جست‌وجوی استاد و پژوهشگر

Camila Aquinoمشاهده پروفایل

استادیار

• Movement Disorders
• Parkinson's Disease
• Deep Brain Stimulation
• +۵ مورد دیگر

Dr. Camila Aquino serves as Assistant Professor in both the Department of Clinical Neurosciences and Department of Community Health Sciences at the University of Calgary's Cumming School of Medicine, and is a Full Member of the Hotchkiss Brain Institute. As Medical Director of the Deep Brain Stimulation Program, she specializes in Parkinson's disease, essential tremor, dystonia, and chorea management, including EMG-guided botulinum toxin injections. Her educational background includes: M.D. in Medicine from Escola Superior de Ciencias da Santa Casa (2005) M.S. in Neurosciences from Federal University of Sao Paulo (2012) Ph.D. in Neurosciences from Federal University of Sao Paulo (2019) M.S. in Health Research Methods, Clinical Epidemiology from McMaster University (2020) Dr. Aquino's research addresses unmet needs in movement disorders through innovative clinical trial designs for Parkinson's disease, focusing on precision-medicine approaches, early intervention, and outcome optimization. She actively evaluates neuromodulation therapies including Deep Brain Stimulation, Spinal Cord Stimulation, and MRgFUS, with emphasis on expanding indications and improving patient outcomes. As an International Parkinson and Movement Disorder Society member, she chairs the web-based learning committee and serves on evidence-based medicine and outcome measure committees. Analysis of her 15 most recent publications (2021-2025) reveals a cohesive research trajectory centered on Parkinson's disease management, with dominant themes in motor fluctuation treatments, deep brain stimulation methodology, and clinical trial innovation. Her work bridges fundamental clinical practice guidelines with advanced neuromodulation technologies, demonstrating consistent commitment to evidence-based solutions for movement disorders. Her scientific recognition includes: Parkinson Canada research grant Mohammed Al Zaibak Foundation scholarship CAPES scholarship from Brazilian Ministry of Education Dr. Aquino has secured significant research funding supporting clinical trials in Parkinson's disease neuroprotection and neuromodulation therapies. While specific student advisees aren't listed, her leadership of the DBS Program and active clinical trial portfolio indicate substantial mentorship responsibilities. Her grant portfolio emphasizes translational research with direct clinical impact. She directs the University of Calgary's Deep Brain Stimulation Program and contributes to the MRI-guided focused ultrasound initiative. Through her International Parkinson and Movement Disorder Society committee roles, she shapes global educational standards and evidence-based practices in movement disorders.

Michael McAlpineمشاهده پروفایل

استاد

• 3D Printing
• Nanotechnology
• Biomedical Engineering
• +۴ مورد دیگر

Michael McAlpine is a Professor in the Mechanical Engineering department at the University of Minnesota . He also holds affiliations with the Biomedical Engineering and Electrical and Computer Engineering departments. His research focuses on 3D printing functional materials & devices , Nanoscale inks , Biomedical devices , Bioelectronics , and Flexible Microsystems . Research Interests : 3D Printing, Biomedical Engineering, Nanotechnology, Flexible Electronics, Microfluidics Labs : ME 361/363 Contact : mcalpine@umn.edu , (612) 626-3303, ME 117 Recent Research Trends include 3D Printed Biomedical Devices , Flexible Electronics , and Bioprinting Applications . His work spans from Spinal Organoid Formation to Programmable Drug Release Capsules . Scientific Award : Circulation Research 2020 Best Manuscript Award

David S. Eisenbergمشاهده پروفایل

استاد

• Protein Aggregation
• Amyloid Structures
• Prion Diseases
• +۵ مورد دیگر

David S. Eisenberg is a Professor of Chemistry and Biochemistry and Biological Chemistry at the University of California, Los Angeles, where he also serves as Director of the UCLA-DOE Institute for Genomics and Proteomics and as an HHMI Investigator. His research focuses on protein interactions, particularly the structural basis for conversion of normal proteins to the amyloid state and conversion of prions to the infectious state. Dr. Eisenberg earned his undergraduate degree in biochemical sciences from Harvard College and his D.Phil. degree in theoretical chemistry from Oxford University on a Rhodes Scholarship. His postdoctoral research was on ice and water with Walter Kauzmann at Princeton and in protein crystallography with Richard Dickerson. He joined the UCLA faculty after his postdoctoral studies. Dr. Eisenberg and his research group focus on protein interactions in amyloid and prion diseases. These diseases involve protein aggregation where normal functional proteins convert to abnormal aggregated forms. Systemic amyloid diseases like dialysis-related amyloidosis result from fiber accumulation until organ failure, while neurodegenerative diseases like Alzheimer's, Parkinson's, ALS, and prion conditions appear to be caused by smaller oligomers. In 2005, his team determined the atomic-level structure for the amyloid fiber spine, revealing a 'steric zipper' of two parallel beta sheets packed across a dry interface. Since then, they've determined approximately 90 amyloid spines from 15 disease-related proteins. In 2010, they identified the structure of a toxic amyloid-related oligomer consisting of six anti-parallel beta strands forming a cylindrical barrel. His recent publications demonstrate continued innovation in amyloid research, with focus areas including structural prediction of amyloid formation, mechanisms of tau fibril disassembly in Alzheimer's disease, cryo-EM analysis of amyloid polymorphism, and structure-based design of inhibitors for amyloid toxicity. His work integrates computational, structural, and biochemical approaches to understand protein aggregation across multiple disease contexts. Dr. Eisenberg has received numerous prestigious awards and honors: National Academy of Sciences Member American Philosophical Society Member Institute of Medicine Member Howard Hughes Medical Institute Investigator Biophysical Society Emily M. Gray Award Harvard Westheimer Medal UCLA Seaborg Medal Technion - Israel Institute of Technology Harvey Prize in Human Health As Director of the UCLA-DOE Institute for Genomics and Proteomics and an HHMI Investigator, Dr. Eisenberg leads significant research initiatives in protein structure and aggregation. His laboratory combines X-ray crystallography, bioinformatics, and biochemical techniques to investigate protein interactions, with particular emphasis on amyloid-forming proteins and their role in disease. The Eisenberg Lab, located in Boyer Hall at UCLA, maintains an active research program investigating the structural basis of protein aggregation. The lab continues to build on its landmark discoveries of amyloid structures while exploring new frontiers in understanding protein misfolding diseases and developing potential therapeutic interventions.

Massimo Mischiمشاهده پروفایل

استاد

• Biomedical Signal Processing
• Diagnostic Imaging
• Ultrasound Technology
• +۴ مورد دیگر

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.

Julia A. Mundyمشاهده پروفایل

دانشیار

• Quantum Materials
• Molecular-Beam Epitaxy (MBE)
• Thin Film Synthesis
• +۵ مورد دیگر

Julia A. Mundy is the John L. Loeb Associate Professor of the Natural Sciences and Engineering and Applied Sciences at Harvard University. Her research focuses on designing quantum materials at the atomic scale using molecular-beam epitaxy (MBE) to synthesize metastable thin films. She leads the Mundy Group, which explores superconductors, frustrated magnets, and oxide interfaces for quantum and energy applications. Her work bridges materials synthesis, characterization, and fundamental physics. Affiliations: Harvard University, School of Engineering and Applied Sciences, Applied Physics Department Labs: Mundy Group (LISE 7th floor) Research interests include MBE growth of novel oxides, thin film superconductors, and 2D electronic systems. She has pioneered methods for creating room-temperature multiferroics and discovered superconductivity in layered nickelates. Her group uses advanced tools like aberration-corrected electron microscopy and synchrotron-based spectroscopy. Key achievements include the 2024 Moore Inventor Fellowship, NSF CAREER Award, and Packard Fellowship. Her work on transparent superconductors and fluoride-ion battery materials highlights interdisciplinary impact. Notable Grants: DOE Early Career Award, NSF MRI funding for LEEM/PEEM microscopy Team: 15+ current members including graduate students, postdocs, and undergraduates

Craig H. Meyerمشاهده پروفایل

استاد

• Medical and Molecular Imaging
• Signal and Image Processing
• Biomedical Data Sciences
• +۲ مورد دیگر

Craig H. Meyer is a Professor in Biomedical Engineering and Radiology & Medical Imaging at the University of Virginia. He holds a Ph.D. from Stanford University and leads the Rapid MRI Research Group, focusing on developing advanced MRI techniques for cardiovascular disease, neural disorders, and pediatrics. His work integrates physics, signal processing, and machine learning to improve MRI acquisition and processing speed. Education: Ph.D. in Biomedical Engineering, Stanford University. Research Interests: Medical and Molecular Imaging, Signal and Image Processing, Biomedical Data Sciences, Biomechanics, and Cardiovascular Engineering. His innovations include fast spiral imaging, conjugate phase reconstruction, and machine learning-enhanced MRI denoising. Awards: Notably includes the Dean’s Award for Excellence in Team Science (2014), Fellowships from NAI (2021), AIMBE (2015), and ISMRM (2013). He also authored two landmark MRI papers recognized as pivotal in the field. Teaching: Courses include BME 6310 (Computation and Modeling in Biomedical Engineering) and BME 8782 (Magnetic Resonance Imaging). He emphasizes translational research, with applications in clinical MRI advancements and collaborative interdisciplinary projects. Labs/Groups: Rapid MRI Research Group focuses on cutting-edge MRI technologies, including real-time cardiac imaging and artifact reduction through deep learning.

• Nuclear Magnetic Resonance (NMR)
• In vivo imaging
• MRI pulse sequence development
• +۷ مورد دیگر

Professor Guy Williams is a leading academic at the University of Cambridge with a focus on imaging science and clinical neurosciences, affiliated with Downing College and the Wolfson Brain Imaging Centre . Holding a PhD in Physics from his initial Natural Sciences degree, he specializes in nuclear magnetic resonance (NMR) and MRI techniques for brain imaging. Education: BA, PhD in Physics His research centers on non-invasive imaging of brain structure and function, particularly in traumatic brain injury (TBI) and dementia. His work involves developing novel MRI pulse sequences and advanced data analysis algorithms, including AI-based diagnostic tools. He leads studies on white matter integrity post-trauma, longitudinal dementia assessment, and applications of MRI in disorders of consciousness and addiction. Recent publications highlight collaborations in traumatic brain injury outcomes, AI-guided dementia prediction, and neuroimaging of post-COVID cognitive deficits. His team's work on ultra-high field laminar fMRI and distortion correction methods has advanced clinical neuroscience applications. Key techniques include diffusion tensor imaging (DTI), 7 Tesla MRI, and positron emission tomography (PET/MR). His research spans from basic NMR physics to clinical translation, with a strong emphasis on multi-site studies and real-world diagnostic implementation.

• Audio Signal Processing
• Spatial Audio Technology
• Medical Engineering
• +۳ مورد دیگر

Craig Jin is an Associate Professor at the University of Sydney, leading the CARlab (Computing and Audio Research Laboratory) and Spatial Audio Research initiatives within the School of Electrical and Computer Engineering. He holds a BS from Stanford University, an MS from Caltech, and a PhD from the University of Sydney. His work focuses on immersive audio technologies, biomedical signal processing, and assistive technologies for sensory augmentation. Research interests include spatial audio reproduction, binaural processing, acoustic sensing for accessibility, and machine learning applications in signal processing. Key contributions span HRTF interpolation, noise reduction algorithms, and acoustic touch systems for the visually impaired. Recent projects include real-time MRI analysis of vocal tract dynamics and sparse recovery techniques for sound field reconstruction. His publications span over 150 peer-reviewed articles in journals like IEEE Transactions on Audio, Speech, and Language Processing, and conferences such as ICASSP. He advises four current PhD/Master’s students on projects like predictive gesture tracking, voice disorder classification, and magnetic resonance imaging techniques.

Hongye Zhangمشاهده پروفایل

مدرس

• Superconductor Technology
• Cryogenic Techniques
• Electric Machines and Drives
• +۳ مورد دیگر

Dr. Hongye Zhang serves as a Lecturer in Superconducting and Cryogenic Electric Machines at the School of Engineering, University of Edinburgh, while maintaining a Visiting Research Fellow position at the University of Manchester. He actively contributes to the European Society for Applied Superconductivity (ESAS) as a Board Member and chairs the international HTS 2026 workshop. His educational foundation includes: BSc and MSc in Electrical Engineering from Xi’an Jiaotong University (2015, 2018) Diplôme d’ingénieur (MEng) from École Centrale de Lyon (2018) PhD in Applied Superconductivity from the University of Edinburgh (2021) Dr. Zhang’s research centers on decarbonizing transport through superconducting/cryogenic electric machines for hydrogen-powered aircraft, integrating artificial intelligence with superconductor technology and cryogenic techniques. His work targets net zero emissions by developing high-power-density propulsion systems that leverage hydrogen energy and advanced numerical modeling of superconductors. Analysis of his 2022-2025 publications reveals dominant themes in superconducting machine design for wind energy and electric aviation, with significant contributions to loss mitigation, flux pump technology, and trapped field magnet applications. His research bridges fundamental superconductor characterization with practical system integration for renewable energy. Recognized with the 2021 IEEE Council on Superconductivity Graduate Study Fellowship, his professional engagements include: Early Career Editorial Board Member for Elsevier’s Superconductivity journal Technical Editor for IEEE Transactions on Applied Superconductivity Program Committee Member for SMT 2023 He leads critical research within the £54-million H2GEAR project developing hydrogen-electric aircraft propulsion, while teaching Power Engineering 2 and Electrical Machines courses. His advisory roles span doctoral supervision and industry collaboration through Energy Systems research institute. Based at the University of Edinburgh’s Faraday Building, Dr. Zhang directs a research group focused on hydrogen energy applications and superconducting machine testing, with strong ties to the H2GEAR consortium and ESAS working groups.

Peter Gordonمشاهده پروفایل

دانشیار

• Language Acquisition
• Developmental Neuroscience of Language and Cognition
• Cross-cultural Studies of Numerical Cognition
• +۳ مورد دیگر

Peter Gordon is an Associate Professor of Neuroscience and Education and Cognitive Science in Education at Teachers College, Columbia University. He directs the Language and Cognitive Neuroscience Lab and holds affiliations with Biobehavioral Sciences, Human Development, and other departments. His research focuses on language acquisition, developmental neuroscience, cross-cultural numerical cognition, and MRI-based studies of language processing. Dr. Gordon earned a B.A. (Hons) in Psychology from the University of Stirling (Scotland) and a Ph.D. in Psychology from MIT. His fieldwork includes extensive studies with the Piraha in Amazonia, Brazil, and the Kadiweu in Mato Grosso do Sul, Brazil. His research interests span infant event representations, behavioral genetics of language, and the interplay between language structure and cognitive development. Notable contributions include work on anumeric cultures and the linguistic relativity hypothesis. Publications highlight cross-cultural studies, morphological processing, and cognitive neuroscience of language. He has conducted influential research on numerical cognition in Amazonian cultures and the genetic influences on language acquisition. Contact: pg328@tc.columbia.edu | Office: 1152 Building 528 | Lab: [Link Provided].

Craig S. Levinمشاهده پروفایل

استاد

• Molecular Imaging
• Medical Physics
• Positron Emission Tomography
• +۵ مورد دیگر

Dr. Craig S. Levin is a Professor of Radiology at Stanford University's Molecular Imaging Program at Stanford (Nuclear Medicine), with courtesy appointments in Physics, Electrical Engineering, and Bioengineering. He also holds memberships in Bio-X, the Cardiovascular Institute, the Wu Tsai Human Performance Alliance, and the Stanford Cancer Institute. Dr. Levin received his B.S. Summa Cum Laude in Physics and Mathematics from UCLA in 1985, followed by M.S., M.Phil., and Ph.D. degrees in Physics from Yale University in 1987 and 1993. His educational achievements were recognized with multiple honors including Phi Beta Kappa, Sigma Pi Sigma, and various departmental awards at UCLA. Dr. Levin's research focuses on the development of novel instrumentation and software algorithms for molecular imaging. His work spans medical physics, biomedical engineering, and instrumentation development with specific emphasis on positron emission tomography (PET), gamma camera technology, and multimodal imaging systems. His laboratory explores new concepts in radiation detection, image reconstruction algorithms, and the application of these technologies to cancer, heart disease, and neurological disorders. A notable aspect of his research involves pushing the physical limits of sensitivity and spatial, spectral, and/or temporal resolutions in imaging systems. His recent publications demonstrate a strong focus on enhancing PET technology, particularly time-of-flight capabilities, with significant work on improving coincidence timing resolution, developing MR-compatible PET systems, and applying deep learning techniques to image reconstruction and normalization. His research shows a clear trajectory toward higher resolution imaging with improved quantitative accuracy for both clinical and preclinical applications. Dr. Levin's scientific achievements have been recognized with numerous awards: American Institute for Medical and Biological Engineering's College of Fellows Academy of Radiology Research Distinguished Investigator Recognition Award National Research Service Award from NIH (1993-5) Pilot Research Award from the Society of Nuclear Medicine (1996) Multiple honors from UCLA including Phi Beta Kappa and Sigma Pi Sigma Full Tuition and Research Fellowship and Bates Graduate Fellowship from Yale University As an educator and mentor, Dr. Levin directs the NIH-NCI funded T32 Stanford Molecular Imaging Scholars postdoctoral training program and serves as a Doctoral Dissertation Advisor for students in Bioengineering and Biophysics. He currently advises five postdoctoral scholars and three doctoral candidates. His laboratory, the Molecular Imaging Instrumentation Laboratory, comprises approximately 20 members who work on developing new imaging technologies and translating them into clinical applications. Dr. Levin has secured substantial NIH funding as Principal Investigator along with grants from other government agencies, industry partners, and private institutions to support his research program. Dr. Levin's Molecular Imaging Instrumentation Laboratory is at the forefront of developing new imaging technologies that bridge physics, engineering, and medicine. The lab focuses on creating instrumentation for in vivo imaging of cellular and molecular signatures of disease, with particular emphasis on pushing the physical limits of imaging performance. Their work spans computer modeling, sensor development, electronics design, data acquisition systems, and advanced image processing algorithms. The lab maintains strong industry partnerships to translate their innovations into products used for patient care worldwide.

Carlos Fernandez-Grandaمشاهده پروفایل

دانشیار

• Machine Learning
• Medical AI
• Climate Science
• +۷ مورد دیگر

Carlos Fernandez-Granda is an Associate Professor of Mathematics and Data Science at New York University, holding joint appointments at the Courant Institute of Mathematical Science and the Center for Data Science. He currently serves as the Interim Director of the Center for Data Science. His academic career spans over a decade at NYU, where he has taught probability and statistics to data-science students. Dr. Fernandez-Granda's research focuses on designing and analyzing data-science methodology, with current emphasis on machine learning applications in medicine, climate science, and scientific imaging. His work bridges theoretical foundations with practical applications across multiple domains. His notable contributions include: Development of the COBRA (COnfidence-Based chaRacterization of Anomalies) score for automatic assessment of impairment and disease severity Applications of machine learning to improve climate projections through the M2LInES project Research on magnetic resonance fingerprinting for quantitative tissue parameter estimation Development of AI systems for medical diagnostics including Alzheimer's detection and breast cancer diagnosis Dr. Fernandez-Granda is the author of the book "Probability and Statistics for Data Science," published by Cambridge University Press. The book serves as a comprehensive guide to the two pillars of data science, featuring real-world datasets and addressing fundamental challenges like overfitting, the curse of dimensionality, and causal inference. His research has been supported by grants from the National Science Foundation (Division of Mathematical Sciences, grants 1616340 and 2009752) and the Alzheimer's Association (grant AARG-NTF-21-848627). Dr. Fernandez-Granda is actively involved in several collaborative projects: M2LInES project: An international collaboration focused on improving climate projections using machine learning to capture unaccounted physical processes at the air-sea-ice interface Math and Data group: Exploring the intersection of mathematical theory and data science applications

Reinhard Heckelمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Computational Imaging
• +۵ مورد دیگر

Reinhard Heckel is a Tenured Associate Professor (equivalent to Professor) of Machine Learning at the Department of Computer Engineering, Technical University of Munich (TUM), and Adjunct Faculty in Electrical and Computer Engineering at Rice University. He was previously an Assistant Professor at Rice (2017–2019), a postdoc in the Berkeley Artificial Intelligence Research (BAIR) Lab at UC Berkeley, and a researcher at IBM Research Zurich. Education: PhD, 2014 – ETH Zurich Visiting PhD student – Department of Statistics, Stanford University Research Interests: His work centers on machine learning and information processing with three major thrusts: (1) developing algorithms and theoretical foundations for deep learning, especially for accelerated magnetic resonance imaging ; (2) establishing rigorous mathematical and empirical underpinnings for modern machine-learning systems; and (3) leveraging DNA as a digital information-storage medium , including error-correction coding and system design for DNA-based storage. Across more than 100 peer-reviewed papers since 2017, Heckel’s research exhibits a strong interdisciplinary blend of computational imaging , machine-learning theory , and molecular data storage . Recent 2024–2025 publications show intensive focus on robust MRI reconstruction using diffusion priors, evaluation of bias in large web-text corpora, and state-of-the-art error-correcting codes for DNA storage channels. A forthcoming book, Deep Learning for Computational Imaging (Oxford University Press), consolidates his contributions to the field. Outreach & Media: Keynote and panel talks at DLD, TUM, and major ML conferences Op-eds in Frankfurter Allgemeine on ChatGPT and DNA storage Science features on Netflix, BBC, and German television (Galileo, “Gut zu Wissen”) Research Environment: At TUM he leads a group investigating theoretical and applied aspects of deep learning, compressed sensing, and coding for DNA storage. Open-source repositories on GitHub (e.g., dna_data_storage , supplement_deep_decoder ) provide code and data supplements accompanying his publications.

F. Levent Degertekinمشاهده پروفایل

استاد

• Micro and Nano Engineering
• Acoustics and Dynamics
• Electromechanical Transducers
• +۷ مورد دیگر

F. Levent Degertekin is a Regents' Entrepreneur and the George W. Woodruff Chair in Mechanical Systems and Professor at the George W. Woodruff School of Mechanical Engineering at Georgia Institute of Technology. His office is located in Love Building, room 311B, and his contact email is levent.degertekin@me.gatech.edu. Dr. Degertekin's academic journey includes a Ph.D. in Electrical Engineering from Stanford University (1997), an M.S. in Electrical Engineering from Bilkent University, Turkey (1991), and a B.S. in Electrical Engineering from Middle East Technical University, Turkey (1989). Dr. Degertekin's research focuses on micromachined ultrasonic devices and systems for medical applications, particularly in intravascular ultrasound imaging, therapeutic ultrasound, and acousto-optical sensors for MRI. His work spans from fundamental research on novel transduction methods to complete catheter-based imaging systems close to commercialization. He has made significant contributions to capacitive micromachined ultrasonic transducers (CMUTs), developing diffraction grating based optomechanical sensing methods now commercialized by Silicon Audio, novel atomic force microscopy imaging probes, and micromachined ultrasonic ejector structures for cell transfection commercialized by OpenCell Technologies. His research integrates acoustics, optics, and their combinations for various medical applications, utilizing conventional microfabrication (MEMS) and integrated circuit technologies. The Degertekin lab exposes students to applied physics, electrical, mechanical and biomedical engineering, biology, and biomimetic systems, providing them with thorough theoretical and experimental education in acoustics and optics while learning interdisciplinary research. Dr. Degertekin's work has received significant media attention, including coverage in IEEE Spectrum, Wired Magazine, The New York Times, and Fox Business News, highlighting innovations such as handheld ultrasound probes, MRI safety sensors, and minimally invasive cardiac imaging technologies. IEEE Fellow for 'Contributions to micromachined ultrasonic and optomechanical transducers and systems,' 2022 IEEE UFFC Society Inaugural Carl Hellmuth Hertz Ultrasonic Achievement Award, 2014 George W. Woodruff School Outstanding Achievement in Commercialization and Entrepreneurship Award, 2024 National Science Foundation CAREER Award, 2004-2009 Whitaker Foundation Biomedical Engineering Research Grant Award, 2001 66 US and 6 International Patents Dr. Degertekin has mentored numerous students who have gone on to make significant contributions in the field. Several of his students have received IEEE Ultrasonics Symposium Best Student Paper Awards, including Jeff McLean (2003), Sheng-Yu Peng (2006), Rasim O. Guldiken (2005 and 2007), and Toby Xu (2014). His research has been supported by various grants including the NSF CAREER Award and Whitaker Foundation grant. His work has led to multiple commercial ventures including Silicon Audio and OpenCell Technologies. The Degertekin Group at Georgia Tech focuses on transducers and systems for medical imaging and sensing, with current projects including capacitive parametric transducers, acousto-optic sensors for MRI, novel transducer methods for focused ultrasound in the brain, microsystems for intravascular and intracardiac ultrasound imaging, and CMUT-on-CMOS systems for IVUS imaging.

Taylor Wareمشاهده پروفایل

دانشیار

• Biomaterials
• Micro/Nanotechnology
• Medical Devices
• +۷ مورد دیگر

Taylor Ware is an Associate Professor in Biomedical Engineering and Materials Science & Engineering at Texas A&M University's College of Engineering, holding the Cain Faculty Fellowship. Her research focuses on designing structured biomaterials and medical devices using stimuli-responsive polymers for clinical applications. Education: Ph.D. in Materials Science and Engineering, The University of Texas at Dallas, 2013 Research Interests: Dr. Ware pioneers the development of liquid crystal elastomers as artificial muscles and implantable electronics substrates, engineered living materials for infection treatment, and directed self-assembly of hydrogels. Her lab specializes in polymer formulation, thermomechanical testing, and microfabrication. Key research thrusts include: Smart elastomers, hydrogels, and composites for dynamic medical devices Programming liquid crystalline polymers for shape-morphing applications Engineered living materials that respond to biomolecular cues in urinary tract environments Publication Trends: Recent work (2023-2025) demonstrates convergence of materials science, microbiology, and medical device engineering. Her group advances liquid crystal elastomers for soft robotics and implantable electronics, develops engineered living materials for UTI treatment using microbial competition, and creates novel hemostats and urethral support devices. Publications emphasize translational applications in urology, wound healing, and neural interfaces. Scientific Awards: Invited Participant, NAE Japan-USA Frontiers of Engineering Bilateral (2023) Senior Member, National Academy of Inventors (2022) NSF CAREER Award (2018) Air Force Young Investigator Award (2017) NSF Graduate Research Fellowship (2011) Fellow of AIMBE (American Institute for Medical and Biological Engineering) Advising and Grants: Dr. Ware leads the Ware Lab with significant funding including an NIH R01 grant (with UT Dallas and Case Western collaborators) and the NSF CAREER award. Her lab mentors postdoctoral fellows like Mustafa (winner of a prestigious postdoctoral fellowship) and graduate students. Current projects are supported by the NSF Engineering Research Center HAND, focusing on advanced materials for healthcare applications. Laboratory and Teams: The Ware Lab collaborates globally and is featured in Texas Monthly, Houston Chronicle, and National Geographic for breakthroughs in engineered living materials. As part of the NSF HAND ERC, the lab develops dynamic materials for stress urinary incontinence treatment and collaborates with medical institutions on UTI therapies using engineered E. coli strains.