جست‌وجوی استاد و پژوهشگر

• Medical Imaging
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Dr. Neal Bangerter is a Visiting Professor in the Department of Bioengineering at Imperial College London's Faculty of Engineering. He specializes in medical imaging (MRI), artificial intelligence, machine learning, and signal processing. Dr. Bangerter holds adjunct appointments at INSEAD, the University of Utah, and Brigham Young University. His research focuses on ultra-high field MRI, AI applications in healthcare, and data-driven bioscience technologies. He leads the London Collaborative Ultra-High Field Scanner (LOCUS) project and advises companies on AI and innovation strategies. Education: B.S. in Physics (UC Berkeley), M.S. and Ph.D. in Electrical Engineering (Stanford University). Career highlights include roles at McKinsey & Company, Microsoft, and Reactrix, as well as founding BYU's Medical Imaging Research Center. He has pioneered cross-faculty initiatives like the Crocker Innovation Fellowship Program. Research interests include novel MRI pulse sequences, AI in medical imaging, and large-scale health data analysis. His work spans collaborations with Stanford, Oxford, Cambridge, and Siemens Healthcare. He teaches executive education at INSEAD, focusing on bridging technical concepts with business strategies. Key awards include the David Evans Chair at Brigham Young University. His contributions to the UK Biobank Neuroimaging study and development of MRI techniques like RAFO-4 highlight his impact on advancing imaging technologies and AI applications in healthcare.

Joanna Austinمشاهده پروفایل

استاد

• Hypervelocity Flight
• Planetary Entry
• Supersonic Combustion and Detonation
• +۵ مورد دیگر

Joanna Austin is a Professor of Aerospace and serves as the Graduate Option Representative for Aeronautics and Space Engineering, as well as the Undergraduate Option Representative for Aerospace at the California Institute of Technology (Caltech). She leads the Caltech Hypersonics Group, which operates facilities like the T5 Reflected Shock Tunnel and the Hypervelocity Expansion Tube (HET). Her research focuses on reactive, compressible flows in applications such as hypervelocity flight, planetary entry, supersonic combustion, bubble dynamics, and explosive geological events. Key projects include studying shock-boundary layer interactions, Martian atmospheric entry aerothermodynamics, and high-speed fluid-structure interactions. She advises four Ph.D. students and collaborates with a team including staff members like Liza Bradulina and research assistants such as Noel Esparza-Duran. Her work bridges experimental fluid dynamics with geophysical phenomena, leveraging advanced diagnostics like Focused Laser Differential Interferometry (FLDI) and laser spectroscopy. The group’s facilities enable studies of high-enthalpy flows and hypersonic aerodynamics critical for aerospace and planetary exploration. Research highlights include investigations into CO₂ Martian entry conditions, boundary layer transition mechanisms, and fluid-structure coupling in high-speed flows. The Hypersonics Group’s experimental setups replicate extreme environments to advance predictive models for aerospace systems. Her contributions span both fundamental fluid mechanics and applied engineering challenges, with a focus on real-gas effects and shock dynamics. Collaborations with institutions like NASA and academic partners further her interdisciplinary impact.

Andreas Peter Burgمشاهده پروفایل

دانشیار

• Circuits and systems for telecommunications
• Silicon implementation of communication technologies
• Communication algorithms optimization
• +۵ مورد دیگر

Andreas Peter Burg is a Tenured Associate Professor at the École Polytechnique Fédérale de Lausanne (EPFL), where he leads the Telecommunications Circuits Laboratory (TCL) within the School of Engineering. He holds multiple academic and administrative roles at EPFL including Associate Professor in Teaching (SEL, EDMI, EDEE), Director of SEL Management, and Member of the Doctoral Program Committee for Electrical Engineering. Dr. Burg received his Dipl.-Ing. degree in 2000 and Dr. sc. techn. degree in 2006 from ETH Zurich. His academic career includes positions as SNF Assistant Professor at ETH Zurich (2009-2011) before joining EPFL in January 2011 as a Tenure Track Assistant Professor, where he was promoted to Tenured Associate Professor in June 2018. His research focuses on circuits and systems for telecommunications , with particular expertise in silicon implementation of communication technologies, communication algorithms optimization for hardware, low-power VLSI signal processing, and digital integrated circuits. His work bridges theoretical communication concepts with practical circuit implementations, addressing challenges in wireless and wired communication systems. His recent publications (2024-2025) demonstrate a strong focus on next-generation communication technologies including 6G systems, advanced error correction coding, wireless sensing applications, and ultra-low power circuit design. These works span multiple subfields from LDPC and polar code decoding to RF signal processing and machine learning applications in wireless systems. Willi Studer Award (2000) ETH Medal for diploma thesis (2000) ETH Medal for Ph.D. dissertation (2006) Swiss National Science Foundation Assistant Professorship grant (2008) Dr. Burg has been involved in the development of more than 25 ASICs throughout his career and co-founded Celestrius, an ETH spinoff in MIMO wireless communication. His laboratory work focuses on practical implementations of communication algorithms with emphasis on power efficiency and hardware optimization. Current research directions include 6G technologies, wireless sensing applications, and novel error correction techniques for next-generation communication systems.

• Synthetic Biology
• Biomedical Engineering
• Systems Biology
• +۴ مورد دیگر

Harrison Steel is an Associate Professor of Engineering Science at the University of Oxford and Tutorial Fellow at Harris Manchester College. He holds a BEng in Mechanical Engineering and BSc in Physics and Mathematics from the University of Sydney, followed by a DPhil at Oxford as a Monash Scholar. His research focuses on synthetic biology, control engineering, and bioprocess optimization, with a particular emphasis on microbial systems and genetic circuit design. Dr. Steel’s work integrates computational modeling, experimental biology, and control theory to engineer robust biological systems. His contributions include advancements in genome editing via SIBR-Cas systems, cybernetic control of microbial co-cultures, and the development of open-source platforms like Chi. Bio for automated biological experimentation. His recent publications highlight innovations in directed evolution strategies, modular biomolecular control architectures, and the application of machine learning to fitness landscape analysis. He has pioneered approaches for stabilizing genetically engineered cell populations and enhancing bioprocess efficiency through adaptive control systems. Dr. Steel’s research is supported by collaborations across engineering, biology, and computational disciplines. He actively contributes to academic leadership through his role at Harris Manchester College and maintains an experimental focus on bridging theoretical models with practical biological implementations.

R. Luke DuBoisمشاهده پروفایل

دانشیار

• Digital Media
• Human Computer Interaction
• Cyber Physical Systems
• +۳ مورد دیگر

R. Luke DuBois is an Associate Professor and Co-Chair of the Technology, Culture and Society Department at the NYU Tandon School of Engineering, where he also directs the Integrated Design & Media program and the Brooklyn Experimental Media Center. He holds a DMA in music composition from Columbia University and is a renowned artist, composer, and performer whose work explores intersections between technology, sound, and visual media. His research focuses on digital media, human-computer interaction, and emerging technologies applied to artistic expression and accessibility. Key roles include directing the SONYC initiative (addressing urban noise pollution via AI) and leading the NYU Ability Project (advancing disability studies through technology). He has collaborated with institutions like the Smithsonian and artists such as Maya Lin, and his work has been exhibited globally, including at the Sundance Film Festival and the Aspen Institute. DuBois co-developed the Jitter software suite for real-time data manipulation and performs in avant-garde groups like Bioluminescence and Fair Use. His artistic practice combines time-lapse phonography, interactive installations, and interdisciplinary projects that critique cultural ephemera while advancing accessibility in STEM and the arts. Recent contributions include browser-based tools for accessible music notation (SoundCells) and sonification techniques for calculus education. He serves on the Board of the ISSUE Project Room and has been featured in major publications like the New York Times and TED Conference talks.

Karim Sabraمشاهده پروفایل

استاد

• Acoustics
• Structural Health Monitoring
• Biomechanics
• +۷ مورد دیگر

Dr. Karim Sabra is a Professor at the George W. Woodruff School of Mechanical Engineering , Georgia Institute of Technology, specializing in Acoustics and Dynamics . He holds a Ph.D. from the University of Michigan (2003) and joined Georgia Tech in 2007 as an Assistant Professor. His research integrates theoretical and experimental approaches to study wave propagation in diverse fields including structural health monitoring, biomechanics, and ocean acoustics. Key areas of focus include passive imaging techniques using ambient noise and diffuse wave fields, with applications in non-invasive monitoring of mechanical systems and seismoacoustic environments. Education: Ph.D., University of Michigan, 2003 M.S., University of Michigan, 2000 M.Sc., École Nationale Supérieure de Techniques Avancées (France), 2000 Research Interests: Dr. Sabra’s work spans acoustics, structural health monitoring, biomechanical systems evaluation, underwater acoustics, and geophysics . Recent projects include developing passive elastography techniques for soft tissues using physiological vibrations and exploring ambient noise-based tomography for ocean environments. His interdisciplinary approach bridges multi-scale engineering challenges with multi-wave tools (acoustical, electrical, optical). Publications: His work focuses on advanced acoustic technologies, including underwater communication systems, passive acoustic identification tags, and ray-based tomography methods. Themes include seamount effects on sound propagation, machine learning for acoustic modeling, and environmental sensing using shipping noise. Awards: R. Bruce Lindsay Award (2011) Fellow of the Acoustical Society of America (2007) Institute of Acoustics A.B. Wood Medal (2009) Advising & Grants: Dr. Sabra mentors graduate students in acoustics and wave phenomena, emphasizing interdisciplinary collaboration. His research is supported by grants focused on underwater acoustics, environmental sensing, and biomedical applications. Labs/Teams: His research group develops novel sensors and algorithms for oceanographic and biomedical applications, collaborating with industry and academic partners.

• Data Science
• Machine Learning
• Harmonic Analysis
• +۷ مورد دیگر

Mauro Maggioni is a Professor in the Departments of Mathematics and Applied Mathematics and Statistics at Johns Hopkins University. His research focuses on the mathematical foundations of Data Science, with applications in molecular dynamics, hyperspectral imaging, and reinforcement learning. He employs techniques from Harmonic Analysis, Approximation Theory, and Probability to develop scalable algorithms, particularly multiscale methods for analyzing high-dimensional data. Maggioni’s work bridges theoretical mathematics and practical applications, including cardiac electrophysiology modeling, unsupervised segmentation of hyperspectral images, and reduced-order modeling of complex systems. Education: B.S. in Mathematics from Università degli Studi in Milan, Italy; Ph.D. in Mathematics from Washington University in St. Louis. He held a Gibbs Assistant Professorship at Yale before moving to Duke University and later becoming a Bloomberg Distinguished Professor at JHU. Research Interests: Mathematical foundations of Data Science, Machine Learning, Partial Differential Equations, and their applications in physical and biological systems. Notable contributions include diffusion wavelets, interaction kernel learning, and multiscale geometric analysis of molecular dynamics data. Scientific Awards: Popov Prize in Approximation Theory (2007), NSF CAREER Award and Sloan Fellowship (2008), Fellow of the American Mathematical Society (2013), Simons Fellowship (2020). Advising & Grants: Maggioni mentors postdocs and students in areas like stochastic systems and signal processing. His group’s work is supported by Simons Foundation grants, NSF funding, and collaborations with institutions like MINDS and CIS at JHU. Labs/Teams: Leads a research group focused on data-driven discovery in mathematics and applied sciences, emphasizing interdisciplinary collaboration across computational methods, statistics, and domain-specific applications.

Zixiang Xiongمشاهده پروفایل

استاد

• Machine Learning
• Image/Video Processing
• Network Information Theory
• +۷ مورد دیگر

Zixiang Xiong is a Professor and Associate Department Head in the Department of Electrical and Computer Engineering at Texas A&M University, holding the Robert M. Kennedy '26 Endowed Professorship II. He earned his Ph.D. in Electrical Engineering from the University of Illinois at Urbana-Champaign in 1996. His career includes roles at Princeton University, University of Hawaii, and Texas A&M since 1999. Education: Ph.D., Electrical Engineering, University of Illinois at Urbana-Champaign, 1996 Visiting Research Associate, Princeton University, 1995–1997 University of Hawaii, 1997–1999 Research Interests: Focuses on machine learning, image/video processing, federated learning, network information theory, biomedical engineering, and communications. His work spans distributed source coding, genomic signal processing, and energy-efficient systems. Publications & Awards: Over 200 publications, including seminal works on distributed video coding and network information theory. Notable awards include the NSF Career Award (1999), ONR Young Investigator Award (2001), IEEE Fellow (2006), and the ECE Outstanding Faculty Award (2024). His research has led to patents in video compression and multimedia systems. Grants & Advising: Active in NSF-funded projects on coding theory and energy-delay tradeoffs. Advises numerous PhD and MS students, with over 50 alumni in academia and industry. Collaborates on biomedical imaging, remote sensing, and federated learning initiatives. Labs & Teams: Leads a dynamic research group at Texas A&M, focusing on cutting-edge projects in signal processing and machine learning applications. Collaborates with industry and governmental agencies on applied research.

Fatemeh Mollaeiمشاهده پروفایل

مدرس

• Motor Speech Disorders
• Parkinson’s Disease
• Neuroimaging
• +۴ مورد دیگر

Fatemeh Mollaei is a Lecturer in Clinical Language Sciences at the University of Reading, affiliated with the School of Psychology and Clinical Language Sciences. She is a core member of the Centre for Integrative Neuroscience and Neurodynamics (CINN), focusing on neurophysiological mechanisms of speech disorders. Her work integrates behavioral, electrophysiological, and neuroimaging techniques to study Parkinson’s disease (PD) and develops neuro-rehabilitation methods using non-invasive brain stimulation (e.g., TMS, tDCS). Her research explores how sensory and motor systems interact during speech production in PD, employing tools like EEG, fMRI, and MEG. She investigates microstructural white matter changes and auditory processing deficits linked to speech impairments, aiming to translate findings into clinical interventions. Her studies also address broader topics like sensorimotor adaptation and stuttering, emphasizing translational neuroscience. Publications highlight trends in neuroimaging of speech disorders, auditory feedback mechanisms, and neuroplasticity in PD. While no formal awards are listed, her contributions to understanding speech motor control and rehabilitation practices are significant. Advising and grant details are not explicitly provided, but her involvement in interdisciplinary CINN projects suggests active collaborative research. Labs/Teams: Active contributor to the Centre for Integrative Neuroscience and Neurodynamics (CINN) at the University of Reading, collaborating on translational neuroscience projects.

• Robotics
• Autonomous Systems
• Unmanned Aerial Vehicles (UAVs)
• +۹ مورد دیگر

Nabil Aouf is a Professor of Robotics and Autonomous Systems in the Department of Electrical and Electronic Engineering at City, University of London, a position he has held since January 2019. Previously, from 2006 to 2018, he was Professor of Autonomous Systems at Cranfield University’s Defence and Security campus, where he also served as Head of the System and Autonomy Group and Research Lead of the Centre of Electronic Warfare, Information and Cyber. He earned his PhD in Electrical Engineering from McGill University Faculty of Engineering between 1999 and 2002. His research focuses on Robotics, Autonomous Systems, UAV Navigation, Computer Vision, and Fault-Tolerant Control . Key areas include visual odometry, sensor fusion (vision/IMU, RGBD, thermal-visible), robust control for UAVs, fault diagnosis in inertial systems, 3D perception, and autonomous landing. His work integrates theoretical control methods with real-time implementation in aerospace and defense contexts. His recent publications reflect a strong emphasis on robust optimization, multispectral vision, and real-time autonomous navigation. Trends indicate a focus on enhancing autonomy under uncertainty—through illumination-invariant stereo matching, L∞ optimization, and robust feature matching—particularly for UAVs operating in challenging environments. Nabil Aouf has collaborated extensively with researchers such as M. Richardson, O. Araar, T. Mouats, and M. Boulekchour across numerous projects in UAV control, sensor fusion, and autonomy. While no scientific awards are listed in the provided text, his leadership roles and sustained publication record in high-impact journals and conferences underscore his academic contributions. He has supervised or collaborated with several advisees including S.H. Almutairi, L. Chermak, I. Vitanov, and D. Nam, contributing to both theoretical developments and practical implementations in autonomous systems. His work has applications in aerospace, defense, planetary exploration, and critical infrastructure inspection.

Jiayun Wangمشاهده پروفایل

پژوهشگر ارشد

• Computer Vision
• Machine Learning
• Computational Imaging
• +۳ مورد دیگر

Jiayun (Peter) Wang is a Postdoctoral Scholar Research Associate in the Department of Computing and Mathematical Sciences at the California Institute of Technology (Caltech). His research focuses on advancing AI-driven solutions in medical imaging, computational imaging, and computer vision. Current projects emphasize applying deep learning to diagnose ocular conditions like dry eye syndrome and improving 3D reconstruction techniques. Collaborations with institutions such as UC Berkeley, Microsoft, and NVIDIA highlight his interdisciplinary approach to solving real-world medical and imaging challenges. Research Interests: Medical AI and Healthcare Analytics Deep Learning Applications in Ophthalmology 3D Reconstruction and Scene Understanding Physics-Informed Neural Networks Compressed Sensing MRI Key Contributions: Developed machine learning models predicting dry eye-related outcomes using meibography images Pioneered physics-aware neural operators for ultrasound lung aeration mapping Advanced open-vocabulary 3D object detection systems Labs/Teams: Collaborates with Caltech's AI4Health initiative and NVIDIA's research group, contributing to medical imaging advancements through interdisciplinary teams.

• Atomic Force Microscopy
• Nanotechnology
• Mechatronics
• +۴ مورد دیگر

Amir Farokh Payam is a Senior Lecturer in Electronics and Software at the School of Engineering, Ulster University, UK since 2019. He holds a PhD in Electronics Engineering-Nanotechnology and has previously worked at Instituto de Ciencia de Materiales de Madrid (2012–2015), Durham University (2016–2018), and University of Bristol (2018–2019). Education: B.Sc. and M.Sc. in Electrical and Electronics Engineering, PhD in Electronics Engineering-Nanotechnology His research focuses on dynamic Atomic Force Microscopy (AFM) , NEMS/MEMS , Surface Science , and Applied Nonlinear Control . Recent work explores nonlinear harmonics in AFM, solid-liquid interfacial dynamics, and single-cell biomechanical profiling. He leads projects on quantum sensor fabrication and cancer cell viscoelasticity analysis. Key trends in his 15 most recent publications (2025–2023) include advancements in nanoscale imaging , multifrequency AFM , viscoelastic material analysis , and biomedical applications such as viral protein sensing and corneal cell profiling. Collaborative projects span institutions in Ireland, Spain, and the UK. Scientific Awards: Editor's Highlights in Journal of Applied Physics (2018) and Nanotechnology (2015) Best Innovative Idea, Second International R&D Award of Iran (2012) Distinct Graduate Student, University of Tehran Visiting Study Scholarship, Instituto de Microelectronica de Madrid (2010) M.Sc. First Class Student (top among 15) He serves as Unit Director for Mechatronics II and Electronics II modules and supervises BEng/MEng research projects. Active research grants include Royal Society funding (2024–2026) for cancer cell biomechanics and an ongoing 2022–2026 project on solid-liquid interface dynamics.

• Computational Imaging and Photography
• Computer Vision and Graphics
• Sensors and Mixed-signal Circuits
• +۲ مورد دیگر

Suren Jayasuriya is an Associate Professor at Arizona State University's The GAME School, with joint appointments in the School of Electrical, Computer and Energy Engineering (ECEE) and the Department of Arts, Media and Engineering (AME). He is also an Affiliate Faculty Member at the Mary Lou Fulton College for Teaching and Learning Innovation. His lab, the Imaging Lyceum, focuses on transdisciplinary research bridging computational imaging, computer vision, sensors, and STEAM education. Education Ph.D. Electrical and Computer Engineering, Cornell University (2017) M.S. Electrical and Computer Engineering, Cornell University (2015) B.S. Mathematics, University of Pittsburgh (2012) B.A. Philosophy, University of Pittsburgh (2012) Research Focus Dr. Jayasuriya's work integrates optics, computational photography, and machine learning to develop novel imaging systems. His research spans: Computational cameras and light transport analysis Atmospheric turbulence modeling and video restoration Neural volumetric reconstruction for sonar/radar STEAM education frameworks for K-12 teachers Philosophical aspects of imaging and representation His lab emphasizes interdisciplinary collaboration across engineering, arts, and humanities. Publication Trends Recent publications demonstrate strong focus on computational imaging (45%), AI/ML applications (30%), and educational technology (25%). Dominant themes include turbulence mitigation in videos, neural rendering for sonar/radar, sensor fusion, and AI curriculum development for middle schools. Work frequently appears in top venues like CVPR, SIGGRAPH, and IEEE Transactions. Awards Image Electronics Technology Excellence Award (IIEEJ, 2021) Best Demo Awards: IEEE ICCP 2019, MIRU 2018 Best Paper Award: IEEE ICCP 2014 ASEE Diversity Paper Finalist (2020) Teaching Honors: Fulton Top 5% Award (2019, 2021), ASU Game Changing Faculty (2021) Teaching & Advising Teaches graduate/undergraduate courses including Machine Vision (EEE 515), Minds and Machines (AME 400), and thesis supervision. Leads NSF-funded projects on computational imaging education and AI teacher training. Mentors students through the Imaging Lyceum lab with projects spanning optics, philosophy, and educational technology. Lab & Collaborations Directs the Imaging Lyceum, emphasizing Aristotle-inspired collaborative research. The lab works on: computational cameras, STEAM education, sensor development, and philosophical inquiries into imaging. Collaborates with Carnegie Mellon Robotics Institute and international partners. Funded by NSF, NEH, and industrial partners for projects in sonar imaging, heat resiliency sensing, and educational AI.

• Human Neurophysiology
• Motor Learning
• Neurorehabilitation
• +۶ مورد دیگر

Professor Charlotte Stagg is based at the Nuffield Department of Clinical Neurosciences (NDCN) within the University of Oxford . She serves as Associate Director of the Oxford Centre for Integrative Neuroimaging and holds a Beale Fellow in Medicine position at St Hilda's College. Her research focuses on the physiological mechanisms of motor learning and stroke recovery, utilizing multimodal neuroimaging and brain stimulation techniques. Research Interests : GABA signaling, neuroplasticity, transcranial ultrasound, stroke neurorehabilitation Techniques : 7T MRI, MEG, non-invasive brain stimulation, neurochemistry Selected Scientific Awards : Wellcome Trust Senior Research Fellow Beale Fellow in Medicine, St Hilda's College Collaborations : Leads the Physiological Neuroimaging Group (PiNG), part of the Neuroplastics Collaborative Network with groups led by Heidi Johansen-Berg and Jacinta O'Shea. Current advisees include DPhil student Birtan Demirel and visiting researchers from HEC Montréal and The University of Manchester.

• Digital Circuits
• Digital Signal Processing
• Machine Learning
• +۱۰ مورد دیگر

Maurizio Martina is a Full Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino. He is a member of the Interdepartmental Center PEIC - Power Electronics Innovation Center and serves as an Associate Editor for the IEEE Transactions on Circuits and Systems I (2018-2023). His research focuses include: Digital circuits and signal processing Machine learning hardware architectures RISC-V extensions and post-quantum cryptography VLSI design for edge computing and IoT Recent publications emphasize cryptographic hardware implementations (CHIMERA, Keccak co-processors), RISC-V integration methodologies, and privacy-preserving neural network frameworks. His work spans VLSI architectures for video processing, bio-inspired electronics, and error correcting codes, with applications in cybersecurity, robotics, and biomedical systems. Scientific Recognition : Premio Nazionale Innovazione (2013) Premio dei Premi (2014) He supervises 12 PhD students across cycles 35-40 in Electrical, Electronics and Communications Engineering, including: Valeria Piscopo (2024-in progress) Alessandra Dolmeta (2022-in progress) Luigi Giuffrida (2022-in progress) Walid Walid (2019-2023) As part of the VLSILAB Group , his research explores hardware accelerators for machine learning, post-quantum cryptography on RISC-V, and bio-inspired embedded systems. Teaching activities include courses on Integrated Systems Architecture and Hardware & Wireless Security at Politecnico di Torino and Università di Pavia.