جست‌وجوی استاد و پژوهشگر

Denis Vladimirovich Kapulinمشاهده پروفایل

دانشیار

• Space Instrumentation
• Satellite Navigation Systems
• Radio-Electronic Equipment Design
• +۴ مورد دیگر

Denis Vladimirovich Kapulin is an Associate Professor at the School of Space and Information Technologies, Siberian Federal University, holding the academic title of доцент (Associate Professor) with a Candidate of Technical Sciences degree in technical sciences. His work spans multiple departments related to radio-electronic systems and space instrumentation, with an office located at Kirensky street, 26B, building № 17 (F), room 2-20a. He serves as Acting Director of a research unit focused on space instrumentation and navigation systems. Dr. Kapulin's research interests center around space instrumentation, satellite navigation systems, radio-electronic equipment design, and production optimization. His work bridges theoretical research with practical applications, particularly in developing miniature band-pass microwave filters, angular satellite navigation equipment, and automated production planning systems. He has made significant contributions to both aerospace engineering and manufacturing optimization fields, with numerous patents reflecting his practical approach to solving engineering challenges. His publication trends show consistent research output with 15+ publications annually, demonstrating expertise across multiple domains including satellite navigation, production planning, and radio-electronic equipment design. Recent work focuses on digital transformation in manufacturing, augmented reality applications for predictive maintenance, and optimization of small-batch production systems. Scientific Awards and Recognition: Laureate of the award for young talents of the head of Krasnoyarsk city for achievements in scientific and educational activities Laureate of the award from JSC AKC "International Financial Club" for contributions to space instrumentation science Expert in the scientific and technical field of FSBSI NII RINKTSE Member of the expert council of the Krasnoyarsk regional innovation and technology business incubator Dr. Kapulin has secured multiple significant research grants from the Russian Ministry of Education and Science, including projects on high-tech production of miniature band-pass filters (2017-2019), development of highly selective microwave filters (2017-2019), creation of angular satellite navigation equipment (2016-2017), and architecture development for System-on-Chip navigation receivers (2015-2017). His collaborative research involves extensive work with colleagues like Oleg Drozd and Polina Russkikh across multiple laboratories focused on radio-electronic systems and space technologies. The research team he participates in maintains strong connections with industry partners in the aerospace and radio-electronic sectors, facilitating technology transfer from academic research to practical applications. Current projects focus on digital transformation of manufacturing processes, advanced satellite navigation systems, and optimization of production planning for small-batch manufacturing environments.

Daniel Martin Yergaمشاهده پروفایل

استاد مدعو

• Electrochemistry
• Sustainable Energy Conversion
• Materials Science
• +۶ مورد دیگر

Daniel Martín-Yerga is an Adjunct Professor at the Department of Chemistry and Materials Science, Aalto University, with a focus on advancing clean technologies for a low-carbon future through electrochemistry. His work bridges sustainable energy conversion, materials science, and analytical chemistry. Green hydrogen production Electrochemical valorization of biomass Development of functional materials for electrochemical systems His research employs advanced methodologies such as materials synthesis, high-throughput experimentation, correlative multi-microscopy, and multiscale electrochemistry to uncover performance-degradation relationships. Publications span journals like ACS Nano , ACS Applied Energy Materials , and Angewandte Chemie , emphasizing lithium-ion batteries, electrocatalysis, and surface engineering.

• Theoretical Physics of Amorphous Materials
• Charge Transport Modeling in Semiconductors
• Phase-Change Memory Devices
• +۲ مورد دیگر

Rossella Brunetti is an Associate Professor at the Department of Physical, Computer and Mathematical Sciences (formerly Physics campus) at the University of Modena and Reggio Emilia . Her research focuses on theoretical physics of amorphous materials, particularly chalcogenides used in phase-change memory (PCM) devices. She specializes in charge transport modeling, hydrodynamic equations, and advanced numerical methods like the Numerov process. Research Interests: Theoretical physics of amorphous semiconductors, trap-limited conduction, time-dependent transport phenomena, and simulation of nanoscale devices. Her work bridges fundamental physics with technological applications in high-speed memory devices and semiconductor modeling. Notable Contributions: Development of the first self-consistent 5th-order numerical methods for non-uniform grids 3D random-network models for threshold switching Quantum transport frameworks for hot-carrier dynamics Her research has enabled accurate simulation of Ovonic devices and contributed to understanding voltage snapback phenomena.

Jian Luمشاهده پروفایل

استاد

• Nanostructured Materials
• Surface Science and Engineering
• Experimental Mechanics
• +۵ مورد دیگر

Professor Jian Lu is the Dean of the College of Engineering and Chair Professor of Mechanical Engineering at City University of Hong Kong. He concurrently directs the Hong Kong Branch of National Precious Metals Material Engineering Research Center (NPMM) and the Centre for Advanced Structural Materials (CASM). An Academician of France's National Academy of Technologies and recipient of the French Legion of Honor, he holds affiliations with biomedical and materials science departments. Education: Habilitation in Mechanics, Sorbonne University (1993) PhD in Materials Science, University of Technology of Compiegne (1986) MSc in Materials Science, University of Technology of Compiegne (1984) MEng in Mechanical Engineering, University of Technology of Compiegne (1984) Research Focus: His work spans nanostructured metallic materials, surface engineering, 4D printing, residual stress analysis, and biomaterials. Pioneering contributions include dual-phase nanostructuring for ultra-strong alloys, metallic glass catalysts, and origami-inspired ceramic manufacturing. Research integrates computational modeling with experimental mechanics to enhance material properties. Publication Trends: Recent articles (2023-2024) demonstrate expansion into energy-related applications, including hydrogen evolution catalysts, zinc-air batteries, and water purification systems. Over 45% of recent works involve multi-material design or additive manufacturing, reflecting cross-disciplinary innovation. Awards & Honors: Chevalier de la Légion d'honneur (2017) Guanghua Engineering Science Award (2018) Gold Medal, Brussels World Innovation Expo (2007) Fellowships: SEM (USA), HKAES, HKIS Leadership & Grants: Secured 25+ competitive grants since 2007 totaling >HK$50M, including CRF projects on magnesium implants and ITF initiatives on nanostructured gold. Oversees 100+ researchers at CASM and NPMM, focusing on lightweight structural materials and precious metal engineering.

• Bayesian Inference
• Digital Signal Processing
• Global Navigation Satellite Systems (GNSS)
• +۵ مورد دیگر

Alex Minetto is a Fixed-Term Tenure-Track Assistant Professor at the Department of Electronics and Telecommunications (DET), Politecnico di Torino. He teaches courses such as Satellite Navigation Signal Exploitation and Numerical Estimation Methods across various Engineering programs. Research interests include Bayesian inference, GNSS signal processing, and deep-space navigation. Key research lines involve designing Bayesian filters, lunar orbiter GNSS applications, and RFI threat monitoring. His 2025-2024 publications focus on GNSS for cislunar navigation, solar storm impacts, and inter-orbiter synchronization. Supervised PhD students include Lorenzo Sciacca, Luca Morichi, and Anais Delepaut. He contributes to projects like INSPIRE and collaborates with NavSAS research group.

• Machine Learning
• Deep Learning
• Health Data Analysis
• +۳ مورد دیگر

Mattias Ohlsson is a Visiting Professor at the School of Information Technology , Halmstad University . His research focuses on machine learning and deep learning for analyzing diverse health data, particularly patient trajectory modeling with multimodal approaches. Primary affiliation: IT - Computer Department Collaboration areas: Healthcare sector and industry His work emphasizes explainable AI in clinical contexts, including survival analysis, cardiac event prediction, and cross-domain applications in satellite poverty mapping. Recent projects explore temporal healthcare data analysis using transformer architectures and self-supervised learning . Key article trends include: 2025: AI integration with medical expertise for emergency diagnostics 2024: Survival model evaluation, temporal data challenges, and graft failure prediction 2023: Multi-robot routing optimization and fatty liver disease etiology modeling 2022: Heart failure mortality algorithms and anomaly detection systems Current affiliations include the CAISR Health research group, with technical expertise spanning CNNs, transformers, and robust imputation methods.

• Textile and Fashion Design
• Garment Production
• Textile Engineering
• +۳ مورد دیگر

Raşit ARSOY serves as a full-time Lecturer and Department Head in the Textile and Fashion Design Department at Kafkas University's Faculty of Fine Arts since 2019. Holding a PhD in Textile Engineering from Süleyman Demirel University, he bridges academic theory with industrial applications in textile manufacturing and fashion technology. Education: PhD in Textile Engineering, Süleyman Demirel University, Faculty of Engineering (2010-2015) Master's in Technology of Clothing Products, Azerbaijan University of Technology (2000-2002) Bachelor's in Garment Technology and Construction, Azerbaijan University of Technology (1996-2000) His research centers on optimizing garment production through textile engineering innovations, with emphasis on bias tape efficiency, fabric waste reduction, and bonding technologies. He develops specialized software solutions for ready-made clothing industry challenges while advancing textile machinery design and sustainable manufacturing practices. Analysis of his 32 publications reveals a consistent focus on practical industrial applications, particularly software-driven efficiency improvements in cutting rooms and bias tape management. His work increasingly integrates mechanical engineering principles with fashion technology to solve production bottlenecks. Scientific Awards: Ispartek 2012 Proje Pazarı - Dalga Enerji Sistemi (2012) ARSOY has secured three research projects as principal investigator for software development initiatives targeting bias tape optimization (2021-2023, 2024-2025) and co-investigated adhesive technology development (2012-2014). Though actively teaching 40+ courses including Technical Drawing and Garment Design, he has no thesis advisees. His collaborative network spans 8 researchers including Gabil Abdulla (16 joint works) and İbrahim Üçgül (8 publications), reflecting strong interdisciplinary partnerships in textile engineering.

Johanna Viitanenمشاهده پروفایل

استادیار

• Usability
• User Experience
• User-Centred Design
• +۶ مورد دیگر

Johanna Viitanen is an Assistant Professor at the Department of Computer Science , Aalto University School of Science . Her work focuses on usability , user experience , and user-centred design within healthcare and social care contexts, particularly examining health information systems , patient experiences , and IT procurement processes. Doctoral degree (2011), Aalto University Licentiate degree (2009), Helsinki University of Technology Master's degree (2005), Helsinki University of Technology Her research explores the intersection of human-computer interaction and health informatics , addressing challenges in electronic health records (EHRs) , digital ethics , and socio-technical systems . She leads the BOC Home Dialysis project (2022–2026) to optimize predialysis and home dialysis care through technology. Recent publications (2024–2025) analyze physician and nurse experiences with EHR usability, socio-technical challenges in healthcare IT, and cross-sectional surveys on digitalization's impact on professional job strain . She received the CHI 2025 Honorable Mention Award for contributions in human-computer interaction and ergonomics . Viitanen actively participates in hosting academic visitors , organizing healthcare digital transformation events , and reviewing scientific journals . Her work aligns with UN Sustainable Development Goals related to education and digital equity in healthcare.

Shenghan Guoمشاهده پروفایل

استادیار

• Knowledge-informed data analytics and AI
• Human-in-the-Loop Machine Learning
• Human-AI collaborative manufacturing
• +۵ مورد دیگر

Shenghan Guo is an Assistant Professor in the School of Manufacturing Systems and Networks at Arizona State University, specializing in data-driven solutions for smart manufacturing. She leads the DAIM (Data Analytics & Insights in Manufacturing) research lab, which focuses on human-AI collaboration in manufacturing processes. Her lab utilizes specialized equipment including an OPTOMEC Aerosol Jet Printer for flexible 3D printing applications. Education: Ph.D. in Industrial and Systems Engineering, Rutgers University (2021) M.S. in Engineering Sciences and Applied Mathematics, Northwestern University (2016) M.S. in Financial Mathematics, Johns Hopkins University (2014) B.S. in Financial Engineering, Jilin University (2013) Her research integrates knowledge-informed AI with human-centered approaches to advance manufacturing systems. Key areas include: Human-in-the-Loop ML : Developing collaborative AI systems that incorporate human expertise Additive Manufacturing : In-situ monitoring and defect detection for 3D printing Process Optimization : Real-time quality control using computer vision and signal processing Publications (2017-2025) demonstrate a consistent focus on machine learning applications in manufacturing, with recent emphasis on generative AI for process simulation, contrastive learning for worker monitoring, and multi-modal data fusion for quality prediction. Over 60% of recent works involve additive manufacturing applications. Awards and Honors: ASU FWA Outstanding Mentor Award (2023) INFORMS Best Paper Runner-up (2021) IISE Data Challenge Winner (2019-2020) NSF Conference Support Awards Advising and Grants: Currently mentors three PhD students (Hasnaa Ouidadi, Pius Gyamenah, Boyang Xu) whose work has received SME 30 Under 30 recognition and AEC awards. Secured lab funding for advanced manufacturing equipment supporting electronic printing and human-machine interaction research. Teaching includes courses on computational modeling (EGR 219), machine learning (RAS 585), and specialized manufacturing topics. Developed new curriculum integrating real-world manufacturing data with Python-based ML implementations.

• Fluid-driven mineral reactions
• Nanoscale transport phenomena
• Reactive fluid-rock interaction
• +۳ مورد دیگر

Dr. Alireza Chogani is a Researcher at the Earth Sciences department within Utrecht University's Geosciences school. His work focuses on unraveling the nanoscale mechanisms driving fluid-rock interactions in the Earth's lithosphere. Key research areas: fluid-driven mineral reactions, nanoscale transport phenomena, metamorphic fabric formation Current project: ERC-funded nanoEARTH (2019-2025) investigating reactive fluid dynamics in mineral nanopores His research combines multi-scale physics with geological observations, integrating: Nanoscale experimental analysis In operando imaging of mineral transformations Molecular-to continuum-scale transport modeling Recent publications highlight his contributions to nanopore geochemistry, metamorphic stress dynamics, and advanced imaging techniques for geological processes. He collaborates with researchers like Dr. Oliver Plümper and Dr. Hamed Amiri within the nanoEARTH project.

• Health Informatics
• Clinical Informatics
• Electronic Health Records
• +۸ مورد دیگر

Dr. A Jay Holmgren is an Assistant Professor and Associate Division Chief for Research in the Division of Clinical Informatics and Digital Transformation (DoC-IT) at the University of California, San Francisco School of Medicine. He also serves as Director of the Center for Clinical Informatics and Improvement Research (CLIIR) and holds faculty affiliations at the UCSF Bakar Computational Health Sciences Institute, the Philip R. Lee Institute for Health Policy Studies, and the UCSF UC Berkeley Joint Program in Computational Precision Health. Additionally, he is a Senior Advisor at the Stanford Clinical Excellence Research Center. Dr. Holmgren earned his PhD in Health Policy from Harvard University in 2021, an MHI in Health Informatics from the University of Michigan in 2017, and a BA in History from the University of Michigan in 2011. He also completed UCSF's Diversity, Equity, and Inclusion Champion Training in 2022. His research focuses on the impact of information technology on patients, clinicians, and healthcare organizations, with particular attention to electronic health records, health information exchange, and the deployment of artificial intelligence in clinical care delivery. His work examines how digital tools affect clinician workflow, patient communication, and healthcare quality. Recent research has increasingly focused on generative AI evaluation and monitoring in clinical settings. Analysis of Dr. Holmgren's recent publications reveals a consistent focus on using EHR metadata to understand clinician behavior and healthcare delivery. His work spans multiple domains including interoperability measurement, physician workload analysis, AI implementation in healthcare settings, and the relationship between documentation burden and care coordination. His research employs sophisticated methodologies combining causal inference econometrics with machine learning approaches to address complex healthcare delivery questions. Among his notable scientific achievements are multiple prestigious awards including the NIH Loan Repayment Program Award, the Medical Informatics Europe Best Paper Award, and the CHITA Best Young Researcher Award. His work has been recognized for both methodological rigor and practical impact on healthcare delivery systems. As Principal Investigator on the NIH/NLM R01LM014770 grant titled 'The Last Mile of Interoperability: Integrating Outside Data Into Clinical Workflows to Improve Care,' Dr. Holmgren leads research examining how clinicians use outside records data and developing open-source tools to improve EHR workflows. His research has been published in top-tier journals including JAMA, Health Affairs, and JAMIA, and featured in major media outlets such as The New York Times and NPR. Through the Center for Clinical Informatics and Improvement Research (CLIIR), Dr. Holmgren oversees a research program dedicated to improving healthcare delivery through informatics approaches. His work bridges clinical practice, health policy, and technological innovation to address pressing challenges in healthcare delivery systems.

• Nanoparticle synthesis
• Plasmonic materials
• Polymer and colloid chemistry
• +۴ مورد دیگر

Vladimir Kitaev is a Professor in the Department of Chemistry and Biochemistry at Wilfrid Laurier University. His research focuses on applications of nanoparticles, materials with tunable optical and electronic properties, nanoparticle synthesis, and polymer/colloid chemistry. Education: MSc in Polymer Chemistry from Lomonosov Moscow State University, PhD in Materials Chemistry from the University of Toronto Research: Nanoscale chirality, size- and shape-selective nanoparticle synthesis, plasmonic metal nanoparticles, biosensing substrates, water remediation technologies Current Projects: Collaboration with Nicoya Inc. on plasmonic sensors and Imperial Oil on environmental remediation His work explores colloidal nanoscale building blocks (NBBs) with controlled properties for sensing and photonics applications, particularly silver decahedra, pentagonal rods, and gold nanostructures. Research spans from fundamental nanoparticle synthesis to applied projects in cancer therapy, chemical detection, and photonic crystal development. The selected publications (2016-2025) focus on plasmonic materials, nanoparticle self-assembly, and biomedical applications. Key themes include nanoparticle surface chemistry, optical property control, and advanced sensing techniques. The research group (CLAN) specializes in translating nanoscience discoveries into practical solutions.

• Automatic Control Systems
• Energy Loss Minimisation in Electric Motors
• Fuzzy Logic Control
• +۳ مورد دیگر

Eleftheria Sergaki is a permanent Laboratory Teaching Staff member (EDIP) at the Technical University of Crete , School of Electronic and Computer Engineering and the Electrical Power Systems Laboratory . She has served the university continuously since 1985 in roles ranging from Contract Lecturer-Researcher to her current academic post. Education PhD in Electronic & Computer Engineering, Technical University of Crete, 2011 MSc in Electronic & Computer Engineering, Technical University of Crete, 1997 BSc in Physics, Aristotle University of Thessaloniki, 1985 Research Interests Her research lies at the intersection of automatic control, energy efficiency and machine learning . Core themes include the design of fuzzy-logic-based control algorithms that minimise energy losses in electric motors—work that has yielded an individual 2008 patent—the application of machine-learning techniques for predictive modelling of physical processes, and the development of AI-assisted diagnostic algorithms for medical imaging. Across these areas she leverages techniques such as adaptive control, artificial neural networks, neuro-fuzzy systems, discrete wavelet transforms and convolutional neural networks, bridging power engineering, biomedical engineering and computer science. Publication Trends Her 27 peer-reviewed works (2000–2023) exhibit a clear trajectory: early contributions focused on laser instrumentation and physics education shifted after 2006 toward electric-motor efficiency optimisation and advanced motor-control algorithms , and since 2018 have expanded into deep-learning applications in medical imaging , particularly capsule endoscopy and brain-tumour detection. Scientific Awards & Distinctions Teaching Work Award (EDIP) – Senate of the Technical University of Crete, 2018 National distinction – Greek delegation leader, International Physics Teaching Conference, CERN Distinction – Panhellenic Physics Construction and Experiment Competition, National Research Foundation 2 nd eligible contractor – national educational textbook authoring programme Grants, Projects & Service Scientific Project Manager, EPEAEK Project (Greek National Research Council), 1998–2000 Evaluator, IEEE Transactions on Industrial Electronics, IEEE Transactions on Fuzzy Systems, Elsevier journals, etc. Co-author, Laser: Working Principles and Applications (Evgenidis Foundation, 2008) Laboratory & Team Affiliations She is a key member of the Electrical Power Systems Laboratory , where she co-supervises student projects and experimental work. Previously she co-founded and worked in the Laboratory of Matter Structure & Laser Physics (TUC) from 1985 to 2013, contributing to its establishment and instrumentation.

• Materials Science
• Solid State Physics
• Ultra-High Temperature Ceramics (UHTC)
• +۴ مورد دیگر

Alexey Popov is an Associate Professor at Taras Shevchenko National University of Kyiv, Ukraine, with a focus on advanced ceramic materials and reaction sintering techniques. His academic career spans over two decades, including roles as a Reader (2006–2012) and Research Scientist (2003–2006). He holds a Doctor of Science degree (2018) and a Ph.D. (2006) in Solid State Physics from his affiliated university. Education: Master's (1999), Ph.D. (2006), Doctor of Science (2018) Current Position: Associate Professor (2014–Present) His research emphasizes ultra-high temperature ceramics (UHTC) with in-situ formed carbon nanostructures, exploring how processing parameters influence material properties. Key contributions include enhancing UHTC toughness using graphite plates and CNTs, developing reactive hot pressing methods for dense ceramics, and studying thermal shock resistance mechanisms. Recent publications highlight his work on graphene-reinforced composites, high-entropy ceramics, biocompatible materials, and advanced sintering techniques. His methodological expertise includes powder metallurgy, X-ray diffractometry, and scanning electron microscopy with energy-dispersive spectroscopy. Future projects aim to expand reaction sintering to new ceramic systems like ZrB2-SiC-C and HfB2-SiC-C, develop multiphase and high-entropy ceramics, and explore applications in armor plates, bone prosthetics, and concentrated solar energy absorbers.

Luc Van Goolمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Object Recognition
• +۵ مورد دیگر

Prof. Luc Van Gool is a leading academic in computer vision and machine learning, holding dual positions at ETH Zurich and KU Leuven. He heads the Computer Vision Laboratory at ETH Zurich while leading the Computer Vision Research Group at KU Leuven. With over 160,000 citations, he ranks among the world's most cited computer scientists and has co-founded 12 startups that attracted tech giants like Nvidia, Apple, and Facebook to Zurich. His research spans 2D/3D object recognition , texture analysis , range acquisition , stereo vision , robot vision , and optical flow . Recent work demonstrates exceptional breadth across fundamental algorithms and real-world applications, with particular emphasis on robustness in dynamic environments and cross-domain adaptation. His teams consistently bridge theoretical innovation with industrial implementation through EU-funded projects like Vanguard, Improofs, and Impact. 2025 publications reveal dominant trends in multimodal learning , 3D scene representation via Gaussian splatting , and incremental object detection . Key advancements include vision-language model integration, embodied reasoning frameworks, and robustness benchmarks for human-object interaction. The research demonstrates a strategic shift toward compositional learning and cross-domain generalization while maintaining core strength in classical vision tasks. His accolades include: David Marr Prize (highest honor in computer vision) Koenderink Prize for fundamental contributions Helava Prize for photogrammetry Tsuji Award for pattern recognition ERC Advanced Grant for groundbreaking research Professor Van Gool drives technology transfer through 12 startups (assaia, Eyetronics, segments.ai, etc.) and major EU projects including ACTS Vanguard and Brite-Euram Soquetec. His labs maintain deep industry partnerships with automotive, medical imaging, and consumer electronics sectors, securing continuous funding for high-risk/high-reward research. Current grants emphasize embodied AI and real-world deployment challenges. The Computer Vision Laboratory at ETH Zurich and KU Leuven group operate as interconnected hubs with over 50 researchers. They maintain specialized facilities for 3D reconstruction, robotic vision, and multimodal sensing, recently expanded through industry partnerships. Current initiatives focus on embodied scene understanding for autonomous systems and vision-language models for industrial inspection.