جست‌وجوی استاد و پژوهشگر

• Hydrogeology
• Karst Systems
• Groundwater Flow Modeling
• +۳ مورد دیگر

Anita Mondok is an External Lecturer at the Institute of Health Promotion and Sport Sciences, Eötvös Loránd University (Hungary), with a focus on hydrogeological research and environmental tracer applications. Her academic work bridges groundwater dynamics, karst systems, and sustainable water management. 2025 : Studies on hypogene karst transitions and groundwater aging 2024 : Investigations in soda lake budgets, uranium mobility, and AI-driven hydrology Her research leverages isotopic tracers and numerical models to address drinking water quality, climate change impacts, and aquifer vulnerability. She has also explored unconventional topics like pediatric medicine and thermal spring biofilms, suggesting interdisciplinary interests. Her publications highlight applications of mesh graph neural networks and reactive transport models to hydrological challenges. While no formal awards or advisees are documented in available sources, her work directly informs groundwater protection strategies in Hungary and Northern Italy.

• 3D Imaging
• Signal Processing
• Optical Engineering
• +۵ مورد دیگر

Dr. Daniel Lau is a Professor and Director of Graduate Studies in the Department of Electrical and Computer Engineering at the University of Kentucky, part of the Stanley and Karen Pigman College of Engineering. He holds a Ph.D. (1999) from the University of Delaware and a B.Sc. (1995) from Purdue University. His research focuses on 3D imaging systems, spectral imaging, machine vision, and signal processing, with notable contributions to structured light technologies, blue-noise halftoning, and QR code embedding systems. Prior to academia, he worked as a DSP Engineer at Aware, Inc., and an Image and Signal Processing Engineer at Lawrence Livermore National Laboratory. Key research areas include 3D fingerprint identification, multispectral color acquisition/display, and compressive spectral imaging using novel coded apertures. His recent work emphasizes real-time 3D reconstruction, lens distortion correction, and hypergraph signal processing frameworks. Lau has pioneered methods for blue-noise sampling on non-Euclidean domains and developed algorithms for phase-measuring profilometry. His innovations in QR code embedding (e.g., Colored-QRNet) bridge machine vision and information security. Publications span 30+ years, showing progression from early work on halftoning (green-noise models) to current advancements in AI-driven imaging systems. He leads projects funded by NSF and industry partners, focusing on applications in automotive inspection, medical imaging, and industrial automation. His lab develops both theoretical frameworks and hardware implementations, such as FPGA-based error diffusion systems.

Hanieh Fattahiمشاهده پروفایل

پژوهشگر

• Ultrafast Optics
• Nonlinear Optics
• Attosecond Physics
• +۳ مورد دیگر

Hanieh Fattahi is the Head of the Femtosecond Fieldoscopy research group at the Max Planck Institute for the Science of Light in Erlangen, Germany (W2 equivalent position since 2020). She holds a PhD in Physics (summa cum laude) from the Max Planck Institute of Quantum Optics and Ludwig-Maximilians-University Munich (2015), under Prof. Ferenc Krausz. **Affiliations**: Max Planck Institute for the Science of Light, Max Planck School of Photonics Fellow (2020), and former Postdoctoral Scientist at the Max Planck Institute of Quantum Optics (2015-2017). Visiting Scientist roles include Harvard University (2019-2020) and Oxford University (2017-2018). **Research Focus**: Ultrafast optics, attosecond physics, femtosecond laser technology, and biomedical applications such as super-resolution microscopy. Recent work explores photonics education in underdeveloped regions using small language models. **Awards**: Best Lecturer (Siegman Summer School, 2019), Elisabeth-Schiemann Kolleg Member (2018), and Minerva Fast-Track Position (2017-2019). **Grants & Leadership**: Co-coordinator of the International Max Planck Research School of Advanced Photon Science (2016-2019), and organizer of major conferences like CLEO Europe and IEEE Photonics.

• Business Information Systems
• Digital Transformation
• Artificial Intelligence Applications
• +۳ مورد دیگر

Josep Lluís Cano Giner serves as a Senior Lecturer and Assistant Professor in the Department of Operations, Innovation and Data Sciences at Esade Business School. His academic career spans over 15 years with consistent research output from 2009 through 2024. His work bridges business operations with technological innovation, focusing particularly on how digital transformation impacts organizational processes and decision-making. Dr. Cano Giner's research interests center on the practical applications of technology in business contexts. His work examines how artificial intelligence, particularly generative AI, can enhance productivity and transform traditional business operations. He has published extensively on digital transformation, information systems implementation, and the integration of sustainability goals into business decision processes. His fingerprint analysis reveals significant contributions to Marketing, Management Information Systems, and Digital Business fields, with strong connections to Barcelona's business ecosystem. Analysis of his publication trends shows a clear evolution toward cutting-edge business technology applications, with recent work focusing on generative AI's impact on productivity, human augmentation in manufacturing, and the role of business simulations in promoting sustainable development goals. His research demonstrates consistent engagement with both theoretical frameworks and practical business case studies across multiple industries. Dr. Cano Giner has been actively involved in research projects, most notably as a researcher in the GRUGET (Grup de Recerca en Gestió Turística) projects from 2009-2013 and 2014-2017. These collaborative research initiatives focused on tourism business management and demonstrate his engagement with interdisciplinary research teams addressing complex business challenges in the tourism sector.

Adrian Virgil CRĂCIUNمشاهده پروفایل

دانشیار

• Electronic circuits analysis and design
• Electronic devices and circuits modeling
• Data acquisition systems
• +۷ مورد دیگر

Adrian Virgil CRĂCIUN is an Associate Professor at the Department of Electronic and Computers, Faculty of Electrical Engineering and Computer Science, Technical University of Brașov. His research focuses on analog electronics, electronic circuit modeling, and data acquisition systems. He has published extensively on topics like VHDL-based filter design, low-power amplifiers, and FPGA security. His work includes both theoretical contributions and practical implementations in medical electronics and embedded security systems. Education Background: No explicit education details provided in text Research Interests: Dr. CRĂCIUN specializes in electronic circuit analysis and design, with emphasis on analog systems. His work integrates hardware security (PUF-based solutions), low-power medical electronics, and advanced simulation techniques using VHDL. Recent efforts focus on optimizing power consumption in complex integrated circuits and developing robust FPGA identification methods. Grants & Collaborations: No grant information explicitly stated Labs & Teams: Participates in university-based electronics research groups focused on analog circuit design and embedded systems security.

Moawia Eldowمشاهده پروفایل

دانشیار بالینی

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۲ مورد دیگر

Dr. Moawia Eldow is a Clinical Associate Professor in the Department of Computer Science and Engineering at the University of North Texas. His research spans artificial intelligence, machine learning, and computer vision, with applications in healthcare, security, and education. His recent work includes COVID-19 detection algorithms and facial recognition systems. His publications demonstrate a consistent focus on neural networks, pattern recognition, and human-computer interaction. Recent articles explore AI diagnostics, educational technology, and cybersecurity, reflecting interdisciplinary collaboration with healthcare and linguistics domains. Dr. Eldow maintains an extensive publication record with contributions to IEEE, Springer, and ACM venues. His lab investigates adaptive algorithms for real-world challenges including medical diagnostics and network optimization.

Carsten Jersمشاهده پروفایل

پژوهشگر

• Enzyme Biochemistry
• Molecular Biology
• Bacterial Signal Transduction
• +۶ مورد دیگر

Carsten Jers is a Senior Researcher at the Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark (DTU), specializing in bacterial signal transduction and enzyme engineering. His work contributes to multiple UN Sustainable Development Goals through biosustainability research. As part of the DTU Microbes Initiative, he maintains an active research profile with 44 publications and involvement in 9 research projects. Dr. Jers' research focuses on enzyme biochemistry, molecular biology, and microbiology, with particular expertise in sialidase/neuraminidase studies, protein phosphorylation mechanisms, and thermostability of enzymes. His fingerprint analysis reveals strong connections to Escherichia coli research (85%), thermostability studies (55%), protein phosphorylation (49%), and human milk oligosaccharide research (47%). His recent publications demonstrate a strong trend in enzyme engineering for industrial applications, genomic analysis of bacterial pathogens (particularly Enterococcus species), and development of bacterial systems for protein production. His work bridges fundamental molecular mechanisms with practical applications in food safety, biocatalysis, and sustainable bioproduction. Dr. Jers actively supervises multiple PhD students through the Novo Nordisk Foundation Center for Biosustainability, with current projects focusing on bacterial cell engineering, pathogen proteomics, and microbiome analysis. His research has gained significant attention, with publications mentioned by news outlets, blogged about, and shared across social media platforms including X (Twitter) and Facebook. His laboratory work centers on bacterial signal transduction mechanisms, with particular focus on developing engineered bacterial systems for industrial applications, studying microbial safety profiles, and exploring thermostable enzymes from extremophiles for biocatalytic processes.

• Steganography
• Biometric Data Security
• Signal Processing
• +۳ مورد دیگر

Mandy Douglas is an Assistant Lecturer in the Department of Computing at Atlantic Technological University. Her research focuses on steganography techniques for biometric data protection, automotive safety systems using sensor technologies, and signal processing algorithms for secure image watermarking. She has published three peer-reviewed works between 2017 and 2021, addressing topics ranging from intoxicated driver prevention systems to fingerprint image security enhancement through mathematical transforms like SVD and DWT. Her research interests intersect computer science, information security, and engineering applications. Key contributions include developing embedded systems for vehicle safety and advancing methods to protect biometric data through advanced steganographic approaches.

Steven Goderisمشاهده پروفایل

استاد پژوهشی

• Geochemistry
• Cosmochemistry
• Environmental Science
• +۵ مورد دیگر

Steven Goderis is a Research Professor at the Vrije Universiteit Brussel (VUB), affiliated with the Department of Geochemistry and Environmental Sciences within the Faculty of Sciences. His work focuses on interdisciplinary research in geochemistry, cosmochemistry, and environmental science, with expertise in meteorites, isotopes, and impact processes. He holds a PhD from VUB (2011) and has supervised 26 research projects and student theses. Key areas of research include analysis of impact structures, micrometeorite flux dynamics, and isotopic tracing of environmental and planetary processes. Notable projects include the FLUX project studying cosmic dust flux and the HERC65 initiative exploring X-ray analytical approaches. His work has been recognized with awards such as the 1st Prize for podium presentation (2024) and the 2021 Best Student Poster award. Recent publications (2023–2025) highlight studies on clumped isotope thermometry, impact event isotopic signatures, and the geochemical analysis of meteorites. His research also addresses climate impacts of large-scale events like the Chicxulub impact, linking extraterrestrial material to Earth's environmental history. Collaborations span global institutions, with active projects in Antarctica, Greenland, and Poland. He has hosted multiple academic visitors and contributed to media outreach through high-profile publications in Nature Geosciences and Science Advances .

• Behavioral Biometrics
• User Authentication
• Affective Classification
• +۵ مورد دیگر

Joseph Barrowclough is an active researcher with a PhD, focusing on interdisciplinary applications of artificial intelligence across behavioral biometrics, neuroscience, and educational technology. His work bridges computer science with practical implementations in user authentication, affective computing, and scholarly writing analysis. Research Interests: Specializing in behavioral biometrics, Barrowclough develops machine learning systems for user authentication while exploring EEG-based affective classification and NLP tools for academic writing evaluation. His environmental science collaborations demonstrate AI's versatility in waste management applications. Recent Publications reveal expertise in Behavioral biometric dataset creation Deep learning for affective computing Machine learning in educational outcome prediction NLP-based language assessment systems Environmental image classification Collaborations: Barrowclough works extensively with colleagues like Nnamoko, Korkontzelos, and Liptrott, contributing to the SustainNET research group and maintaining connections through the Fingerprint Network.

• Archaeology
• North American Archaeology
• Mississippian Culture
• +۳ مورد دیگر

Tamira K Brennan serves as an Associate Research Scientist within the Archeology Collection of the Illinois State Archaeological Survey at the University of Illinois Urbana-Champaign. Her research centers on the Mississippian period (800-1500 CE) in the American Midwest, with intensive focus on Cahokia and Kincaid Mounds as critical hubs of pre-Columbian sociopolitical complexity. Her work spans North American Archaeology , Mississippian Culture studies , archaeological diaspora dynamics , and mound-centered settlement analysis . She integrates scientific methodologies including radiocarbon dating, dendrochronology, and isotopic analysis to reconstruct population movements, cultural interactions, and environmental adaptations in indigenous societies. Her fingerprint analysis reveals dominant connections to East St. Louis precincts, Cahokia regional networks, and diaspora formation processes. Recent publications demonstrate a methodological emphasis on refining chronological frameworks through tree-ring and radiocarbon techniques at Kincaid Mounds, while her theoretical contributions explore diaspora as a lens for understanding Cahokian influence across the Southeast. This dual approach bridges precise scientific dating with broader anthropological questions about cultural transmission. Based at the Illinois State Archaeological Survey, Dr. Brennan contributes to one of North America's most significant archaeological repositories, where she engages in field research, curation of material culture, and public interpretation of indigenous heritage through transportation archaeology initiatives and media outreach including her 2024 feature 'Excavating my own archaeology'.

• Software Engineering
• Software Defect Prediction
• Machine Learning for Software Engineering
• +۷ مورد دیگر

Akito Monden is a prolific Japanese software-engineering scholar with 171 publications recorded in dblp during 1995-2025. His recent work centres on defect prediction, online learning, bandit-based tool selection, and empirical studies of software quality and human factors. Research interests span software defect prediction, mining software repositories, effort estimation, clone detection, code generation, and the application of machine-learning techniques (notably bandit algorithms and ensemble methods) to practical software-engineering tasks. He also investigates requirements ambiguity, security-bug identification with large language models, and gaze-based human-computer interaction in programming education. Across 2022-25 articles Monden explores online learning to cope with concept drift in defect datasets, multi-armed bandit algorithms for dynamic selection of clone detectors, fault-localisation techniques and code generators, and LLM-based security-bug detection. These themes reflect a sustained focus on data-driven, adaptive approaches that improve software quality assurance processes.

Nicolas AGUIRREمشاهده پروفایل

پژوهشگر

• Cardiovascular Health
• Machine Learning
• Biomedical Engineering
• +۳ مورد دیگر

Nicolas AGUIRRE is a Researcher at the University of Technology of Troyes (UTT), specializing in cardiovascular health and machine learning applications. His work focuses on analyzing blood pressure waveforms and morphologies using advanced techniques like deep learning and CycleGAN. He has contributed to studies on central arterial dynamics, coronary artery assessment, and arterial-ventricular coupling impairments. Key research interests include biomedical engineering, signal processing, and health informatics. His recent work emphasizes developing in silico models and non-invasive diagnostic tools, with publications in journals like Sensors. He has also explored educational initiatives in machine learning through the clusterAI pipeline in Argentina. Collaborations involve projects on artificial neural networks for cardiovascular age assessment and attention mechanisms for blood pressure analysis. Despite his prolific publication record, no scientific awards or student advisement are explicitly listed here.

• Metabolomics
• Mass Spectrometry
• Gene Cluster Analysis
• +۳ مورد دیگر

Justin van der Hooft is an EPS Assistant Professor in Bioinformatics (BIF) at Wageningen University & Research. His research focuses on metabolomics, mass spectrometry, and computational approaches to natural product discovery. He leads efforts in gene cluster analysis, molecular networking, and AI-driven data integration. His work emphasizes open science and collaboration, as highlighted by the Lighthouse Award 2022 and contributions to tools like antiSMASH and MIBiG. Research interests include advancing computational methods for metabolite identification, optimizing mass spectrometry workflows, and leveraging AI for natural product discovery. Key projects involve linking biosynthetic gene clusters to metabolites, developing scalable data platforms, and exploring plant and microbial specialized metabolomes. Recent articles highlight advancements in mass spectrometry data patterns, AI integration, and community-driven curation of biosynthetic gene clusters. His contributions span over 130 publications, emphasizing metabolomics, gene cluster analysis, and computational biology. Advising: Co-promotor for PhD students in metabolomics, bioinformatics, and microbial ecology projects. Grants/Projects: Active in food safety analysis, natural product discovery, and integrative omics studies. Labs/Teams: Collaborates with global networks on antiSMASH, MIBiG, and molecular networking initiatives.

Christiaan Bekkerمشاهده پروفایل

پژوهشگر ارشد

• Quantum Physics
• Materials Science
• Photonics
• +۳ مورد دیگر

Christiaan Bekker serves as a Research Fellow at Heriot-Watt University's Institute of Photonics and Quantum Sciences within the School of Engineering & Physical Sciences. His work bridges physics and engineering for quantum technology applications. His research focuses on atomic-scale defects in silicon carbide, specializing in quantum emitters and scalable quantum memory development. Key areas include femtosecond laser fabrication of solid immersion lenses, spectroscopy of quantum systems, and integrated quantum photonics. The fingerprint analysis reveals strong expertise in silicon carbides (100%), solid-state systems (85%), optical lenses (77%), and spin physics (54%). Recent publications demonstrate consistent output from 2014-2025 with accelerated activity in 2025, showing specialization in quantum emitter characterization, nanofabrication techniques, and silicon carbide-based quantum devices. The work spans journal articles, conference proceedings, and preprints with significant open-access availability. Bekker actively supervises PhD students through projects like 'Engineering a scalable quantum memory in silicon carbide' and has contributed to three major datasets supporting quantum research. His collaborations include prominent institutions working on silicon carbide quantum systems and photonics integration. Current research involves quantum sensing applications, ultra-narrow spectral distribution studies of vanadium centers, and real-time adaptive estimation of qubit decoherence. The work maintains strong industry and academic partnerships focused on scalable quantum technologies.