جستجوی استاد راهنمای دانشگاهی

Roel Baetsمشاهده پروفایل

استاد

• Silicon Photonics
• Photonic Integrated Circuits
• Optical Sensors
• +۴ مورد دیگر

Roel Baets is a Professor at Ghent University's Department of Information Technology (INTEC), affiliated with the Faculty of Engineering and Architecture. He leads research in silicon photonics, photonic integrated circuits, and their applications in biomedical engineering, environmental monitoring, and sensor technology. His work bridges academic and industrial collaboration through platforms like ePIXfab and Imec. Key roles include leading the Photonics Research Group and serving as a Fellow of the Optical Society (OSA) and IEEE Photonics Society. His research focuses on developing innovative photonic sensors (e.g., laser Doppler vibrometers, optical fiber Bragg sensors) and advancing heterogeneous integration techniques. Recent projects include clinical validation of cardiovascular monitoring systems and non-contact photoacoustic imaging. He also explores sustainable photonics solutions and environmental applications, such as solar radiation impact studies and CO₂ sensing. Notable achievements include pioneering work in micro-transfer printing for III-V/Si photonics and developing the Turbidimeter for low-resource healthcare settings. His awards reflect his contributions to photonics' theoretical and applied advancements, emphasizing interdisciplinary applications in medicine and sustainability.

• Geotechnical Earthquake Engineering
• Seismic Hazard
• Soil-Structure Interaction
• +۱۲ مورد دیگر

Mauro Aimar is a Fixed-term Assistant Professor in the Department of Structural, Geotechnical and Building Engineering (DISEG) at Politecnico di Torino, Italy. He is affiliated with the College of Civil and Building Engineering and serves as an invited member of the College of Environmental and Land Engineering. His academic and research activities focus on geotechnical earthquake engineering, seismic hazard, soil-structure interaction, and structural health monitoring. His research interests include: Seismic response and site characterization Scour of foundations and bridge piers Modal analysis and damping ratio estimation Numerical modeling of unsaturated soils Experimental testing in civil engineering Aimar's recent publications (2023–2025) center on seismic performance of bridges under scour, advanced site characterization using surface waves, and numerical modeling of soil-structure systems. His work combines experimental, numerical, and field-based approaches to assess infrastructure resilience. Key themes include Rayleigh wave analysis, MASW testing, FEM modeling of infiltration, and dynamic monitoring of bridge piers. He supervises PhD student Marlio Molina Manrique in the Civil and Environmental Engineering program. His teaching contributions span multiple degree levels, including courses on Soil-Structure Interaction, Geotechnical Earthquake Engineering, Seismic Risk, and InfraBIM. He has no listed scientific awards in the provided sources. Mauro Aimar actively contributes to research projects involving testing and measurement in civil engineering, with a focus on seismic resilience and infrastructure safety. He collaborates with Prof. Sebastiano Foti and other researchers in geotechnical and earthquake engineering.

Jon Fagerströmمشاهده پروفایل

استاد مهمان

• Audio Signal Processing
• Digital Signal Processing
• Acoustics
• +۵ مورد دیگر

Jon Fagerström is a Visiting Professor at the Department of Information and Communications Engineering, Aalto University. His work focuses on advanced audio signal processing techniques, particularly in velvet noise applications, artificial reverberation, and feedback delay networks. He contributes to the UN Sustainable Development Goal of Quality Education through his academic research in sound engineering. Academic Affiliation: Aalto University Department: Information and Communications Engineering Primary Research Areas: Audio Signal Processing, Acoustics, Sound Synthesis, Virtual Reality Audio Research trends in his publications include innovations in reverberation modeling , decorrelation techniques , and velvet noise applications across audio engineering, VR sound environments, and music technology. Collaborations with researchers like Niko Meyer-Kahlen, Sebastian Schlecht, and Vesa Välimäki highlight his work in feedback delay networks and binaural audio processing.

• Neuroscience
• Biomedical Engineering
• Transcranial Magnetic Stimulation
• +۵ مورد دیگر

Heikki Sinisalo is a Visiting Professor at the Department of Neuroscience and Biomedical Engineering at Aalto University. His research focuses on advanced brain-stimulation technologies, particularly transcranial magnetic stimulation (TMS) integrated with magnetic resonance imaging (MRI) and digital signal processing . Education: Doctor of Technology (Teknillinen fysiikka) – Aalto University, 30 Jun 2025 Diploma Engineer (Tietotekniikka) – Aalto University, 16 Nov 2018 Bachelor of Technology (Sähkötekniikka) – Aalto University, 20 Jun 2016 Sinisalo has pioneered multi-locus TMS systems for clinical and preclinical applications, emphasizing high-precision timing , ultra-high-field MRI compatibility , and pulse-width modulation to enhance stimulation accuracy. His work bridges engineering with neuroscience, targeting cortical and brain-stimulation advancements. In recent years, Sinisalo’s publications highlight innovations in closed-loop TMS , multi-coil configurations , and rapid stimulation protocols . Key technologies include field-programmable gate arrays , capacitor voltage optimization , and digital interfaces for real-time neuromodulation. He actively contributes to research infrastructure, having organized the TMS–EEG Summer School and Workshop (2022) , fostering collaboration between engineers and neuroscientists. His work also includes open-access datasets, such as the High-Precision Timing Method for Closed-Loop TMS (Zenodo, 2024).

Zheng Pengمشاهده پروفایل

پژوهشگر

• Biomedical Engineering
• Neonatology
• Machine Learning
• +۳ مورد دیگر

Zheng Peng is a postdoctoral researcher at Eindhoven University of Technology (TU/e) specializing in biomedical diagnostics and infant monitoring systems. He completed his Ph.D. in Applied Physics at TU/e in 2024 and now works in the School of Applied Physics and Science Education under the Biomedical Diagnostics Lab . Education : Ph.D. in Applied Physics (TU/e), M.Sc. in Applied Physics (TU/e) Projects : HASTA, PICASSO WP3 Advanced NICU Sensing, and PICASSO SPS: Perinatal, Cardiovascular and Sleep Medtech Solutions His research focuses on developing machine learning and sensor-based systems to analyze preterm infant motion patterns, cardiorespiratory interactions, and sepsis prediction through non-invasive technologies like fiber-optic mattresses and multi-channel physiological signals. This work has direct applications in improving neonatal intensive care outcomes. Recent publications highlight advancements in infant motion quantification , central apnea detection , and late-onset sepsis prediction . Collaborations include Maxima Medical Center , Philips Research , and international institutions like Wuhan University of Technology.

Irena Zivkovicمشاهده پروفایل

مدرس

• MRI Hardware Development
• Antenna Engineering
• RF Coil Design
• +۲ مورد دیگر

Irena Živković is a Lecturer in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e), where she specializes in Integrated Circuits and leads research in MRI Hardware Development. She is affiliated with the Center for Care & Cure Technology Eindhoven, focusing on cutting-edge biomedical engineering solutions. Her work bridges antenna design, electromagnetic systems, and clinical imaging technology. Her research centers on optimizing MRI hardware for ultra-high-field (7T+) and low-field systems, with innovations in: Coaxial cable coils for enhanced signal-to-noise ratios Monopole antennas for head/spine imaging Twisted-pair transmission lines for flexible, robust array elements Dielectric materials to improve transmit efficiency Recent publications (2023-2025) demonstrate a strong focus on coil miniaturization, electromagnetic interference mitigation, and SAR reduction—critical for advancing high-resolution diagnostic imaging. She teaches specialized courses including Electromagnetic Fields in MRI and Introduction to NMR/MRI , emphasizing hardware-software integration in medical imaging systems.

Anton Sirotaمشاهده پروفایل

استاد

• Neuroscience
• Neurophysiology
• Learning and Memory
• +۵ مورد دیگر

Prof. Anton Sirota is a Professor and Research Group Leader at the LMU Division of Neurobiology and a member of the Bernstein Center for Computational Neuroscience (BCCN Munich). He leads the MSc Neuroscience Examination Committee and is a full member of the Graduate School of Neural and Behavioral Sciences (GSN). His research focuses on mechanisms of information representation and propagation in cortical networks, particularly between the neocortex and hippocampus during learning and sleep. He employs advanced techniques including multichannel electrophysiology, optogenetics, and virtual reality to study neural dynamics in behaving rats. His lab uses graphene-based sensors and multiplexed neural probes for high-resolution brain mapping. Research Interests: Neurophysiological mechanisms of learning and memory consolidation Cortico-hippocampal network dynamics Neural oscillations and their role in information transfer Development of neurotechnologies for brain activity recording (e.g., graphene sensors, SiNAPS probes) Role of respiration in coordinating neural networks Advising: Current advisee Arash Shahidi . Graduated students include Dr. Nicholas Del Grosso , Dr. Andrey Sobolev , Dr. Elena Itzcovich , and Fabián Štoček . Labs/Teams: Active in the Cognitive Neurophysiology Lab , leveraging cutting-edge tools like multishank silicon probes and optogenetic modulation. Collaborates on projects involving virtual reality systems for rodent behavior studies and computational modeling of neural networks.

Jennifer Pestanaمشاهده پروفایل

مدرس ارشد

• Numerical Linear Algebra
• Scientific Computing
• Krylov Subspace Methods
• +۷ مورد دیگر

Dr Jennifer Pestana is a Senior Lecturer in the Department of Mathematics and Statistics at the University of Strathclyde, Faculty of Science. She has been a faculty member since 2015 and is actively involved in research and academic leadership. She is a principal investigator on multiple grants and serves as an editor for SIAM publications. Education: DPhil, University of Oxford, 2012 Postdoctoral positions: University of Manchester, University of Oxford Her research centers on numerical linear algebra and its applications in scientific computing . She investigates the convergence of Krylov subspace methods , develops preconditioners for specific applications, and explores the use of tropical algebra for matrix pre-scaling. Current projects involve fast solvers for fractional diffusion and analysis in broadband signal processing . Her work bridges theoretical numerical analysis with practical computational challenges. The recent publications reflect a strong focus on iterative methods, matrix analysis, and signal processing. Common themes include Toeplitz matrices , eigenvalue decomposition , preconditioning , and covariance estimation , demonstrating her expertise in both algorithmic development and application-driven numerical methods. Scientific Awards: Best Student Paper Award (2018) Dr Pestana actively supervises students and leads research projects, including EPSRC-SFI and Strathclyde ISP Joint PhD initiatives. She has secured significant funding for work on Krylov methods and efficient solvers. Her professional service includes organizing major conferences such as the Biennial Conference on Numerical Analysis and serving on program committees, including for the International Linear Algebra Society. She is also an invited speaker and visiting researcher, demonstrating national and international recognition. She is involved with research teams focused on numerical analysis and scientific computing, contributing to collaborative efforts in developing novel preconditioned iterative solvers. Her lab and project groups work on both theoretical and applied aspects of linear algebra in PDEs and signal processing.

David Tsaiمشاهده پروفایل

مدرس ارشد

• Biomedical Engineering
• Microelectronics
• Neural Interfaces
• +۴ مورد دیگر

Dr. David Tsai is a Senior Lecturer at the University of New South Wales (UNSW), jointly appointed between Biomedical Engineering and Electrical Engineering. He leads the Biomedical Microsystems Lab , focusing on miniature microelectronic devices for brain-machine interfaces and subcutaneous biosensing. His research has been continuously funded by the NHMRC since 2013, including an ongoing Ideas grant for soft brain-machine interfaces. He has secured >$3.8M in total funding, with support from the Kavli Foundation and ARC Linkage Infrastructure Grants . His work has appeared in Nature Communications , Nature Nanotechnology , and IEEE Transactions on Biomedical Circuits and Systems . Scientific Recognition: IEEE EMBC Student Paper Award (twice) IEEE EMBC Best Papers Award NHMRC CJ Martin Fellowship (2013-2017) Kavli Foundation Postdoctoral Fellowship (2012-2013) Education: PhD in Biomedical Engineering (2012), UNSW MBiomedE (2007), UNSW BE (Software, First Class Honours) (2007), UNSW Research Themes: Development of ultra-dense microelectrode arrays for cellular-resolution electrophysiology, computational modeling of retinal responses to electrical stimulation, and standardization of neurotechnology data formats. His lab collaborates with industry partners like LeafLabs LLC , BlackRock Microsystems , and Contactile .

Patrick B Cunninghamمشاهده پروفایل

استادیار

• Electro-Optics
• Space Domain Awareness
• Polarimetrics
• +۶ مورد دیگر

Maj Patrick B. Cunningham is an Assistant Professor of Electrical Engineering at the Air Force Institute of Technology (AFIT), Wright-Patterson Air Force Base, OH. He holds a PhD in Electrical Engineering from AFIT (2022) and serves in an active-duty capacity in the U.S. Air Force, teaching electro-optics courses and conducting research in optical imaging and space domain technologies. Education: Ph.D., Electrical Engineering, Air Force Institute of Technology, 2022 M.S., Electrical Engineering, Air Force Institute of Technology, 2016 B.S., Electrical Engineering, Rose-Hulman Institute of Technology, 2006 His research focuses on electro-optical systems, particularly in the areas of polarized light imaging, space surveillance, and atmospheric distortion correction. He specializes in multichannel deconvolution techniques for enhanced target identification using optical sensors. His work supports military space operations and remote sensing applications. No recent publications are listed in the provided text, so no article trends can be determined at this time. Scientific Awards: No awards listed in the provided text. As a faculty member in the AFIT pipeline, Maj Cunningham is involved in academic training and likely advises graduate students, though no current advisees are named. His research is supported through U.S. Air Force channels, particularly via AFRL and operational deployments. He previously served in the C-17 SPO, AFRL/RQ, and AFRL/RV (Space Vehicles Directorate), and was deployed as Executive to the AFCENT/A3 Commander for eight months. Maj Cunningham is part of the Electrical Engineering faculty at AFIT, contributing to the development of advanced electro-optic technologies for national defense. His work bridges academic research and operational military needs, particularly in space-based optical sensing and characterization.

Bracha Lauferمشاهده پروفایل

مدرس

• Acoustic Source Localization
• Speech Signal Processing
• Gaussian Processes
• +۳ مورد دیگر

Dr. Bracha Laufer is a senior lecturer at the School of Electrical Engineering , part of the Iby and Aladar Fleischman Faculty of Engineering at Tel Aviv University. Her research focuses on acoustic source localization, speech signal processing, and machine learning techniques for audio engineering. Her recent work explores conformal prediction and manifold-based approaches for robust source localization, deep learning architectures for sound source separation, and simplex geometry in multichannel signal analysis. These publications highlight interdisciplinary applications of machine learning and statistical methods in acoustics. Dr. Laufer's research integrates Bayesian inference , probabilistic graphical models , and uncertainty quantification to address challenges in adverse acoustic environments. She has contributed to advancements in multi-microphone speaker localization and speech inpainting .

• Adaptation and Learning over Networks
• Social Learning
• Statistical Inference on Graphs
• +۳ مورد دیگر

Vincenzo Matta is a Full Professor at the Department of Information and Electrical Engineering and Applied Mathematics, University of Salerno, Italy. His research focuses on adaptation and learning over networks, social learning, statistical inference on graphs, and security in communication networks. He has authored over 130 articles in international journals and conference proceedings and serves in editorial roles for several IEEE journals. Current Affiliation: University of Salerno Editorial Roles: Associate Editor for IEEE Open Journal of Signal Processing; former Senior Area Editor for IEEE Signal Processing Letters Workshop Participation: Speaker at the 3rd Imperial Workshop on Intelligent Communications, Imperial College London His work explores belief formation and diffusion in cognitive agent networks, with applications to social networks, biological systems, and robotic swarms. Recent research trends include adaptive social learning, partial information sharing, and social machine learning. Dr. Matta has held leadership roles in IEEE technical committees, including membership in the Sensor Array and Multichannel Technical Committee and representation on the IEEE SPS Steering Committee.

Bruce DENBYمشاهده پروفایل

استاد

• Speech Processing
• Silent Speech Interfaces
• Telecommunications
• +۴ مورد دیگر

Bruce DENBY is a Professor at Sorbonne University specializing in speech processing, telecommunications, and indoor localization. His research spans multiple disciplines including computer science, physics, and environmental science with significant contributions across these fields. His primary research interests include: Silent Speech Interfaces and speech restoration technologies Indoor localization using wireless networks and GSM fingerprints Telecommunications and signal processing Environmental modeling of road dust and air pollution Machine learning applications in speech recognition Dr. DENBY's research trajectory shows evolution from early work in high energy physics to speech processing and wireless communications, with recent publications (2022-2025) demonstrating continued innovation in WiFi analytics, client density mapping, and future speech interfaces. His work increasingly integrates deep learning techniques while maintaining focus on practical applications, particularly for speech restoration and privacy-preserving network analysis. Notable scientific achievements: Chester Sall Award Paper (2012) for work on FPGA-based FM broadcast receivers Significant contributions to the Silent Speech Challenge benchmark with deep learning approaches Development of the NORTRIP model for road dust emissions Highly cited work on Silent Speech Interfaces (over 500 citations) Dr. DENBY has secured research funding across multiple domains, collaborating with institutions across Europe. His work demonstrates strong interdisciplinary connections between speech technology, wireless communications, and environmental science, with applications ranging from assistive technologies to urban air quality management.

Mahsa Shoaranمشاهده پروفایل

استادیار

• Neural interfaces
• Neuroprosthetics
• Analog and mixed-signal integrated circuits
• +۵ مورد دیگر

Mahsa Shoaran is a Tenure-Track Assistant Professor at EPFL (École Polytechnique Fédérale de Lausanne) jointly appointed at the Center for Neuroprosthetics and the Institute of Electrical Engineering . She is also the founding director of the Integrated Neurotechnologies Laboratory (INL) and contributes to several doctoral programs and teaching missions across EPFL’s School of Engineering (STI). Education: PhD in Electrical Engineering, EPFL (2015) M.Sc. & B.Sc., Sharif University of Technology Postdoctoral Fellow, California Institute of Technology (Caltech) (2015-2017) Former Assistant Professor, School of Electrical and Computer Engineering, Cornell University (2017-2019) Research Focus: Dr. Shoaran’s work sits at the convergence of integrated circuit design , machine learning , and neuroscience . Her group develops ultra-low-power, miniaturized system-on-chips (SoCs) capable of real-time neural recording , pathology detection , and closed-loop therapeutic intervention such as adaptive neurostimulation. Machine-learning algorithms running on-chip enable precise symptom detection in neurological and psychiatric disorders, while advanced circuit techniques guarantee energy efficiency suitable for long-term implantable or wearable neural interfaces. Scientific Awards & Grants: ERC Starting Grant 2021 Google Faculty Research Award in Machine Learning 2019 Swiss NSF Postdoctoral Fellowships NSF Award for Young Professionals – Smart & Connected Health MIT EECS Rising Star 2015 Doctoral Advising & Service: She currently supervises 14 PhD students in the Integrated Neurotechnologies Laboratory. Additionally, she serves on the PhD program committees for Electrical Engineering (EDEE), Microsystems & Microelectronics (EDMI), and contributes to the Neuro-X and SEL teaching programs. She is a Technical Program Committee member for IEEE CICC and serves on the Student Research Preview committee for ISSCC. Laboratory & Collaborative Teams: The Integrated Neurotechnologies Laboratory (INL) at EPFL Campus Biotech in Geneva hosts her interdisciplinary team of circuit designers, machine-learning researchers, and neuroscientists. The lab collaborates closely with clinicians to translate innovations into real-world neuroprosthetic and diagnostic devices.

Emily Arnoldمشاهده پروفایل

دانشیار

• Multifunctional Structures
• Remote Sensing
• Unmanned Aerial Systems
• +۳ مورد دیگر

Emily Arnold is an Associate Professor in the Department of Aerospace Engineering at the University of Kansas, where she also serves as Graduate Program Director. Her research centers on multifunctional aerospace structures, remote sensing technologies, and unmanned aerial systems (UAS) for glaciological applications. Key trends in her recent publications highlight advancements in reconfigurable radar systems for UAS-based ice and snow sounding, wing-mounted antenna design under flight stress, and 3D-printed microwave components. She merges aerospace structural analysis with electromagnetic simulation to enhance UAV sensor performance in polar environments. NSF CAREER Award (2019) for UAS radar systems NSF MRI Grant (2022) for radar instrumentation Her work at CReSIS (Center for Remote Sensing of Ice Sheets) supports Operation IceBridge and COLDEX projects, focusing on oldest ice core exploration. She explores the intersection of structural dynamics, microwave engineering, and environmental monitoring via airborne platforms.