جست‌وجوی استاد و پژوهشگر

• Neuroscience
• Cognitive Science
• Psychology
• +۴ مورد دیگر

Juliane Britz is a Lecturer at the Department of Psychology, Faculty of Letters and Human Sciences, University of Fribourg. Her research focuses on the interplay between brain and body in conscious awareness, particularly through EEG microstate analysis and multimodal investigations of interoceptive signals. Current project: BBC - Brain, Body and Consciousness (2019-2025) examining how bodily rhythms (heartbeat/respiration) interact with brain activity in perceptual awareness. Key methodologies: Simultaneous EEG-ECG-respiration recording, source reconstruction, network dynamics modeling. Research Focus Her work bridges cognitive neuroscience and physiological psychology, exploring: Temporal organization of EEG microstates in health and neurological disorders Brain-body interactions in sensory threshold perception Embodied semantics in language processing Neural dynamics during propofol-induced unconsciousness Publication Trends Recent articles reveal a trajectory from basic neural dynamics (2008-2011) to translational applications in schizophrenia vulnerability markers (2014) and anesthesia research (2022), culminating in current investigations of interoceptive influences on consciousness (2024). Contact Email: juliane.britz@unifr.ch Office: RM 01 bu. C-4.110, University of Fribourg

Svein Ketil Jacobsenمشاهده پروفایل

استاد

• Ultrasound Technology
• Microwave Radiometry
• Optics
• +۵ مورد دیگر

Svein Ketil Jacobsen is a Professor at the Department of Physics and Technology, UiT The Arctic University of Norway in Tromsø. He specializes in applied physics with a focus on Ultrasound, Microwaves, and Optics. His research bridges medical technology and environmental sensing, with affiliations to the university's research group on these topics. Research interests include: Remote sensing technology : Drone-mounted radar systems for snowpack analysis and avalanche research Biomedical instrumentation : Microwave radiometry for non-invasive diagnostics and hyperthermia treatment Ultrasonic systems : High-frequency transducer design and signal processing techniques Antenna design : Optimized microwave antennas for medical and environmental applications His publication trends show a shift from foundational biomedical microwave work (2001-2012) toward drone-based environmental sensing in recent years (2016-2021). Earlier research focused on medical thermometry, bladder diagnostics, and ultrasonic systems, while recent innovations involve UWB radar for snow hydrology and Arctic monitoring. Professor Jacobsen maintains active laboratory facilities at the Technology Building in Tromsø (Room 2.054), conducting experimental work in microwave and ultrasonic technologies.

• Entrepreneurship
• SMEs
• Social Networks
• +۷ مورد دیگر

Mette Søgaard Nielsen is an Associate Professor at the Department of Business and Sustainability , University of Southern Denmark , specializing in Entrepreneurship with a focus on social networks, emotional support, and mental well-being in entrepreneurial contexts. She has held academic positions since 2019 and previously served as Assistant Professor (2015-2018) and PhD student (2010-2014). PhD in Entrepreneurship (2014), M.Sc. in Business (2009), and B.Sc. in Business (2006) from University of Southern Denmark. Research intersects Entrepreneurial Behavior , Social Support , and Emotional Intelligence , with key insights into how network dynamics and emotions affect venture performance. Her scientific awards include the 2019 Syddansk Universitets Undervisningspris and Det Samfundsvidenskabelige Fakultets Undervisningspris . Recent publications address stereotype threat in women’s opportunity evaluation, emotional support during crises, and social skill impacts on resource acquisition.

• Robotics
• Tactile Sensing
• Soft Robotics
• +۳ مورد دیگر

Tito Pradhono serves as an Assistant Professor and Junior Researcher at the Future Robotics Organization under the Research Council, specializing in advanced robotics research with 34 publications and significant scholarly impact (884 Google Scholar citations, h-index 12). His work bridges hardware innovation and algorithmic development to solve critical challenges in robotic perception and interaction. His primary research focuses on tactile sensing systems and soft robotics, where he has pioneered novel sensor technologies including Halbach array-based robot skin (H-PME), interchangeable fingertip sensors (Fingertac), and low-cost proximity-force fusion systems ("Safe Skin"). These innovations enable enhanced human-robot interaction through precise force measurement, slip detection, and grasping stability prediction. His methodology consistently integrates machine learning—particularly spatio-temporal attention networks and ensemble learning—with physical sensor design to create practical, deployable solutions. Analysis of his 15 most recent publications reveals a clear trajectory toward multimodal perception systems (vision-touch fusion), geometric data augmentation techniques, and culturally contextual robotics (anime embodiment). His work demonstrates exceptional consistency in developing cost-effective, real-world applicable technologies while maintaining theoretical rigor in sensor fusion and deep learning architectures. He received the Integrated Doctoral Tuition Support Scholarship in 2015, which supported his foundational research. His scholarly impact is evidenced by sustained citation growth across Scopus (612 citations) and Google Scholar (884 citations) platforms. Dr. Pradhono's research is conducted within the Future Robotics Organization, which appears to focus on socially engaged robotics development including the darumato-3 social robot platform and culturally specific implementations like Wayang puppet theater robots with Gamelan music recognition. His work emphasizes participatory design and real-world deployment rather than purely theoretical exploration.

Agustí Egea-Àlvarezمشاهده پروفایل

استاد

• Power Electronics
• Grid-Forming Converters
• Virtual Synchronous Machines
• +۷ مورد دیگر

Dr Agustí Egea-Àlvarez is a Professor in the Department of Electronic & Electrical Engineering at the University of Strathclyde, where he is a key member of the PEDEC (Power Electronics, Drives and Energy Conversion) research group. He also holds an industry position as Network Operational Performance Manager at ScottishPower Energy Networks, reflecting his strong bridge between academic research and power system operations. BSc, MSc, PhD – Technical University of Catalonia, Barcelona (2008, 2010, 2014) Marie Curie Fellow – China Electric Power Research Institute (CEPRI), 2015 Converter Control Engineer – Siemens Gamesa, 2016 His research is centered on next-generation power converter technologies for renewable integration. Key interests include grid-forming and virtual synchronous machine (VSM) control algorithms, control of voltage source converters in weak and low-inertia grids, alternative HVDC connection schemes for offshore wind farms, and DC-DC converter control for HVDC systems. His work addresses critical challenges in modern power systems transitioning to high renewable penetration. The recent publications highlight a strong trend in analyzing and improving the stability and control of converter-dominated power systems. Topics such as inertia estimation, sub-synchronous oscillations, small-signal stability, and fault current control underpin his focus on ensuring grid reliability and resilience in low-inertia environments. His methodological approaches include wavelet analysis, modal contribution metrics, and comprehensive comparative reviews using structured decision-making frameworks like AHP. 'Sustainable Impact by Design' Team, Strathclyde Medal Recipient (2023) Best Paper, Wind Integration Workshop (2019) – awarded 2020 Teaching Excellence Award – Best in Faculty of Engineering (2019) Dr Egea-Àlvarez is actively involved in major research projects such as SETTLE-INSIGHT (NIA), Shell-iCase protection projects, and SIF BLADE-Beta, often as a Co-investigator or Principal Investigator. These projects are supported by EPSRC and industrial partners like ScottishPower and Shell, indicating strong grant acquisition and collaborative research leadership. He also supervises research students and contributes to academic service as a peer reviewer for journals like Energies and CSEE Journal of Power and Energy Systems , and as an invited speaker on grid-forming converter technologies. He is a member of the PEDEC research group, which is a leading center in power electronics and energy conversion at the University of Strathclyde, fostering interdisciplinary research and innovation in sustainable energy systems.

• Electromagnetic Compatibility
• Antenna Design
• Energy Systems
• +۴ مورد دیگر

Tom H.F. Hartman is an Assistant Professor specializing in Radio Systems with a focus on Electromagnetic Compatibility (EMC) . His research spans antenna design, EMI mitigation, and measurement engineering, often involving collaborations with institutions in the Netherlands and Germany. He has published extensively in high-impact journals and conferences, including IEEE Transactions on Electromagnetic Compatibility. Key Research Areas : Electromagnetic Interference, Measurement Engineering, Time Domain Analysis, Antenna Design, Energy Systems, Signal Processing His recent work includes breakthroughs in mutual coupling correction for shielded loop antennas and notch filter design for EMC applications. He has received prestigious awards like the 2021 IEEE EMC President Memorial Award and the 2022 IEEE Best Transaction Paper Award . Scientific Awards : 2021 IEEE EMC President Memorial Award 2022 IEEE Richard B. Shultz Best Transaction Paper Award Hartman has supervised multiple PhD and master's students on EMC-related topics, including Pokotilov D. , Vogt-Ardatjew R. , and Moonen N. . His work addresses both theoretical and practical challenges in electromagnetic compatibility, such as common-mode choke saturation and dynamic EMI filtering.

• Microelectronics
• Integrated Circuits
• Analog Circuit Design
• +۳ مورد دیگر

Shubin Liu is a researcher specializing in microelectronics, integrated circuits, and analog circuit design. His work focuses on advanced ADC architectures (e.g., pipelined SAR, time-interleaved, noise-shaping), phase-locked loops (PLL), and sensor readout systems for MEMS and biomedical applications. Recent publications highlight collaborations with Zhangming Zhu and colleagues on high-speed, low-power, and PVT-robust designs. Research interests span Analog-to-digital conversion Low-power RF front-ends Calibration techniques High-frequency oscillators Biopotential amplifiers Time-interleaved ADCs His 15 most recent articles (2023-2025) explore power-efficient ADCs, jitter reduction in PLLs, and sensor interfaces, with keywords including Electronics, Integrated Circuits, Signal Processing, and Microelectronics. Notable subfields: SAR ADCs, Time-Domain Interpolation, Capacitor Mismatch Compensation, and IoT-optimized designs. Shubin Liu’s work is published in journals like IEEE Journal of Solid-State Circuits , Microelectronics Journal , and conferences such as CICC and ISSCC, reflecting his active engagement in cutting-edge analog and mixed-signal research.

• Audiology
• Auditory Electrophysiology
• Audiologic Rehabilitation
• +۵ مورد دیگر

Samuel Atcherson, Ph.D., is a Professor at the University of Arkansas for Medical Sciences (UAMS) in both the College of Health Professions Department of Audiology and Speech Pathology and the College of Medicine Department of Otolaryngology—Head and Neck Surgery. His research spans audiologic rehabilitation, auditory electrophysiology, and health literacy, with a focus on addressing challenges faced by individuals with hearing loss, particularly in healthcare communication during mask use and accessibility for people with disabilities. Research Interests: Atcherson's work integrates audiologic rehabilitation through innovations like transparent face masks and amplified stethoscopes, auditory electrophysiology using evoked potential systems, and health literacy research examining readability of medical materials, especially for those with disabilities. Publications: With over 60 peer-reviewed articles, his recent publications explore AI integration in audiology, masked speech challenges, and health disparities. A recurring theme is the intersection of technology, accessibility, and multidisciplinary collaboration. Grants & Awards: He has secured over $477,000 in grants, including NIH funding, and holds the Distinguished Scholar Fellow title from the National Academies of Practice. Leadership: Atcherson serves on the Editorial Board of the Journal of the American Academy of Audiology and has contributed to textbooks like Auditory Electrophysiology: A Clinical Guide .

• Seismology
• Geophysics
• Seismic Event Discrimination
• +۳ مورد دیگر

Timo Tiira is a Researcher at the Institute of Seismology, University of Helsinki , and Supervisor for the Doctoral Programme in Geosciences. His work focuses on seismology and geophysics, particularly seismic event discrimination using Finnish station networks. PhD in Geophysics (Discrimination of seismic events using Finnish station network) MSc in Physics (Seismisten signaalien havaitseminen Hutt&Murdock-detektorin ja digitaalisen suodatuksen avulla) Research Interests: Seismology and geophysics with emphasis on seismic event discrimination, crustal structure analysis, ambient noise tomography, and seismic hazard assessment for critical infrastructure like nuclear power plants. Key Contributions: Leadership in establishing the Finnish Seismic Instrument Pool (FINNSIP) , development of 3D shear wave velocity models for Helsinki, and automated seismic event classification systems. Collaborative work spans Finland, Russia, and Ukraine with 103+ activities and 187+ research outputs. Scientific Awards: Recipient of Best GFF Articles award (2014) Projects: Active in SCARCE: Scandinavian Arctic Continental Experiment (2023–2028) and Monitoring the monitoring (2020–2025). Key roles in seismic networks for geothermal and nuclear facility monitoring.

Dan Maمشاهده پروفایل

دانشیار

• Magnetic Resonance Imaging (MRI)
• Magnetic Resonance Fingerprinting (MRF)
• Medical Imaging Physics
• +۳ مورد دیگر

Dan Ma is an Associate Professor of Neurosurgery and Biomedical Engineering at Duke University School of Medicine, with a focus on advancing quantitative Magnetic Resonance Imaging (MRI) technology. His research bridges MR physics, signal modeling, artificial intelligence, and clinical translation to improve disease diagnosis and treatment. Education: Ph.D., Case Western Reserve University School of Medicine (2015) His lab specializes in Magnetic Resonance Fingerprinting (MRF), a non-invasive technique for quantifying tissue properties, and develops multi-parametric MR methods for clinical applications in epilepsy, brain tumors, breast cancer, and prostate cancer. Recent work includes technical innovations in SyntheticMR implementation for radiation therapy and 3D MRF for dynamic contrast-enhanced imaging. Scientific Awards: Senior Member, National Academy of Inventors (2023) Junior Fellow, ISMRM (2017) I.I. Rabi Young Investigator Award, ISMRM (2016) Dan Ma is a core member of Duke's Center for Brain Imaging and Analysis. His research integrates AI into MRI post-processing and explores motion-robust scans for neonatal imaging. Publications highlight his contributions to pulse sequence design, relaxometry standardization, and cortical dysplasia characterization.

• Proteomics
• Mass Spectrometry
• Bioinformatics
• +۷ مورد دیگر

Pavel Sinitcyn is an Assistant Professor at Utrecht University working in the AI Technology for Life group within the Department of Information and Computing Sciences and the Biomolecular Mass Spectrometry and Proteomics group within the Department of Pharmaceutical Sciences. His research focuses on computational methods for analyzing mass spectrometry-based proteomics data, including advanced machine learning techniques. He previously conducted postdoctoral research at the University of Wisconsin-Madison and completed his PhD at the Max Planck Institute of Biochemistry in Munich. Ph.D. from Ludwig Maximilian University of Munich (2014-2020), Faculty for Chemistry and Pharmacy, Summa Cum Laude B.Sc./M.Sc. from Lomonosov Moscow State University (2009-2014), Faculty of Bioengineering and Bioinformatics Pavel Sinitcyn's research spans multiple interdisciplinary fields at the intersection of computational biology, mass spectrometry, and artificial intelligence. His primary focus is on developing computational methods for analyzing proteomics data, with particular expertise in deep proteome sequencing, phosphoproteomics, and integrative bioinformatics approaches. His work bridges human-centered artificial intelligence with life sciences applications, creating novel algorithms that improve the depth and accuracy of proteome analysis. His research has significant implications for understanding disease mechanisms, developing therapeutic targets, and advancing personalized medicine through comprehensive proteome characterization. Analysis of Sinitcyn's recent publications reveals a strong trajectory in developing computational tools for next-generation proteomics. His work consistently focuses on improving the depth, speed, and accuracy of proteome analysis through innovative algorithm development. Key trends include the application of artificial intelligence to mass spectrometry data, development of tools for variant and isoform detection, and creation of methods for comprehensive proteome characterization within practical timeframes. His publications demonstrate increasing impact in high-profile journals, with notable contributions to Nature Biotechnology, Nature Communications, and other leading scientific publications. Pavel Sinitcyn has been involved in teaching courses such as "Statistical learning and stochastic processes" at the College of Pharmaceutical Sciences. His work has been widely recognized in the scientific community, with numerous publications receiving substantial citations and attention, particularly his contributions to the MaxQuant and Perseus software platforms which have become standard tools in proteomics research.

Nathan Goodmanمشاهده پروفایل

استاد

• Radar Systems
• Signal Processing
• Cognitive Radar
• +۴ مورد دیگر

Dr. Nathan Goodman is a Professor in the School of Electrical and Computer Engineering at the University of Oklahoma, part of the Gallogly College of Engineering. He holds a Ph.D. in Electrical Engineering from the University of Kansas (2002). His research focuses on radar systems and signal processing, including cognitive radar, ground-moving target indication (GMTI), synthetic aperture radar (SAR), and compressive sensing applications in radar technology. Education : Ph.D., Electrical Engineering, University of Kansas (2002) M.S., Electrical Engineering, University of Kansas (1997) B.S., Electrical Engineering, University of Kansas (1995) Research Interests : Cognitive radar with adaptive waveform design GMTI and SAR imaging techniques Compressive sensing for radar signal processing Phased array radar systems and resource management Dr. Goodman’s recent publications explore topics like compressive sensing for time delay estimation, dynamic radar resource allocation, and phased array radar integration. His work emphasizes practical applications in weather monitoring and biomedical imaging. He has been recognized with the Madison A. and Lila Self Graduate Fellowship (1998). He advises at the Advanced Radar Research Center and leads the Radar Innovations Lab, focusing on cutting-edge radar technologies. His editorial roles include Associate Editor for IEEE Transactions on Aerospace & Electronic Systems and Finance Chair for the 2012 Sensor Array and Multichannel Signal Processing Workshop.

Scott Keatingمشاهده پروفایل

مدرس

• Seismic Inversion Methodology
• Uncertainty Quantification
• Numerical Optimization
• +۴ مورد دیگر

Dr. Scott Keating is a Lecturer at ETH Zurich’s Department of Earth and Planetary Sciences (D-EAPS), affiliated with the Institute of Geophysics. His research focuses on seismic inverse problem methodologies, particularly uncertainty quantification, numerical optimization, and the development of automated workflows for regional inversion updates. Current projects include full-waveform inversion of ambient noise measurements and CO2 storage monitoring using advanced sensor technologies like distributed acoustic sensing (DAS) and accelerometers. His work integrates cutting-edge computational methods, such as probabilistic inversion frameworks and adjoint-based optimization, to address challenges in subsurface imaging and parameter estimation. Applications span environmental seismology, carbon sequestration, and reservoir characterization, with a strong emphasis on practical, cost-effective solutions for real-world problems such as CO2 storage validation. Publications highlight contributions to elastic full-waveform inversion (FWI), including multiparameter analysis using combined geophone and DAS data, and innovative techniques like targeted nullspace shuttling to enhance inversion reliability. His research also addresses data sparsity and modeling uncertainties, advancing methodologies for robust subsurface monitoring and decision-making.

• Wireless Communications
• Radio Propagation
• Millimeter-wave (mmWave) Channels
• +۷ مورد دیگر

Xuesong Cai is an Associate Professor (Docent) in the Department of Electrical and Information Technology at Lund University, Sweden. He serves as an Associate Senior Lecturer and holds roles in ELLIIT and the NEXTG2COM Competence Centre. His research focuses on radio propagation, millimeter-wave (mmWave), and terahertz (THz) channel modeling for 5G and beyond wireless systems. He has published over 70 peer-reviewed papers and leads projects like 'Breaking the Barriers of Terahertz Communications.' Education: B.S. and Ph.D. (Hons.) from Tongji University (2013, 2018), with internships at Huawei and postdocs at Aalborg University, Nokia Bell Labs, and Lund University. Recognized with awards including the EU Marie Skłodowska-Curie Fellowship and Swedish Research Council grants. Key research interests include high-resolution parameter estimation, channel emulation, and radio-based localization. He is an Associate Editor for IEEE journals and a Senior IEEE Member. Projects span distributed MIMO, channel sounding technologies, and 6G initiatives. Supervised research students include Xu Y. and Al-Ameri A. His work contributes to UN SDGs related to innovation and infrastructure. Current grants include funding from the Crafoord Foundation and Swedish Research Council.

Roni Michaelyمشاهده پروفایل

استاد

• Empirical Corporate Finance
• Corporate Governance
• ESG
• +۴ مورد دیگر

Professor Roni Michaely is The Hong Kong Jockey Club Professor in Finance and Entrepreneurship at The University of Hong Kong (HKU) Business School, where he also serves as Associate Dean (Global Engagement), Chair of Finance and Entrepreneurship, and Co-director of the HKU Jockey Club Enterprise Sustainability Global Research Institute. He is the Founder & Executive Director of the HKU-TLV Innovation Hub and a research member at the European Corporate Governance Institute (ECGI). Previously, he was The Rudd Family Professor of Finance at Cornell University and Cornell Tech. Professor Michaely's research focuses on empirical corporate finance, corporate governance, ESG (examining how financial markets and institutions affect sustainability and climate change), and entrepreneurial finance. His work addresses how informational and agency frictions in capital markets influence managers, investors, and information providers' decisions and outputs, and their effect on capital market efficiency. He has published over 80 academic papers in top finance journals including the Journal of Finance, Review of Financial Studies, and Journal of Financial Economics. His recent publications demonstrate a strong focus on sustainability and corporate governance issues, with significant research on ESG investing, index fund monitoring, and the impact of social responsibility on firms. The research shows a clear trend toward examining how financial institutions and markets influence corporate behavior regarding environmental and social issues, with several high-impact papers published in leading journals between 2019-2024. Professor Michaely has received numerous prestigious awards throughout his career: 2024 Review of Finance best paper award 2024 Antitrust Writing Award Best paper award of the 2023 Financial Management Association International Best paper at the 2022 French Finance Association 2020 Review of Finance best paper award 2017 Distinguish research award of the Eastern Finance Association With over 33,000 citations, Professor Michaely is recognized as one of the most prolific researchers in finance. He has given over 300 invited research talks worldwide and collaborates with scholars from Asia, the US, and Europe. He has also co-founded two startups and serves on the advisory boards of several others. His practical experience includes serving as Director of the Israeli Securities Authority (1998-2003) and as chairperson of Tachlit investment committee. Professor Michaely leads the HKU-TLV Innovation Hub, which fosters collaboration between entrepreneurs from HK and China with those from Israel and Europe. This initiative aims to promote innovation and entrepreneurship, establish intellectual exchanges between the regions, and leverage Israel's strong startup ecosystem to benefit students, scholars, and business leaders from both areas.