جست‌وجوی استاد و پژوهشگر

Adrian Lupascuمشاهده پروفایل

دانشیار

• Quantum Computing
• Superconductivity
• Quantum Information Processing
• +۵ مورد دیگر

Dr. Adrian Lupascu is an Associate Professor at the University of Waterloo, affiliated with the Institute for Quantum Computing (IQC) and the Department of Physics and Astronomy. He holds a cross-appointment in the Department of Electrical and Computer Engineering. His research focuses on superconducting quantum devices, including quantum annealing, quantum control, and strong light-matter interactions. Lupascu leads the Superconducting Quantum Devices Group, which explores novel architectures for quantum computing and sensing. Education: BSc in Physics (University of Bucharest, 2000); PhD in Physics (Delft University of Technology, 2005). Postdoctoral training included work at Delft University of Technology and École Normale Supérieure Paris under Professors Haroche and Raimond, supported by a Marie Curie Fellowship. Research Interests: Development of superconducting flux qubits for quantum information processing, quantum sensing, and ultrastrong light-matter interactions. Key projects include quantum annealing error suppression, qubit-qutrit gate optimization, and advanced flux qubit fabrication techniques. Awards: Alfred P. Sloan Fellowship (2011), Early Researcher Award (2011), Waterloo Nanotechnology Institute Research Leader Award (2018, 2022). His work has been funded by NSERC, MRI, and industry partnerships. Teaching: Courses include Quantum Nanophysics (PHYS 461), Nanoelectronics for Quantum Computing (QIC 880/ECE 770), and Quantum Optics Theory (QIC 895). Lab Activities: Active in developing scalable superconducting qubit systems, cryogenic microwave engineering, and quantum device fabrication. Collaborates with industry and academic partners on quantum computing hardware advancements.

• Medical Imaging
• Radiation Therapy
• Medical Physics
• +۳ مورد دیگر

Professor Davide Fontanarosa holds a PhD in Medical Physics from Maastricht University and is a Professor in the School of Clinical Sciences at QUT’s Faculty of Health. His research focuses on AI-driven ultrasound imaging, radiation therapy guidance, and orthopaedic applications. He has authored 140+ peer-reviewed publications, 11 patents, and teaches the Physics of Ultrasound unit. As unit coordinator for Honours students across five disciplines, he supervises 18 PhD candidates. Education: PhD in Medical Physics, Maastricht University (Netherlands) Research Interests: Artificial intelligence for medical imaging interpretation Image-guided radiation therapy innovations Ultrasound applications in surgery and orthopaedics Adaptive radiotherapy planning strategies Publications Trends: Recent work emphasizes computational dosimetry, placental elastography, and 3D ultrasound imaging advancements. Over 50% of 2023-2025 publications address AI-enhanced imaging or radiation therapy optimization. Grants & Labs: Led multidisciplinary projects in biomedical technologies Collaborates with industry partners like Philips Research Develops novel imaging tools for clinical applications His lab focuses on ultrasound-guided interventions and radiation safety innovations , with active projects in placental health monitoring and preclinical dosimetry.

Stefan Robilaمشاهده پروفایل

استاد

• Computational Sensing
• Hyperspectral Data Analysis
• Computer Security
• +۴ مورد دیگر

Dr. Stefan Robila is a Professor of Computer Science and Director of the Computational Sensing Laboratory (CSL) at Montclair State University, where he leads research in computational sensing, cybersecurity, and hyperspectral data analysis. He holds a PhD from Syracuse University and has held visiting scholar positions at prestigious institutions including Cambridge and Oxford Universities. Roles: NSF Program Director (2018-2021), Director of CSL, Undergraduate Research Mentor Affiliations: Member of ACM and IEEE (Senior Member since 2003) His research spans computational sensing applications such as hyperspectral imaging, energy-efficient data centers, and cybersecurity. Notable projects include NSF-funded work on cyberinfrastructure development and a $2.5M HP grant for tablet integration in computer science education. Research interests include: Unsupervised feature extraction algorithms for large datasets High-performance computing for environmental modeling Green computing and data center sustainability Recent work focuses on STEM education initiatives, including K-12 data science curricula and interdisciplinary robotics projects. Dr. Robila has secured over $5.25M in external funding from NSF, HP, PSEG, and SPIE, supporting projects ranging from MRI instrument development to undergraduate research experiences.

Enrico Raveraمشاهده پروفایل

دانشیار

• Solid-state NMR
• Paramagnetic NMR
• EPR Spectroscopy
• +۳ مورد دیگر

Enrico Ravera is an Associate Professor in the Department of Chemistry at the University of Florence, affiliated with the Magnetic Resonance Center. He holds a B.Sc., M.Sc., and Ph.D. in Chemistry from the University of Florence (2008–2013), followed by postdoctoral fellowships at CERM and a FIRC Fellowship at CIRMMP. His research focuses on NMR spectroscopy (solution/solid-state), paramagnetic systems, EPR, and biomaterial characterization. Key achievements include developing novel NMR methodologies for protein-material interactions and co-authoring influential textbooks like NMR of Paramagnetic Molecules . Education: B.Sc. Chemistry, University of Florence (2008) M.Sc. Chemistry of Biological Molecules, cum laude (2009) Ph.D. in Chemistry (2013) Research interests span solid-state NMR, paramagnetic systems, EPR, and bioinspired materials. Notable contributions include engineering enzymes for bioinspired silica formation and studying protein dynamics via paramagnetic tagging. Awards include the 2020 Premio Raffaello Nasini, GIDRM Under 35 Award, and UNESCO/IUPAC Green Chemistry Prize. His work bridges chemistry, biology, and materials science, with applications in drug design and medical imaging. Grants and collaborations include projects on protein-drug conjugates, NMR-based drug development, and biotherapeutic characterization. He leads efforts in developing interdisciplinary approaches for structural biology. Labs/Teams: Active in the Magnetic Resonance Center (CERM) and collaborates with CIRMMP. Research integrates NMR with computational methods and biophysical techniques.

• Neuropsychiatry
• Bipolar Disorder
• Magnetic Resonance Imaging
• +۳ مورد دیگر

Dr. Kutlu Kaya is a Postdoctoral Research Fellow in the Mood Disorders Research Program at Yale School of Medicine. He holds a PhD in Physiology from Hacettepe University (2022) and completed additional doctoral research at Massachusetts General Hospital (2021). His research focuses on neuropsychiatric mechanisms, bipolar disorder, and cerebral hemodynamics using advanced optical imaging techniques like near-infrared spectroscopy and diffuse correlation spectroscopy. His work bridges clinical neuroscience with biomedical engineering to develop non-invasive monitoring tools for neurological conditions. Education: PhD, Physiology, Hacettepe University (2022) PhD Dissertation, Radiology, Massachusetts General Hospital (2021) MS, Physiology, Hacettepe University (2016) BS, Biology, Ankara University (2011) Key Research Areas: Near-infrared spectroscopy, bipolar disorder pathophysiology, cerebral blood flow dynamics, and wearable health monitoring devices. Labs: Mood Disorders Research Program, Yale School of Medicine. His publications highlight innovations in intraoperative cerebral monitoring during carotid surgery, neonatal cerebral health tracking, and oxytocin receptor gene influences on brain connectivity.

• Machine Learning
• Medical Imaging
• Neuroscience
• +۳ مورد دیگر

Arman Afrasiyabi is an Associate Research Scientist at the Yale School of Medicine, Yale University. His research focuses on advancing machine learning and artificial intelligence techniques for medical imaging and neuroscience applications, particularly in multimodal data integration, neural network architectures, and precision medicine. He explores methods such as domain-agnostic image translation, few-shot learning, and distortion-aware neural networks to address challenges in healthcare and biomedical research. His work spans theoretical advancements in neural networks (e.g., non-Euclidean vector products) and practical applications like brain activity decoding and HD data representation. Key contributions include developing encoder-decoder networks for multimodal analysis and energy-efficient neural architectures. No specific awards or grants are listed in the provided information. His academic role emphasizes research without part-time designation. No student advisees are mentioned in the texts. Laboratory or team affiliations are not explicitly detailed in the available data.

• Medical Imaging
• RF Engineering
• Biomedical Engineering
• +۳ مورد دیگر

Chenhao Sun is an Associate Research Scientist in the Department of Radiology & Biomedical Imaging at Yale University. His work focuses on advancing MRI technology through innovations in RF engineering, coil design, and imaging methodologies. Key research areas include low-field MRI systems, hyperpolarized imaging, and geometric decoupling techniques for multi-nuclear applications. Sun's contributions span hardware development, algorithm optimization, and clinical translation of imaging solutions. Research Interests: RF coil design and optimization for MRI systems Nonlinear encoding and gradient-free imaging techniques Hyperpolarized 13C and 31P spectroscopy Low-cost, point-of-care MRI solutions Multi-nuclei imaging and geometric decoupling strategies Recent Trends in Publications: Recent work emphasizes low-field MRI advancements, dynamic spectroscopic methods, and hardware innovations like broadband receive arrays and phase shifters. His research bridges fundamental RF engineering with clinical applications, targeting improved accessibility and diagnostic precision in medical imaging. Lab/Team Affiliation: Part of Yale School of Medicine's Radiology & Biomedical Imaging team, collaborating on MRI system design and biomedical engineering projects.

• Medical Imaging
• Nuclear Medicine
• Biomedical Engineering
• +۴ مورد دیگر

Tianyi Zeng is an Associate Research Scientist at the Yale PET Center and junior faculty in the Department of Radiology and Biomedical Imaging at Yale School of Medicine. He holds a Ph.D. in Biomedical Engineering from the University of Chinese Academy of Sciences (2021) and a B.E. from Xi'an Jiaotong University (2016). His research focuses on advancing PET imaging technologies, particularly motion correction and reconstruction methods for the NeuroEXPLORER brain PET scanner. Key areas include deep learning applications, MRI compatibility, and improving image quality. Research Interests PET image reconstruction and motion correction Development of high-resolution PET systems (e.g., NeuroEXPLORER, SIAT bPET) Deep learning for medical imaging Multi-modal imaging (PET/MRI integration) Recent Articles Recent work emphasizes motion correction algorithms, NeuroEXPLORER performance evaluation, and semi-supervised learning in medical image segmentation. His studies address challenges in clinical PET accuracy and hardware innovation. Awards 2024 IEEE NSS/MIC/RTSD Trainee Grant 2024 SNMMI Poster Award (Third Place) 2023 Best Paper Award (2nd Place) at Machine Learning in Clinical Neuroimaging workshop Grants & Collaborations Recipient of multiple IEEE and SNMMI grants. Collaborations include United Imaging Healthcare America for multi-tracer PET studies. Labs & Teams Primary affiliation: Yale PET Center. Active in the Department of Radiology and Biomedical Imaging, contributing to translational imaging research.

Thomas Robertsonمشاهده پروفایل

پژوهشگر ارشد

• Nuclear Magnetic Resonance (NMR)
• Microfabrication
• Hardware Development
• +۴ مورد دیگر

Dr. Thomas Robertson is a Research Fellow at the University of Southampton, affiliated with the Spectroscopy, Spectrometry, and Structure Interdisciplinary Centre for Magnetic Resonance. His research focuses on advancing NMR techniques, microfabrication, and hyperpolarization methods (e.g., SABRE/PHIP) for applications in biomedical, forensic, and material science contexts. He collaborates on projects involving tissue engineering, drug analysis, and forensic spectroscopy. Research Groups: Member of Spectroscopy, Spectrometry, and Structure Interdisciplinary Centre for Magnetic Resonance Teaching: Contributes to NMR Advanced Practicals for the Advanced Practical Chemistry module (38794) His research interests include: Development of hyperpolarization techniques for enhanced NMR/MRI sensitivity Instrumentation design for NMR systems and microfluidic devices Forensic applications of NMR in drug detection and analysis Computational modeling of diffusion and spin dynamics in porous media Recent work explores SABRE hyperpolarization of pyruvate, mirfentanil, and piperazine-based drugs, as well as 3D-printed scaffolds for tissue engineering. His articles address methodological advancements in NMR spectroscopy and interdisciplinary applications across chemistry, biology, and forensics.

Anuj Sharmaمشاهده پروفایل

عضو هیئت علمی

• Magnetic Resonance Imaging (MRI)
• RF Pulse Design
• MRI-guided Interventions
• +۳ مورد دیگر

Anuj Sharma, PhD, is a Research Assistant Professor in the Department of Biomedical Engineering at Case Western Reserve University's Case School of Engineering and School of Medicine. His work focuses on advancing Magnetic Resonance Imaging (MRI) technologies, including pulse sequence design, RF pulse optimization, and MRI-guided interventions. He holds a PhD and MSc from Vanderbilt University and a BEng from Manipal University, India. Dr. Sharma has been recognized with prestigious awards such as the ISMRM Summa Cum Laude Merit Award (2013) and the ViewRay Visibly Better Award (2022). Education: PhD in Biomedical Engineering, Vanderbilt University MSc in Biomedical Engineering, Vanderbilt University BEng in Biomedical Engineering, Manipal University Research Interests: RF Pulse Design for High-Field MRI MRI-Guided Therapeutic Interventions B1+ Mapping and Correction Techniques AI-Driven MRI Workflow Optimization Motion Artifact Mitigation in Clinical Imaging Awards: Visibly Better Award 2022 Magna Cum Laude Merit Award (RF Pulse Design) 2015 ISMRM Summa Cum Laude Merit Awards (2013) Manipal University Distinguished Alumnus 2013 Professional Contributions: Full Member, International Society for Magnetic Resonance in Medicine (ISMRM) since 2011 Past President & Vice President, Biomedical Engineering Society of India (BMESI) Students’ Chapter (2006–2007) His research bridges cutting-edge MRI hardware innovation with clinical translation, emphasizing safety, accuracy, and accessibility in diagnostic and therapeutic imaging.

David Waldmanمشاهده پروفایل

استاد پژوهشی

• Polymer Science
• Optical Engineering
• Data Storage Technologies
• +۴ مورد دیگر

David Waldman is a Research Professor in the Department of Polymer Science and Engineering at the University of Massachusetts Amherst, where he also serves as Director of the Center for Ultrafast Microscopy and Imaging Research (CUMIRP). He holds a PhD in Polymer Science & Engineering from the same institution (1990). His research focuses on advanced materials science, particularly in holographic storage systems, photopolymer materials, and optical engineering. Key contributions include the development of high-density holographic data storage media, phase-encoded data recovery systems, and novel applications of nanotechnology in manufacturing. Waldman’s work integrates interdisciplinary approaches to solve challenges in data storage, medical imaging, and renewable energy systems. Education: PhD in Polymer Science & Engineering, University of Massachusetts Amherst (1990). Research interests span holographic data storage systems, photopolymer chemistry, and the application of holography in medical imaging (e.g., lymphatic system analysis). He has pioneered materials like CROP photopolymers for optical data storage exceeding 100 bits/μm². His recent work explores solar energy systems using volume holograms and nanoimprint lithography for precision manufacturing. Publications highlight advancements in holographic media design, biometric imaging systems, and security device technologies. Waldman collaborates with the Sylvio O. Conte National Center for Polymer Research, contributing to cutting-edge polymer science initiatives.

Edward Mulliganمشاهده پروفایل

استاد

• Orthopedic Physical Therapy
• Sports Medicine
• Clinical Education
• +۵ مورد دیگر

Edward Mulligan is a Professor in the Department of Rehabilitation Sciences at Tufts University School of Medicine, specializing in orthopedic and sports physical therapy. He holds joint appointments in Physical Therapy and Orthopedic Surgery departments from his prior role at UT Southwestern Medical Center, where he served for over 20 years. He has developed and administered orthopedic and sports physical therapy residency programs, and currently directs Tufts' musculoskeletal curriculum. Education: Bachelor of Science in Biology Education (University of Nebraska, 1980) Bachelor of Science (University of Texas Medical Branch, 1982) Master of Science (Texas Woman's University, 1995) Doctor of Physical Therapy (Regis University, 2008) His research focuses on musculoskeletal disorders, hip preservation surgery, sports-related injuries, and healthcare education. Notable contributions include over 30 peer-reviewed studies, residency program development, and advocacy for financial literacy among healthcare students. Awards include the American Academy of Sports Physical Therapy Hall of Fame (2020) and Lifetime Excellence in Education Award (2017). Dr. Mulligan’s articles analyze clinical practice guidelines, surgical outcomes, and healthcare workforce dynamics. He has led grants on topics like bone science in running athletes and financial stress in students. His teaching spans courses in musculoskeletal management, evidence-based practice, and business administration in healthcare. Professional Activities: Chair, Sports Physical Therapy Council (APTA, 2010–2011) Research Committee Member, Academy of Orthopedic Physical Therapy Senior Site Reviewer, Physical Therapy Residency Programs He advises on sports physical therapy education and has contributed to specialty practice standards. His work bridges clinical care, education, and research in musculoskeletal health.

• Control Systems
• Model Identification
• Autonomous Robotics
• +۴ مورد دیگر

Tamer Inanc is a Professor in the Department of Electrical and Computer Engineering at the University of Louisville's J.B. Speed School of Engineering. He holds a B.S. from Dokuz Eylul University (1991), M.S. and Ph.D. from Pennsylvania State University (1996, 2002), followed by a postdoctoral scholarship at Caltech (2002–2004). His research focuses on control systems, model identification, autonomous robotics, and biomedical applications like personalized drug dosing and anemia management. Education: B.S., Electrical & Electronics Engineering, Dokuz Eylul University (1991) M.S., Electrical Engineering, Pennsylvania State University (1996) Ph.D., Electrical Engineering, Pennsylvania State University (2002) Research Interests: His work spans control systems, biomedical modeling (e.g., warfarin and anemia management), autonomous robotics, and deep learning regularization in neural networks. He emphasizes personalized modeling using limited clinical data and robust system identification techniques. Key Contributions: Developed adaptive modeling frameworks for precise drug dosing in clinical settings. Advanced techniques to reduce redundancy in deep neural networks for better generalization. Contributed to trajectory optimization for unmanned vehicles and medical imaging analysis. Awards: President's Distinguished Teaching Professor Award (2022) Speed School Excellence in Teaching Award (2021) Delphi Center Innovations in Technology Award (2008) Kentuckiana Metroversity Instructional Development Award (2006) Labs/Teams: His research involves collaborations in healthcare technology, robotics, and control systems, with projects funded by academic and industry partnerships.

Leeor Alonمشاهده پروفایل

استادیار

• Medical Imaging Safety
• MRI Technology
• Biomedical Engineering
• +۳ مورد دیگر

Leeor Alon, PhD, is an Assistant Professor in the Department of Radiology at NYU Grossman School of Medicine. His research focuses on advancing medical imaging safety, MRI technology optimization, and biomedical engineering innovations. He holds a PhD from New York University. Alon's work emphasizes the development of open-source medical devices, such as ultra-low-field MRI systems and 3D-printed animal imaging platforms. His research integrates cutting-edge techniques like deep learning for hemorrhage detection and electromagnetic field analysis for RF safety. He has contributed to understanding risks associated with brain-implanted conductors and RF exposure in rodents, alongside pioneering temperature-regulated MRI systems for preclinical studies. His publications highlight interdisciplinary approaches, combining engineering, physics, and biology to address challenges in MRI safety, thermometry, and biomedical instrumentation. Collaborations span neuroimaging, material science, and clinical diagnostics, reflecting his commitment to bridging theoretical and applied research.

Kiaran P. McGeeمشاهده پروفایل

استاد

• Magnetic Resonance Imaging (MRI)
• Medical Physics
• Radiology
• +۵ مورد دیگر

Kiaran P. McGee, Ph.D. is a Professor of Medical Physics and holds an academic rank of Assistant Professor of Biomedical Engineering at Mayo Clinic. His primary appointment is as a Consultant in the Department of Radiology at Mayo Clinic, Rochester, Minnesota. He is Director of the Imaging Biomarker Discovery Program at the Center for Individualized Medicine. Education: Ph.D. in Biomedical Imaging (Mayo Clinic Graduate School) Ph.D. in Biophysics/Biomedical Engineering (Mayo Graduate School) MS in Medical Physics (University of Manitoba) BS in Applied Science (University of Technology, Sydney) Research Focus: Dr. McGee specializes in advancing MRI and MRE (Magnetic Resonance Elastography) techniques for diagnosing diseases such as lung fibrosis, heart conditions, and cancer. His work emphasizes non-invasive imaging of tissue mechanical properties to improve early disease detection and therapy monitoring. Key projects include: Development of MRE for parenchymal lung diseases MRI techniques for radiation therapy planning Biomarkers of therapy response in cancer Publications & Awards: Dr. McGee has authored over 100 peer-reviewed articles and holds awards such as the 2016 Distinguished Reviewer Awards and the Minnesota Teckne Finalist (2015). He contributed to the NIH-funded Regional Assessment of the Lung Using MRE project (2009–2010). Professional Roles: Chair of AAPM Task Group on MR Biomarkers in Radiation Oncology Member of multiple professional committees (AAPM, RSNA) Editorial board member of Medical Physics Journal Labs & Collaborations: He leads the Imaging Biomarker Discovery Program and collaborates with institutions like Beijing Anzhen Hospital and Mayo-Illinois Alliance.