جست‌وجوی استاد و پژوهشگر

Wout Josephمشاهده پروفایل

استاد

• electromagnetic field exposure assessment
• in-body electromagnetic field modelling
• electromagnetic medical applications
• +۱۲ مورد دیگر

Wout Joseph is a Professor in the domain of Experimental Characterization of wireless communication systems at Ghent University (Belgium), where he has been working since October 2009. He is also an IMEC Principal Investigator since 2017. His research is conducted within the wireless, acoustics, environment & expert systems (WAVES) research unit at the Department of Information Technology (INTEC). Dr. Joseph was born in Ostend, Belgium on October 21, 1977. He received his M.Sc. degree in electrical engineering from Ghent University in July 2000. From September 2000 to March 2005 he was a research assistant at the Department of Information Technology (INTEC), where his scientific work focused on electromagnetic exposure assessment around base stations for mobile communications related to health effects. This work led to his Ph.D. degree in March 2005. Professor Joseph's research expertise spans multiple domains within wireless communications and bioelectromagnetics. His primary research interests include electromagnetic field exposure assessment, in-body electromagnetic field modeling, electromagnetic medical applications, propagation for wireless communication systems, IoT, antennas and calibration. He also specializes in wireless performance analysis, industry 4.0 applications, wireless localization, and Quality of Experience metrics. His work is particularly notable for its focus on dosimetric studies in the radiofrequency range, where his research is ranked first in number of peer-reviewed studies. His research has practical applications in wireless network planning, occupational safety, and public health policy related to electromagnetic fields. His extensive publication record (over 886 publications with an h-index of 45 in ISI Web of Science and 66 in Google Scholar) demonstrates a clear trajectory from fundamental electromagnetic field measurements to applied research in industrial wireless networks and bioelectromagnetic applications. Recent work shows a strong emphasis on 5G exposure assessment across multiple European countries, millimeter-wave channel modeling, and the application of machine learning techniques to exposure assessment and wireless localization. EBEA council board member (2015-2018) EBEA board member at large (2019) Bioelectromagnetics Society board member (2022) Bioelectromagnetics Society board member (2024) 24 research awards Professor Joseph leads significant research efforts in electromagnetic field exposure assessment, with particular emphasis on developing measurement methodologies and computational models for real-world exposure scenarios. His work bridges theoretical electromagnetic modeling with practical applications in wireless communications and bioelectromagnetics. His research group within the WAVES unit is highly active in both theoretical and experimental aspects of wireless communications and bioelectromagnetics, with current projects focusing on 5G exposure assessment across Europe, millimeter-wave channel modeling for data centers and industrial environments, and the development of novel exposure assessment methodologies using advanced signal processing and machine learning techniques.

• Self-test and self-calibration of circuits
• Fault-tolerant systems
• Analog and mixed-signal circuits
• +۳ مورد دیگر

Sule Ozev is a Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University (ASU). She holds a Ph.D. in Computer Science and Engineering from the University of California, San Diego (2002), and has been a faculty member since 2008. Her research focuses on analog and mixed-signal circuit testing, fault-tolerant systems, and RF circuit reliability. She has published over 100 papers and holds a U.S. patent. Notable awards include the NSF CAREER Award (2006) and the ASU Joseph Palais Distinguished Faculty Scholar Award (2023-2024). Her education includes: Ph.D., Computer Science and Engineering, UC San Diego (2002) M.S., Computer Science and Engineering, UC San Diego (1998) B.S., Electrical Engineering, Bogazici University, Turkey (1995) Research Interests: Self-test and calibration techniques for analog/RF circuits, fault simulation, and reliability enhancement. Recent work includes BIST solutions for power management units, MEMS sensor calibration, and IoT security. Publications span RF impedance measurement, low-power systems, and marine sensor applications. Awards also include best paper recognitions at IEEE VLSI Test Symposium (2022) and European Test Symposium (2019). Grants include NSF-funded projects on adaptive test strategies and collaborative research on sensor networks. Service roles include associate editor for IEEE Transactions on VLSI Systems and program chairs for major conferences.

Jie Pengمشاهده پروفایل

استاد

• Graphical Models
• High Dimensional Inference
• Functional Data Analysis
• +۴ مورد دیگر

Jie Peng, Ph.D., is a Professor and Vice-Chair for Graduate Affairs in the Department of Statistics at the University of California, Davis. Her research focuses on statistical methodologies with applications in genomics, neuroimaging, and functional data analysis. She holds a Ph.D. from Stanford University and is actively involved in advancing statistical theory and its practical implementations in biomedical and computational sciences. Education Ph.D. in Statistics, Stanford University Research Interests Dr. Peng’s work spans several key areas including graphical models, high-dimensional inference, and neuroimaging analysis. She develops innovative statistical tools for analyzing complex biological data, such as tumor genomics and brain connectivity patterns derived from diffusion MRI. Her research emphasizes the interplay between theoretical statistics and real-world applications in healthcare and precision medicine. Professional Contributions She serves as an Associate Editor for the Journal of Computational and Graphical Statistics and has contributed to numerous high-impact publications. Her methods have been applied to identify biomarkers in ovarian cancer and to study brain lateralization using Human Connectome Project (HCP) data. Dr. Peng also leads efforts in developing computational frameworks for spatial transcriptomics and dynamic network modeling.

Patrick W. C. Hoمشاهده پروفایل

مدرس

• Memristor
• Non-volatile memories
• VLSI
• +۷ مورد دیگر

Dr. Patrick W. C. Ho is a Lecturer in the Department of Electrical & Computer Systems Engineering (ECSE) at Monash University Malaysia School of Engineering. He holds a PhD in Electronics Engineering from the University of Nottingham Malaysia Campus (2016), with research focusing on non-volatile FPGA architectures using memristors. His academic journey includes roles as a Scholarly Teaching Fellow and unit coordinator for courses like ECE2131 Electrical Circuits and ECE4063 Large Scale Digital Design. He has industry experience with Intel Microelectronics and Altera Corporation, alongside teaching A-level Physics at Methodist College Kuala Lumpur. Education: BEng (First Class Honours) in Engineering (2009) MSc in Science (2012) PhD in Electronics Engineering (2016) Research Interests: Dr. Ho specializes in memristor-based non-volatile memory systems, VLSI design, and FPGA architectures. His work bridges hardware design with emerging materials, as seen in his Q1 journal article on memristive LUTs. Collaborations with CAD-IT expand his focus into AI, image processing, and object recognition. Recent projects include studies on memristor substrate performance (2023–2026) and UAV communication reliability (2021–2024). Teaching and Industry Engagement: As ECSE’s Industrial Training Advisor and IAP representative, he actively connects academic curricula with industry needs. His teaching spans foundational engineering courses and advanced digital design modules. Labs and Collaborations: Active in CAD-IT partnerships for student FYP co-sponsorship. Research groups focus on nanotechnology, machine learning integration in UAV systems, and memristor material analysis.

Andreas Beyerمشاهده پروفایل

استاد

• Aging Research
• Proteomics
• Systems Biology
• +۵ مورد دیگر

Prof. Dr. Andreas Beyer holds a faculty position at the University of Cologne, affiliated with the Cluster of Excellence Cellular Stress Responses in Aging-Associated Diseases (CECAD) and the Cologne Excellence Cluster for Cellular Mechanisms in Cancer (CMMC). His research focuses on systems-level analysis of aging processes in humans and model organisms, integrating genomic, proteomic, and computational approaches. Key interests include understanding how genetic variation influences protein networks, developing algorithms for big data analysis, and exploring epigenetic mechanisms related to longevity. Research projects include studying age-associated changes in transcriptional elongation, molecular networks in kidney disease, and the impact of dietary restriction on aging. His group develops tools for proteomics and systems biology, such as methods for analyzing limited proteolysis data and single-cell resolution imaging. Collaborative efforts emphasize translational research in aging-related diseases and drug discovery. Prof. Beyer’s work spans computational biology, molecular genetics, and translational medicine. Notable contributions include identifying epigenetic changes linked to longevity and developing predictive models for age-related disease progression. His lab’s projects often involve multi-omics integration and network-based analyses to uncover disease mechanisms. His research has implications for personalized medicine, cancer biology, and interventions to extend healthspan. Current efforts include optimizing drug combinations targeting aging processes and advancing proteomic technologies for clinical applications.

Changsheng Wuمشاهده پروفایل

استاد

• Wireless Bioelectronics
• Energy Harvesting
• Advanced Manufacturing
• +۴ مورد دیگر

Dr. Changsheng Wu is a Professor at the National University of Singapore (NUS), leading the Lab for Intelligent Sensing, Harvesting and Actuation (LISHA). He holds a Bachelor's from NUS and a PhD from Georgia Tech, with postdoctoral research at Northwestern University. His work focuses on wireless wearables, bioelectronics, energy harvesting, and advanced manufacturing for sustainable solutions. Education: Bachelor in Engineering Science (First Class Honours), NUS PhD in Materials Science and Engineering, Georgia Institute of Technology Postdoctoral Research, Querrey Simpson Institute for Bioelectronics, Northwestern University Research Interests: Wireless bioelectronics for clinical health monitoring Energy harvesting via nanogenerators Soft skin-electronics interfaces using metastructures Programmable materials for adaptive systems Advanced manufacturing techniques for wearable devices Key Achievements: Over 50 publications and 5 patents Recipient of TechConnect 2018 Innovation Award and 56th R&D 100 Award Developed wireless implantable sensors for tissue monitoring and bioresorbable medical devices Teaching: MLE5220: Finite Element Method in Materials MLE5238: Bioelectronics Laboratory: His LISHA lab pioneers innovations in self-powered systems, wearable health monitoring, and biohybrid robots. Current projects include metamaterial-based sensors and sustainable energy conversion materials.

Pedro R. M. Inácioمشاهده پروفایل

دانشیار

• Cybersecurity
• Information Security
• Computer Simulation
• +۷ مورد دیگر

Pedro R. M. Inácio is an Associate Professor at the University of Beira Interior (UBI) , where he teaches information assurance, cybersecurity, and computer simulation courses in undergraduate and graduate programs. He serves as Pro-Rector for the Digital University and Data Protection Officer at UBI, and leads the Cross Cutting Skills Lab and the Network Security research group at Instituto de Telecomunicações. His work bridges academia and industry, including a PhD at Nokia Siemens Networks Portugal.

FENG Menglingمشاهده پروفایل

دانشیار

• Biostatistics
• Healthcare Data Analytics
• Medical AI
• +۳ مورد دیگر

**FENG Mengling** is an Associate Professor at the National University of Singapore (NUS) and holds primary affiliation with the Saw Swee Hock School of Public Health. She serves as the Domain Leader for the Biostatistics, Modelling, AI and Data Analytics (B.MAD) Domain and Director of the AI for Public Health (AI4PH) Program. Her academic credentials include a Senior Post-doc from Harvard-MIT Health Science Technology Division, a PhD from Nanyang Technological University (2009), and a Bachelor's degree (2003) from NTU. Research & Teaching: Her research focuses on causal inference for evidence-based medicine, generative models for medical time-series analysis, and healthcare data analytics. She teaches courses on big data technologies for healthcare problems and healthcare data analytics. Professional Roles & Awards: She has led the Biomedical and Healthcare Analytics Lab at the Institute for Infocomm Research (2014–2015) and currently serves as an Affiliate Scientist at Harvard-MIT. Notable accolades include the MIT Teaching & Learning Laboratory Kaufman Teaching Certificate and recognition as a finalist in MIT’s 2013 Innovation Showcase. Her work has been featured in prominent media outlets like The Straits Times and Channel NewsAsia, highlighting breakthroughs such as AI nurses and Singlish-speaking healthcare assistants. Publications & Impact: Over 50 peer-reviewed publications span AI-driven clinical decision support, medical imaging analysis, and predictive modeling in critical care. Key contributions include frameworks like MedDreamer (reinforcement learning for EHR analysis) and DivScore (LLM-generated text detection). Her research bridges causal inference, generative AI, and scalable healthcare solutions. Labs & Initiatives: As a leader in NUS’s Public Health AI Innovation Center (launching early 2025), she drives initiatives like FxMammo (AI for breast cancer screening) and the Biomedical and Healthcare Analytics Lab. Her work emphasizes ethical AI deployment and cross-disciplinary collaboration in healthcare.

• Medical Image Computing
• Tumor Growth Modeling
• Computational Physiology
• +۳ مورد دیگر

Bjoern Menze is a Professor and Rudolf Mößbauer Tenure Track Chair at the Technical University of Munich (TUM), leading the Image-based Biomedical Modeling Group within the Munich School of Bioengineering. His research focuses on medical image computing, tumor growth modeling, and computational physiology, with applications in clinical neuroimaging and personalized radiotherapy design. He holds a Ph.D. in Computer Science from Heidelberg University and has held positions at ETH Zurich, INRIA Sophia Antipolis, MIT, and Harvard Medical School. His academic journey includes a postdoc at MIT’s CSAIL and Harvard Medical School, followed by roles at ETH Zurich and INRIA. His work bridges biomedical imaging with machine learning, emphasizing model-driven analysis of physiological processes. He has been a visiting professor at Maastricht University and contributes to initiatives like the Center for Translational Cancer Research at TUM. Key research areas include tumor growth modeling, quantitative imaging biomarkers, and integrating mathematical models with clinical data. His awards include the MICCAI Young Scientist Award (2014), Leopoldina Fellowship (2009), and DFG Research Fellowship (2008). He advises on medical AI, leads interdisciplinary projects, and publishes extensively in top journals like Nature Neuroscience and IEEE Transactions on Medical Imaging. His lab’s work spans applications such as glioblastoma radiotherapy optimization, whole-body bone lesion detection, and neural connectivity imaging. Collaborations include institutions like Harvard, MIT, and ETH Zurich. He emphasizes translating computational methods into clinical practice for personalized healthcare solutions.

Vitor Sencadasمشاهده پروفایل

دانشیار

• Materials Science
• Biomedical Engineering
• Nanotechnology
• +۳ مورد دیگر

Vitor Sencadas is an Associate Professor at the Department of Materials and Ceramic Engineering, University of Aveiro, Portugal. His research focuses on advanced materials for biomedical, energy, and environmental applications, with a strong emphasis on nanotechnology and additive manufacturing. He leads projects such as 3S4Leather, addressing leather waste valorization and sensorized additive manufacturing solutions. He has supervised multiple PhD students and contributed to over 150 publications in journals like Advanced Functional Materials and ACS Applied Materials & Interfaces. His research interests include biomimetic materials, flexible electronics, wearable sensors, and sustainable materials. Notable achievements include developing piezoelectric and luminescent solar concentrators, and contributions to Stanford’s 2022/2024 World Top 2% Scientists list. His work bridges materials science with practical applications in healthcare, energy harvesting, and environmental biorefinery processes. He collaborates extensively with CICECO – Aveiro Institute of Materials, contributing to interdisciplinary research and innovation in smart materials and biomedical devices. His group explores multifunctional materials for healthcare monitoring, energy systems, and sustainable manufacturing.

Eileen Martinمشاهده پروفایل

دانشیار

• Near-surface geophysics
• Environmental monitoring
• Fiber-optic sensing (DAS/DTS)
• +۵ مورد دیگر

Eileen Martin is an Associate Professor in the Department of Geophysics and Applied Math and Statistics at the Colorado School of Mines. Her research focuses on near-surface geophysics, environmental monitoring, and the application of distributed acoustic sensing (DAS) technology. She leads projects involving fiber-optic sensing for permafrost degradation, urban seismic monitoring, and mining safety. Martin has developed open-source tools like DASCore and contributes to scalable computational methods for geophysical data analysis. Education: PhD (2018) in Computational and Mathematical Engineering from Stanford University; MS (2017) in Geophysics from Stanford; BS (2012) in Mathematics and Physics from UT Austin. Research interests include fiber-optic sensing systems, seismic imaging, data-intensive computing, and applications in environmental science. Her work bridges geophysics with computational methods, emphasizing real-world deployment in challenging environments like arctic permafrost sites and underground mines. Her recent work explores DAS for glacier monitoring, mine seismicity detection, and urban infrastructure assessment. Collaborative projects include Arctic permafrost monitoring and developing public datasets for geoscience research (PubDAS repository). Grants and lab activities include NSF CAREER funding for scalable computational seismology and partnerships with industry on fiber-optic monitoring solutions.

Peter Suttonمشاهده پروفایل

دانشیار

• Engineering Education
• Embedded Computing Systems
• Reconfigurable Computing
• +۳ مورد دیگر

Associate Professor Peter Sutton is an academic at the University of Queensland (UQ), holding roles as Deputy Head of School (Teaching and Learning) and Associate Professor in the School of Electrical Engineering and Computer Science. His research focuses on Engineering Education, Embedded Systems, Reconfigurable Computing, and Electronic Design Automation. He has contributed to curriculum design, remote lab management during the pandemic, and hardware-software co-design for embedded systems. Sutton completed his undergraduate studies at UQ and earned advanced degrees at Carnegie Mellon University, with over three decades of experience in computer systems research and education. Education Bachelor of Science, University of Queensland Bachelor (Honours) of Engineering, University of Queensland Masters of Science (Coursework), Carnegie Mellon University Doctor of Philosophy, Carnegie Mellon University Research Interests Sutton’s work spans engineering pedagogy, embedded system design, and reconfigurable computing. Recent projects include adapting hands-on labs for remote learning during the pandemic and optimizing FPGA-based architectures for data compression and encryption. His contributions to cache optimization and multiprocessor systems highlight his expertise in hardware-software integration. Publications His 50+ publications cover topics like FPGA implementations of neural networks, code compression techniques for VLIW processors, and embedded system design tools. Notable contributions include frameworks for reconfigurable system-on-chip development and methods to enhance debugging practices in post-novice students. Labs & Teams He collaborates within UQ’s School of Electrical Engineering and Computer Science, contributing to research groups focused on embedded systems and engineering education innovation.

• Antennas
• Applied Electromagnetics
• Computational Electromagnetics
• +۲ مورد دیگر

Giuseppe Vecchi is a Full Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino , Italy. He leads the Applied Electromagnetics research group and contributes to projects in computational electromagnetics, metamaterials, and biomedical applications of electromagnetic fields. He has been a IEEE Fellow since 2010 and serves on PhD college committees for Electrical, Electronic, and Communications Engineering. Research Interests : Antennas, Applied and Computational Electromagnetics, Metamaterials, Microwave Imaging for medical applications, Nuclear Fusion Reactor Physics. Scientific Leadership : Principal Investigator for projects like METEOR, MTSA, and RESOLVED-K, focusing on terahertz generation, metasurface antennas, and real-time temperature mapping in hyperthermia. Awards : IEEE Fellow (2010), recognizing his contributions to electromagnetic simulations and antenna design. Students : Supervises PhD candidates in advanced antenna engineering, computational electromagnetics, and biomedical applications, including Owais Khan, Francesco Lattanzio, and Sara Paknezhad Panahi. Patents : Holds multiple patents in antenna diagnostics, encrypted metasurface antennas, and microwave soil disinfection systems.

Frederik J. Simonsمشاهده پروفایل

استاد

• Geophysics
• Seismology
• Geodesy
• +۳ مورد دیگر

Frederik J. Simons is a Professor of Geosciences and Associate Chair of the Department of Geosciences at Princeton University. He holds affiliations with the Program in Applied & Computational Mathematics, High Meadows Environmental Institute, and Andlinger Center for Energy and the Environment. His research focuses on global geophysics, seismology, and geodesy, emphasizing the lithosphere's physical properties through seismic tomography and spectral analysis. Simons developed methods for oceanic instrumentation, including the EarthScope-Oceans consortium, and pioneered wavelet-based signal processing for seismology. His work integrates computational inverse methods and statistical techniques, with a commitment to reproducible research. Education: PhD in Geophysics (MIT), M.Sc. in Geology (KU Leuven, Belgium). Previous roles include Lecturer at University College London and Hess Postdoctoral Fellow at Princeton. Research interests span seismic tomography, lithospheric mechanics, and planetary science, with notable contributions to mantle structure imaging and earthquake early warning systems. Awards include the Vladimir Keilis-Borok Medal (2022). Simons advises graduate students and mentors researchers in computational geoscience. His teaching emphasizes clarity and engagement, blending theoretical foundations with hands-on applications.

Dierck Hillmannمشاهده پروفایل

دانشیار

• Optical Coherence Tomography
• Biophotonics
• Medical Imaging
• +۳ مورد دیگر

Dr. Dierck Hillmann is an Associate Professor at the Faculty of Science, Department of Biophotonics and Medical Imaging, Vrije Universiteit Amsterdam. He holds a PhD in Holoscopy from Luebeck University (2013). His research focuses on advanced optical imaging techniques, particularly Optical Coherence Tomography (OCT), with applications in retinal imaging, functional signal analysis, and computational imaging. He is affiliated with the LaserLaB - Biophotonics and Microscopy research group. Key research areas include improving OCT resolution through holographic methods, functional imaging of retinal neurons and photoreceptors, and developing computational adaptive optics to enhance imaging quality. His work addresses challenges like speckle reduction, aberration correction, and real-time data processing in biomedical imaging. Dr. Hillmann’s contributions span over 37 publications, including innovations in full-field OCT, optoretinography, and phase-sensitive measurements. He teaches courses such as Computational Optical Imaging and Light-Tissue Interaction. His current project explores imaging individual retinal cells and their functions using advanced techniques. No scientific awards are explicitly listed, but his extensive publication record reflects significant academic impact. Students advised are not specified in the provided materials.