a graduate degree.
Vishwas received his B.Tech. from the Indian Institute of Technology Guwahati in 2020. He is a graduate student in the physiology, biophysics and systems biology (PBSB) program at the Weill Cornell Graduate School of Medical Sciences, and his main research interests lie in computational neuroscience and systems biology. In the Simone Winkler lab he was working on magnetic-resonance guided focused ultrasound coils and their implications in targeted tissue thermal ablation for treating neuropathic pain.
Arthur Nghiem was born in Houston in 2003. After graduating from high school a year early, he is an undergraduate studying biomedical engineering at the University of Minnesota. He is the principal inventor of the wireless communication device grip guide, for which he was granted a United States Patent and Trademark Office (USPTO) patent in 2017. He previously conducted a literature review on the use of high-temperature superconductors for accessible magnetic resonance imaging (MRI) applications under the supervision of Dr. John Thomas Vaughan of Columbia University. He was nominated for the 2019 Institute of Electrical and Electronics Engineers (IEEE) Region 4 Outstanding Student Award for his contributions to technical workshops regarding MRI safety and wireless medical devices. His work in the Simone Winkler Lab focused on the generation and curation of datasets for deep learning of tissue heating prediction in ultra high-field MRI.
The Winkler lab investigates novel hardware and technology methods in ultra high-field (UHF) magnetic resonance imaging (MRI), promising crucial improvement in spatial resolution and sensitivity for deciphering subtle features that are <1mm in size.
The lab fosters collaborations with institutions all over the world, in particular General Electric (GE) Healthcare, Stanford University and inGenuyX engineering solutions.
The lab welcomes a diverse set of talents and fosters an interdisciplinary approach at the intersection of the engineering and medical fields in its attempts to translate fundamental scientific discoveries into clinical innovations.
Follow this LINK for a set of slides that gives an overview of past research topics on UHF MRI at Stanford University.
A great challenge of modern biomedical science is the mapping of the human brain to understand underlying functionality and behavior. The National Institutes of Health (NIH)-funded Human Connectome Project (HCP) is a large-scale,...
The Winkler Lab has a dedicated radiofrequency (RF) team with a top-notch RF lab to design, demonstrate and test high field and UHF receive and transmit coils. Our team is devoted to cutting-edge research studies t...
Magnetic resonance imaging (MRI) relies on a dense array of radiofrequency (RF) coils to obtain functional and anatomical information inside the body. Tightly fitting coil arrays boost the signal to noise ratio (SNR) and imaging speed. Unfortunately, most commercial RF coils are rigid,...
Magnetic resonance (MR)-guided focused ultrasound (MRgFUS) is a non-invasive therapeutic modality for neurodegenerative diseases that allows real-time imaging of targeted regions. However, MR image quality is poor and severely limits the technology due to the use of the body coil for...
A crucial safety concern for ultra-high field (UHF) magnetic resonance imaging (MRI) is the significant radiofrequency (RF) power deposition in the body in the form of local specific absorption rate (SAR) hotspots, leading to dangerous tissue heating/damage. This work is a proof-of-concept demonstration of artificial intelligence (AI)...
The rapid and successful advancement in ultra-high field (UHF) magnetic resonance (MR) scanners (7 tesla (T) or higher) has led to improvement in the spatial and temporal resolution and the signal-to-noise ratio (SNR) per...