جست‌وجوی استاد و پژوهشگر

Baranov Pavel Fedorovichمشاهده پروفایل

دانشیار

• Non-Destructive Testing
• Metrology
• Electrical Measurement
• +۳ مورد دیگر

Baranov Pavel Fedorovich is an Associate Professor and current Director of the Engineering School of Non-Destructive Testing and Safety at Tomsk Polytechnic University, holding a Candidate of Technical Sciences degree and affiliated with the Department of Electronic Engineering. His educational background includes: 2004: Entered Tomsk Polytechnic University's Faculty of Electrophysics in the "Metrology, standardization and certification" program 2010: Master's degree completion 2010-2013: Postgraduate studies 2013: PhD defense in specialty "05.11.01 - Instruments and methods of measurement (measurement of electrical and magnetic quantities)" Dr. Baranov's research centers on precision measurement technologies with emphasis on electrical and magnetic phenomena. His work involves developing specialized instrumentation to overcome measurement challenges in high-interference environments, including: Synchronous amplifier design with differential inputs for detecting minute physical deviations amid strong common-mode noise Advanced fluxgate magnetometer development and analysis Complex waveform synthesis for specialized measurement scenarios His expertise spans non-destructive testing methodologies, metrology fundamentals, and signal processing techniques for industrial applications. No scientific awards were documented in the source material. Academic advising activities and research grant information were not specified in the available records. His teaching responsibilities include the course "Measuring technologies of the Internet of Things". As Director of the Engineering School of Non-Destructive Testing and Safety, he leads institutional efforts in developing non-destructive evaluation standards, safety protocols, and measurement education programs, overseeing faculty and research initiatives within this specialized engineering domain.

• Computational Photonics
• Quantum Cascade Devices
• Microwave Engineering
• +۳ مورد دیگر

Michael Haider is an Associate Professor at the Technical University of Munich within the TUM School of Computation, Information and Technology , specifically affiliated with the Chair of Computational Photonics (Prof. Christian Jirauschek). His work bridges quantum device modeling, stochastic electromagnetic field analysis, and advanced optoelectronic simulations. Research interests include: Quantum Cascade Lasers and Detectors Josephson Traveling-Wave Parametric Amplifiers Stochastic and Cyclostationary Electromagnetic Field Propagation Terahertz Technology and Frequency Comb Generation Computational Photonics and Microwave Modeling Principal Component Analysis for Electromagnetic Systems His recent publications focus on quantum amplification mechanisms, THz laser dynamics, and stochastic field modeling using Maxwell-Bloch frameworks. Collaborations with Prof. Jirauschek, Prof. Russer, and researchers at ETH Zürich and SPIE conferences highlight his interdisciplinary approach.

• Radiation Detection
• Semiconductor Detectors
• ASIC Design
• +۴ مورد دیگر

Piotr Maj is Professor at the Department of Metrology and Electronics within the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering at AGH University of Science and Technology in Kraków. His research focuses on semiconductor radiation detectors and readout electronics for nuclear physics, medical imaging, and space applications. His primary research areas include Radiation Detection using CZT and TlBr semiconductors, ASIC Design for photon counting systems, and Position-Sensitive Detector development. Key specialties encompass virtual Frisch-grid technology, event-driven readout architectures, and integration of machine learning for real-time signal processing in high-energy physics environments. His work frequently involves synchrotron radiation facilities and space instrumentation projects. Analysis of his 2023-2025 publications reveals dominant trends in radiation-hard ASIC development for space missions (e.g., HEXID, EDWARD architectures), 3D position-sensitive detector characterization (CdZnTe/TlBr arrays), and machine learning integration for in-pixel intelligence. His detector systems target applications in gamma-ray astronomy, nuclear security, and biomedical imaging, with emphasis on high-speed, low-noise performance under extreme conditions.

Miles Bergerمشاهده پروفایل

دانشیار مدعو

• Postoperative Neurocognitive Disorders
• Delirium
• Alzheimer's Disease and Related Dementias (ADRD)
• +۵ مورد دیگر

Miles Berger is an Adjunct Associate Professor in the Department of Anesthesiology at Duke University School of Medicine. He is also a Faculty Network Member of the Duke Institute for Brain Sciences and an Associate of the Duke Initiative for Science & Society. Dr. Berger received his Ph.D. and M.D. from the University of California, San Francisco in 2007 and 2009 respectively, followed by an Internship and Residency in Anesthesiology at Duke University School of Medicine from 2009 to 2013. Dr. Berger's research focuses on three main areas: 1) the mechanisms of postoperative neurocognitive disorders such as delirium and their relationship to Alzheimer's Disease and Related Dementias (ADRD); 2) the potential of altered anesthetic-induced brain EEG waveforms as indicators of preclinical neurodegenerative disease pathology; and 3) how the APOE4 allele damages brain circuitry throughout the adult lifespan and contributes to increased risk of late onset Alzheimer's disease. His work employs a transdisciplinary approach, combining methods such as CSF and blood sampling, functional neuroimaging, EEG recordings, rigorous biochemical assays, and cognitive testing and delirium screening. Analysis of Dr. Berger's recent publications reveals a strong focus on the intersection of anesthesia, neurocognitive outcomes, and neurodegenerative processes in older adults. His work increasingly emphasizes EEG-based biomarkers for predicting and understanding postoperative delirium, the role of APOE4 in neuroinflammation, and the relationship between surgical procedures and long-term cognitive outcomes. Many studies incorporate advanced techniques like proteomics, neuroimaging, and machine learning approaches to analyze complex datasets. Dr. Berger currently leads multiple significant research grants including "Brain Vulnerability in Delirium and Alzheimer's Disease and Related Dementias: Intersection of Polygenic Risk and Inflammation" (2023-2027) and "A Phase II Study of an ApoE mimetic peptide to reduce Postoperative Delirium, Cognitive Dysfunction after Non-Cardiac Surgery in Older Adults" (2018-2024). His research team includes individuals with diverse scientific and clinical backgrounds, ranging from neuropsychology and neuroimaging to proteomics, flow cytometry and behavioral neuroscience in animal models, all working to better understand mechanisms of age-dependent brain dysfunction.

• High Voltage Engineering
• Electrical Insulation Systems
• Partial Discharge Measurement
• +۳ مورد دیگر

Jörgen Blennow is an Associate Professor in High Voltage Engineering at Chalmers University of Technology, Sweden, where he also serves as Vice-Rector for Education. His research focuses on electrical insulation systems , partial discharge measurement , and dielectric response analysis under high-voltage conditions. Key Research Areas: High Voltage Engineering Electrical Insulation Systems Partial Discharge Detection Dielectric Response in Oil-Impregnated Paper Electrical Treeing in Polyethylene Current Damage in Wind Turbine Bearings Notable Projects: Integrerat lärande - Expert Learning Lab (2023–2025, VINNOVA) Karakterisering av åldring i isolationssystem (2014–2016, Trafikverket) Lagerströmaktivitet (2011–2016, Swedish Wind Power Centre) His work has been published in journals such as IEEE Transactions on Dielectrics and Electrical Insulation and Conference on Electrical Insulation and Dielectric Phenomena . Current research includes applications in renewable energy systems and power electronics . As Vice-Rector, he plays a pivotal role in shaping educational strategies at Chalmers. His method of monitoring losses and diagnostic techniques for transformers and wind turbine systems have advanced condition monitoring and smart grid technologies .

John Verboncoeurمشاهده پروفایل

استاد

• Plasma Physics
• Radio Frequency Engineering
• Computational Modeling
• +۴ مورد دیگر

John Verboncoeur is a Professor in the Department of Computational Mathematics, Science and Engineering at Michigan State University . His research spans plasma physics , radio frequency discharge modeling , and computational simulation methods , with a focus on: Multipactor breakdown mechanisms Electromagnetic and space charge effects Particle-in-cell (PIC) and PIC-MCC simulations Similarity and scaling laws for plasma systems Machine learning for RF device optimization Terahertz modulator design Recent publications highlight trends in: Non-sinusoidal RF field interactions Dielectric surface dynamics Microscale and high-pressure plasma discharges Algorithm development for self-consistent modeling Harmonic generation in plasma breakdown No further details on education, awards, students, or laboratory affiliations were extracted from available texts.

• Astrophysics
• Gravitational Waves
• Binary Evolution
• +۳ مورد دیگر

Dr. Marc van der Sluys van der Sluijs is a researcher at Utrecht University's Department of Gravitational and Subatomic Physics (GRASP) and the Dutch National Institute for Nuclear and High Energy Physics (Nikhef) in Amsterdam. His academic focus spans gravitational-wave detection, binary evolution, and computational astrophysics, with active roles in the Virgo, LIGO, and Einstein Telescope collaborations. Research Interests: His work centers on gravitational-wave data analysis, neutron star and black hole coalescences, common-envelope evolution, and multi-messenger astronomy. He employs heavy computing and Bayesian statistics for empirical modeling of astrophysical phenomena. Teaching: He teaches Introduction to Astrophysics and Stellar Evolution in Utrecht University's physics bachelor program. Publications: His recent articles (2019–2025) predominantly explore gravitational-wave detection methodologies, dark matter searches, and solar position algorithms. Key themes include machine learning applications in astrophysics, multi-instrument data analysis, and open-source software development for scientific computation. Ancillary Activities: He founded hemel.waarnemen.com , a popular Dutch astronomy website with 1–2 million annual visits, providing observational guides for celestial phenomena in Belgium and the Netherlands.

Hideya Koizumiمشاهده پروفایل

دانشیار

• Quantum Chemistry
• Statistical Mechanics
• Biomolecular Modeling
• +۳ مورد دیگر

Hideya Koizumi is an Associate Professor of Chemistry at Arkansas State University within the Beck College of Sciences & Mathematics. He holds a Ph.D. in Chemistry from the University of Utah and a B.S. in Chemistry from Oklahoma State University. Research spans quantum mechanical modeling, ion trapping simulations, and biomolecular interactions Teaches physical chemistry and general chemistry Focuses on computational methods and statistical mechanics in chemical systems His computational research applies quantum mechanics and statistical methods to study molecular properties and biomolecules, with recent work on intramolecular interactions in proteins and ion trapping dynamics. His publications highlight expertise in mass spectrometry, ion mobility, and computational chemistry. Though no awards are listed, his work bridges theoretical modeling with experimental validation in molecular systems.

Tamulevičius Gintautasمشاهده پروفایل

دانشیار

• Speech Signal Processing
• Machine Learning
• Acoustic Analysis
• +۳ مورد دیگر

Assoc. Prof. Dr. Gintautas Tamulevičius serves as Director of the Institute of Data Science and Digital Technologies at Vilnius University. His primary affiliation is with the Image and Signal Analysis Group, where he contributes as a Senior Researcher and Chief Researcher in projects. Doctor of Science in Technology (2008) Pedagogical Title: Associate Professor (2014, Vilnius Gediminas Technical University) Active in IEEE Computer Society and Signal Processing Society Dr. Tamulevičius specializes in speech signal processing, with research spanning three core domains: Speech Modeling : Autoregressive/linear prediction, nonlinear fractal modeling, non-parametric approaches Recognition Systems : Deep learning-based methods, Hidden Markov models, Wave-U-Net architectures Quality Assessment : Voice phonation evaluation, vocal fold condition analysis using acoustic methods His publication trends show strong focus on: Deep learning applications for speech processing 2D feature space analysis for recognition tasks Fractal dimension-based emotion classification Language preservation through technological development Human-centered AI applications Biomedical signal processing As an educator, he has taught: Digital Signal Processing (VGTU 2012–present) Speech Signal Processing (VGTU 2008–present) Data Visualization (VGTU 2015) User Interface Design (VU 2018–present) Audio Signal Processing (VU 2020–present) His editorial contributions include reviewing for: Informatica IEEE Access Neurocomputing Baltic Journal of Modern Computing Nonlinear Analysis: Modeling and Control IEEE Journal of Biomedical and Health Informatics International Journal of Applied Mathematics and Computer Sciences He has supervised doctoral research including: Daniel Zakševski (2023–2027): Deep learning models for speech enhancement Monika Danilovaitė (2020–2026): Voice quality assessment methods Tatjana Liogienė (2012–2016): Multistage speech emotion classification

Uros Pucمشاهده پروفایل

پژوهشگر

• Terahertz Technology
• Organic Electronics
• Nonlinear Optics
• +۴ مورد دیگر

Dr. Uros Puc is a researcher at the ZHAW Zurich University of Applied Sciences , affiliated with the School of Engineering . His work focuses on terahertz (THz) photonics , organic electronics , and photovoltaics , particularly in developing and characterizing organic crystals for THz wave generation and sensing applications. Research Interests : Puc's research spans terahertz technology , nonlinear optics , and molecular phonon engineering , with applications in materials testing, biomedical sensing, and sustainable technologies. He investigates how substituent groups and crystal structures influence THz phonon vibrations and nonlinear optical properties, aiming to enhance THz emission efficiency and stability. Publications highlight his contributions to broadband THz spectroscopy , organic crystal design , and analytical gas sensing . His work also extends to terahertz applications in circular economy and construction materials characterization .

David Caratelliمشاهده پروفایل

استادیار

• Neutrino Physics
• Particle Astrophysics
• Liquid Argon Time Projection Chamber (LArTPC) Technology
• +۳ مورد دیگر

David Caratelli is an Assistant Professor in the Department of Physics at University of California Santa Barbara. His research focuses on experimental particle physics through neutrino studies to understand fundamental laws of nature and universe evolution. Member of MicroBooNE collaboration (Fermilab Short Baseline Neutrino program) Participant in Deep Underground Neutrino Experiment (DUNE) Office: Broida Hall 5119 Contact: (805) 893-7567 | dcaratelli@ucsb.edu Key research areas include: Neutrino Oscillations and New Physics Searches LArTPC Calibration and Reconstruction Sub-MeV Energy Regime Expansion Coherent Elastic Neutrino-Nucleus Scattering (CEvNS) Dark Matter Detection Techniques Electron Amplification in Liquid Argon Recent publications examine: Sterile neutrino constraints (2023) Electron neutrino excess searches (2022) Pion decay reconstruction (2020) Supernova neutrino detection methods (2021) Comprehensive detector design (2017) Technical contributions include: CRT Veto implementation Waveform visualization tools Software dependency frameworks Argon-39 background analysis

• Signal Processing
• Radar Systems
• Sonar Applications
• +۴ مورد دیگر

John F. Doherty is a Professor in Electrical Engineering, specializing in signal processing and radar systems. His research spans interdisciplinary applications including sonar tracking, steganography, and speech recognition. Key research areas: Data assimilation, spread spectrum, and empirical mode decomposition Collaborations: National Science Foundation-funded projects with J.D. Mathews at Arecibo Observatory Research Interests: Professor Doherty's work focuses on real-time multi-mode data assimilation for geophysical radar systems, interference suppression in signal processing, and covert waveform design for sonar applications. His recent studies explore entropy-based speech quality metrics and compressed speech analysis for speaker recognition systems. Grants & Projects: Lead NSF-funded projects on Arecibo radar systems (2001-2009), developing efficient data assimilation techniques. Collaborated on multi-mode radar systems and sonar steganography. Publications: Over 88 research outputs with 1075 citations. Recent works include nulling algorithms for radar ambiguity functions and covert communication techniques in sonar systems.

• Radar Systems
• Ultra-wideband Engineering
• Frequency Diverse Arrays
• +۳ مورد دیگر

Ram Mohan Narayanan is a Professor in Electrical Engineering, actively contributing to radar systems, ultra-wideband technologies, and microwave engineering. His work spans theoretical and applied research, with a focus on frequency diverse arrays, coherent distributed arrays, and non-destructive testing using noise-based microwave systems. His research interests include Radar systems and waveform diversity Ultra-wideband signal processing Antenna design and optimization Applications in structural diagnostics and materials characterization Recent publications highlight advancements in gradient-based optimization of coherent distributed arrays and the integration of natural language processing in radar systems. He also explores frequency diverse arrays using Sudoku square designs for improved spectral efficiency. Grants from the U.S. Navy support his work on spectral coexistence, cognitive MIMO apertures, and detection of IEDs using ultrawideband waveforms.

Mesut Sahinمشاهده پروفایل

استاد

• Neuromodulation
• Neural Engineering
• Spinal Cord Injury Research
• +۳ مورد دیگر

Mesut Sahin is a Professor in the Department of Biomedical Engineering at the College of Engineering, New Jersey Institute of Technology (NJIT). His academic journey includes a Ph.D. in Biomedical Engineering from Case Western Reserve University (1998) and a B.S. in Electrical Engineering from Istanbul Technical University (1986). Currently, he focuses on neuromodulation of the cerebellum using transcranial AC Stimulation (tACS) and Focused Ultrasound (FUS), while developing floating microstimulators for spinal cord applications (FLAMES). His research spans neural circuits, brain injury recovery, and biomedical signal processing. Education: Ph.D., Biomedical Engineering, Case Western Reserve University (1998) M.S., Biomedical Engineering, Case Western Reserve University (1993) B.S., Electrical Engineering, Istanbul Technical University (1986) Research Interests: Mesut Sahin's work centers on neuromodulation techniques, including transcranial AC Stimulation (tACS) and Focused Ultrasound (FUS), to study cerebellar dynamics and recovery from neural injuries. He has pioneered the development of floating microstimulators for spinal cord applications (FLAMES), enabling wireless neural stimulation. His research also investigates the electrophysiological correlates of brain injuries, neural signal processing methods, and the design of biocompatible devices for chronic implantation. Key themes include neural circuit plasticity, motor control recovery, and the application of advanced technologies like carbon fiber electrodes and PDMS optical waveguides. Scientific Awards: Mesut Sahin is recognized as a Senior Member of the IEEE/EMBS since 2006, highlighting his contributions to biomedical engineering. His work spans over 100 peer-reviewed publications, three patents, and a textbook on bioinstrumentation. Mentoring: He has mentored 17 Ph.D. and 23 Master’s theses, emphasizing student training in neural engineering and biomedical device development.

Ioannis Konstantinidisمشاهده پروفایل

مدرس

• Data Science
• Signal Processing
• Machine Learning
• +۵ مورد دیگر

Ioannis Konstantinidis is a Lecturer at the University of Houston's Honors College and a Senior Researcher in the Department of Computer Science. He holds a PhD in Mathematics from the University of Maryland and integrates his academic background into his work on data science, focusing on the practical impact of research within policy decision-making frameworks. As part of the Honors College Faculty and the Hewlett Packard Enterprise Data Science Institute, he emphasizes data-centric approaches and mentors students in engaged citizenship. Doctorate in Mathematics, University of Maryland His research spans diverse domains, including signal processing , public health , and STEM education . He has contributed to waveform design for radar systems, data visualization tools for humanities, and educational strategies for planetary science. His work in the Data & Society minor promotes structured methodologies for student researchers. Recent publications highlight his interdisciplinary focus, from 2024 research on multimorbidity in intellectual disability to earlier contributions in digital content management and confocal microscopy denoising . His technical work on CAZAC sequences and phase-coded waveforms has advanced signal processing theory.