جست‌وجوی استاد و پژوهشگر

Yuzhen Luمشاهده پروفایل

استادیار

• Optical Sensing
• Machine Vision
• Computer Vision
• +۸ مورد دیگر

Yuzhen Lu is an Assistant Professor in the Department of Biosystems & Agricultural Engineering at Michigan State University (MSU), with a joint appointment between the College of Agriculture & Natural Resources and College of Engineering. Before joining MSU in January 2023, he was an Assistant Professor at Mississippi State University (2020-2022) and a Postdoc Research Scholar with USDA-ARS and North Carolina State University. Dr. Lu earned his Ph.D. in Biosystems Engineering from Michigan State University in 2018. His academic journey reflects a strong foundation in engineering applications for agricultural systems, with a focus on bridging technological innovation with practical farming needs. Dr. Lu's research focuses on developing and deploying sensing and automation/robotics technologies for smart agriculture and food systems. His expertise spans optical instrumentation, machine/computer vision, image analysis, and applied machine learning. His work addresses critical challenges across the agricultural value chain, from in-field applications to postharvest processing, with particular emphasis on specialty crop production. His research integrates engineering principles with agricultural science to create practical solutions for real-world farming challenges. Analysis of Dr. Lu's recent publications reveals a strong trajectory in agricultural technology development, with emphasis on machine vision systems for quality assessment, precision agriculture applications, and robotics for agricultural tasks. His work shows increasing integration of advanced AI techniques with traditional engineering approaches to solve practical agricultural problems, particularly in specialty crop production, livestock monitoring, and food processing. Recognized among the World Top 2% Scientists based on Standford and Elsevier Data in 2025 Dr. Lu actively mentors a diverse team of graduate students, postdocs, and undergraduate researchers. His research is supported by multiple competitive grants from USDA-NIFA, MSU AgBioResearch, MDARD, and other funding agencies, totaling over $2 million in active funding. His projects range from developing vision-guided robotic systems for selective harvesting to non-destructive sensing technologies for food quality assessment, demonstrating both academic rigor and practical applicability. Dr. Lu leads a dynamic research laboratory focused on non-destructive sensing (machine vision, optical imaging, and spectroscopy) and automation/robotics technologies for addressing practical needs in agricultural systems. His team collaborates with industry partners, government agencies, and academic institutions to develop and transfer engineering solutions for smart and sustainable agriculture & food systems, with particular emphasis on specialty crop industries where labor shortages and quality demands create significant challenges.

• Image analysis
• Food quality assessment
• Granular mixture identification
• +۳ مورد دیگر

Dr. hab. inż. Piotr Zapotoczny, Professor at the University of Warmia and Mazury, specializes in Systems Engineering within the School of Technical Sciences. His research focuses on applying image analysis and hyperspectral imaging to evaluate food quality, particularly in agri-food products and granular mixtures. Scientific Discipline: Mechanical Engineering, Food and Nutrition Technology Email: zap@uwm.edu.pl ORCID: https://orcid.org/0000-0003-3051-6940 His work explores: Physical properties of biological materials Image analysis for food quality Drying technology for edible insects Optimization of agricultural processes His recent publications (2025–2017) show expertise in computer vision, hyperspectral imaging, and thermophysical analysis of agricultural products. Key subfields include granular mixture identification, fungal infection detection, and sustainable food processing techniques. He supervises doctoral projects in Polish but not foreign candidates, with laboratory infrastructure available for research tasks.

• Global Seismology
• Body Wave Seismic Imaging
• Ambient Seismic Noise
• +۷ مورد دیگر

Dr. Jenny Jenkins is an Assistant Professor in the Department of Earth Sciences at Durham University, specializing in deep Earth structure through seismic imaging techniques. Her research addresses fundamental questions about mantle convection, crustal formation, and core-mantle boundary dynamics using observational seismology. Education: PhD in Deep Earth Seismology, University of Cambridge (2013-2017) MESci Geophysics with Geology, University of Liverpool (2009-2013) Research Focus: Employing an observation-driven approach, Dr. Jenkins investigates seismic discontinuities, mantle plumes, and subduction zones. Her work integrates body wave seismic imaging , ambient noise analysis , and mineral physics to unravel Earth's structure from crustal to core-mantle boundary scales. Current projects target ultra-low velocity zones (ULVZs) and their role in planetary dynamics. Publication Trends: Recent work (2016-2025) shows evolving focus from Icelandic crustal studies to deep Earth heterogeneities, with increasing emphasis on ULVZ characterization near Hawaii. Her research bridges fundamental seismology with applied contexts like geothermal systems and infrastructure monitoring, demonstrating methodological innovation across geophysical subdisciplines. Scientific Recognition: 2018 Keith Runcorn Prize - Royal Astronomical Society PhD Thesis prize Mentorship & Service: Actively supervises graduate students while championing diversity through leadership in Durham's Earth Science EDI Group and the Unlearning Racism in Geoscience (URGE) initiative. Her departmental roles reflect commitment to inclusive geoscience practices and educational outreach. Ongoing Research: Developing advanced seismic imaging techniques to map ULVZ morphology at kilometer-scale resolution, with implications for understanding mantle thermochemical structure and core-mantle interactions.

MÜCAHİT Çalışanمشاهده پروفایل

مدرس

• Image Processing
• Machine Learning
• Biomedical Engineering
• +۲ مورد دیگر

Dr. MÜCAHİT Çalışan serves as a Lecturer at Bingöl University with dual appointments in the Computer Engineering Department (Faculty of Engineering and Architecture) and the Distance Education Application and Research Center. Holding a PhD from İnönü University (2022), he contributes to both teaching and research in computer engineering. His academic journey includes: Bachelor's Degree: Electronics and Computer Education, Fırat University (2003-2007) Master's Degree: Electronics and Computer Education, Fırat University (2011-2013) PhD: Computer Engineering, İnönü University (2016-2022) Dr. Çalışan's research centers on thermal imaging applications and machine learning techniques, with notable work in biomedical engineering such as skull thickness calculation using thermal analysis. His methodology combines finite element methods with image processing algorithms, extending to dimension reduction techniques and autoencoder optimization for coding performance. The evolution from thermal camera fundamentals (2011) toward biomedical applications (2021) demonstrates growing specialization. His publication portfolio shows consistent output with international reach, highlighted by the 2021 Applied Sciences article featuring cross-border collaboration. While specific grant details aren't public, the research trajectory suggests active projects in thermal imaging and machine learning applications. Teaching core courses including Database and Operating Systems, he bridges theoretical knowledge with practical implementation. Though no dedicated laboratory is documented, his computational research likely utilizes university resources for thermal analysis and machine learning experiments.

• Structural Health Monitoring
• Topology Optimization
• Polymer Processing
• +۳ مورد دیگر

Eric Monteiro is a Lecturer at École Nationale Supérieure d'Arts et Métiers (ENSAM) and Academic Director of the Master 1 Factory of the Future program. He is affiliated with the Laboratory for Processes and Engineering in Mechanics and Materials (PIMM), specifically within the DISCO research team focusing on Laser Processes. His research spans several key areas in mechanical engineering and materials science: Structural Health Monitoring : Developing advanced Lamb wave-based techniques for damage detection using signal processing and machine learning approaches Topology Optimization : Creating constrained natural element methods for stress and fatigue-constrained design optimization Polymer Processing : Modeling viscohyperelastic behavior in manufacturing processes like stretch blow molding Computational Mechanics : Developing novel numerical methods including hybrid twin approaches and meshfree techniques Laser Processes : Researching applications in materials processing and manufacturing His recent publications demonstrate a strong focus on computational methods development, with applications spanning structural optimization, wave propagation analysis, manufacturing process simulation, and material behavior modeling. This work consistently combines theoretical frameworks with experimental validation. As Academic Director, he oversees the Master 1 Factory of the Future program while maintaining an active research portfolio through PIMM laboratory, which provides access to experimental platforms for materials characterization and advanced manufacturing processes.

Jinki Kimمشاهده پروفایل

استادیار

• Smart Materials and Structures
• Sensors
• Structural Health Monitoring
• +۴ مورد دیگر

Jinki Kim serves as an Assistant Professor in the Department of Mechanical Engineering at Georgia Southern University, where he has been a faculty member since 2018. His research program bridges mechanical systems, materials science, and computational methods, with particular emphasis on experimental techniques for structural assessment and manufacturing processes. Professor Kim's academic credentials include a Ph.D. in Mechanical Engineering from the University of Michigan (2017), complemented by both M.S. and B.S. degrees in Mechanical and Aerospace Engineering from Seoul National University (2008 and 2006 respectively). His educational foundation supports his interdisciplinary research approach spanning mechanical systems and experimental dynamics. Research interests center on Smart Materials and Structures , Structural Health Monitoring , and Advanced Manufacturing , with specific expertise in video-based motion estimation, piezoelectric systems, and machine learning applications. His work demonstrates strong connections to piezoelectric engineering (81% fingerprint match) and structural health monitoring (51%), while contributing to UN Sustainable Development Goals in sustainable industrialization. Recent projects integrate deep learning with traditional engineering methods to solve practical problems in bioprinting and infrastructure assessment. Publication trends from 2023-2024 reveal significant focus on applying computational techniques to manufacturing and structural monitoring challenges. Five recent papers demonstrate consistent methodology using video-based vibration analysis combined with machine learning, particularly in bio-printing quality control and soil mechanics characterization. This work shows increasing interdisciplinary collaboration across mechanical, civil, and biomedical engineering domains. Professor Kim currently leads an active NSF grant ($500,000, 2023-2025) as Principal Investigator for bio-printed construct evaluation research. While specific student advising details aren't provided in the source material, his educational publication suggests active engagement in curriculum development for mechatronics and machine learning integration. His research group likely supports graduate students working on video-based monitoring systems and manufacturing applications. Though no formal lab name is specified, Professor Kim's research group focuses on experimental validation of structural systems using non-contact measurement techniques. The group's work combines mechanical testing with computational analysis, particularly in additive manufacturing quality assurance and structural health monitoring applications, utilizing video-based vibrometry as a core methodology.

Tova Ganzelمشاهده پروفایل

استاد

• Biblical Studies
• Jewish Studies
• Prophetic Literature
• +۵ مورد دیگر

Prof. Tova Ganzel is a Professor at the Multidisciplinary Department of Jewish Studies at Bar-Ilan University and Head of the Cramim Jewish Studies Honors Program. She previously served as director of the Midrasha – Institute for Advanced Torah Studies at Bar-Ilan University and is a certified women's halakhic advisor (yo'etzet halakha). Dr. Ganzel holds a Ph.D. in Bible from Bar-Ilan University. Her academic journey reflects deep commitment to both traditional Jewish learning and academic biblical scholarship, navigating the complex interface between religious faith and critical academic inquiry. Prof. Ganzel's research focuses on prophetic literature, ancient Near Eastern temples and second temple texts, the Jewish reception of biblical criticism from the eighteenth century to the present, and women as Halakhic Professionals. She has established herself as a leading scholar on Ezekiel's prophecies, particularly examining how his temple vision draws on Babylonian architectural elements. Her work bridges traditional religious belief and academic biblical scholarship, exploring how modern Orthodox Jews can engage with critical scholarship while maintaining religious commitments. Her publications demonstrate consistent focus on temple studies, Ezekiel's prophecies, and faith-criticism interface. Recent works examine Babylonian influences on Ezekiel's temple vision, discrepancies between Ezekiel's sacrificial system and the Torah, and broader implications of biblical criticism for religious believers. The trajectory shows increasing sophistication in addressing how religious communities can integrate academic insights without compromising faith. Among Prof. Ganzel's notable achievements: Recipient of the prestigious Tikvah Fellowship Author of multiple scholarly books including "Ezekiel's Visionary Temple in Babylonian Context" (2021), "Contextualizing Jewish Temples" (2020), "Ezekiel: From Destruction to Restoration" (2020), and "The Believer and the Modern Study of the Bible" (2019) Co-editor of "People of Faith and Biblical Criticism" (בעיני אלוהים ואדם: האדם המאמין ומחקר המקרא) Prof. Ganzel has created vital spaces for dialogue between religious scholars and academic Bible scholars. She co-organized a two-year seminar at Beit Morasha in Jerusalem (5772-5773/2012-2014) that brought together rabbis, Torah scholars, and academic Bible scholars. As a woman scholar in Orthodox Jewish settings, she has navigated unique challenges in establishing herself as a respected Bible scholar while maintaining traditional religious commitments. Her work has been particularly influential in helping Modern Orthodox believers reconcile faith with academic biblical scholarship.

Vesna Zeljkovicمشاهده پروفایل

استاد

• Signal Processing
• Image Processing
• Medical Diagnostics
• +۴ مورد دیگر

Vesna Zeljkovic serves as a Professor in the Chemistry & Physics Department at Lincoln University, where she applies her expertise in signal and image processing to develop mathematical models and novel algorithms for medical applications. Her office is located in the Ivory V. Nelson Science Center Room 334, and she can be reached at vzeljkovic@lincoln.edu or by phone at 484-365-7258. Professor Zeljkovic's research spans multiple interdisciplinary domains with a strong focus on medical diagnostics. Her work integrates advanced signal processing techniques with clinical applications, particularly in cardiopulmonary analysis and dermatological imaging. She has developed numerous algorithms for medical image analysis, sound signal processing, and diagnostic classification systems that bridge physics, engineering, and medical science. Her publication record demonstrates a consistent research trajectory from 2003 through 2025, with recent work focusing on vaccination effectiveness quantification, dermatological condition assessment, and advanced cardiopulmonary signal analysis. The articles reveal a methodological trend toward increasingly sophisticated machine learning applications while maintaining strong foundations in mathematical modeling and signal processing theory. While specific awards are not documented in the available materials, her extensive publication record across medical and engineering disciplines indicates significant scholarly contributions. Her research appears to focus on practical applications of signal and image processing to solve real-world medical diagnostic challenges across multiple specialties. Professor Zeljkovic's work demonstrates strong interdisciplinary collaboration, particularly between physics, engineering, and medical fields. Her research group appears to focus on developing computational tools for medical diagnostics, with particular emphasis on non-invasive assessment techniques using signal and image analysis.

Jeffrey Dellosaمشاهده پروفایل

استاد

• Renewable Energy
• Solar Photovoltaics
• Energy Engineering
• +۲ مورد دیگر

Jeffrey Dellosa serves as a Professor at Caraga State University in the College of Engineering and Geosciences, Butuan, Philippines. His academic career focuses on renewable energy research with particular emphasis on solar photovoltaic systems for rural development applications in the Philippines. He holds a Doctor of Engineering degree specializing in Renewable Energy from Ateneo de Davao University (2019-2023). Education: Doctor of Engineering in Renewable Energy, Ateneo de Davao University (2019-2023) Professor Dellosa's research spans multiple domains within renewable energy engineering, with particular expertise in solar photovoltaics, energy conversion systems, and power generation technologies. His work bridges theoretical research with practical applications for rural electrification and sustainable development. Current research directions include floating solar photovoltaic systems, IoT-based energy monitoring, and renewable energy integration for healthcare facilities. Analysis of his publication record reveals a strong emphasis on practical implementation of renewable energy solutions in the Philippine context, with increasing focus on interdisciplinary approaches combining AI, IoT, and traditional energy engineering. Recent publications demonstrate a shift toward comprehensive system design that addresses both technical and socioeconomic aspects of renewable energy deployment in rural communities. Professor Dellosa leads research in Nelson Jr Enano's Lab and collaborates extensively with regional institutions on renewable energy projects. His work has resulted in 67 publications with significant readership (60,773 reads) and citations (286 citations), demonstrating impactful contributions to the field of renewable energy engineering in Southeast Asia.

Andreas Hennigمشاهده پروفایل

استاد

• Biomedical Sensors
• Wireless Sensor Networks
• Inductive Sensing
• +۴ مورد دیگر

Prof. Dr. Andreas Hennig is a Professor of Medical Sensor Systems at the Institute of Measurement and Sensor Technology, Ruhr West University of Applied Sciences since 2022. He serves as Program Director for the Master's program in Sustainable Health Technologies and previously held leadership roles at Fraunhofer IMS from 2006-2022 as Group Leader for Wireless Sensorics and Program Manager for Sustainable Production. He earned his Master of Science in Electrical Engineering from Bergische Universität Wuppertal (2001-2006) and completed his PhD at the University of Duisburg-Essen (2006-2009) on optimizing transmission methods for implantable telemetry sensor systems. His research pioneers non-contact sensing through inductive techniques, quantum magnetometry, and machine learning for medical diagnostics (neonatal vital monitoring, biomagnetic sensing), Industry 4.0 applications (predictive maintenance, sustainable production), and Smart City infrastructure. Current projects focus on quantum sensors for electromagnetic tracking and inductive methods for industrial process monitoring in steel manufacturing. Publications reveal an evolution from biomedical wireless sensors (2010-2015) toward industrial quantum sensing (2018-2024), with recent work emphasizing microscale electromagnetic tracking and magnetic property evaluation in hot-rolling mills. Prof. Hennig supervises theses on vital parameter monitoring for newborns, quantum biomagnetic sensing, and sustainable industrial process monitoring. He has secured funding for projects including SmartNeonatalCare, GenSATIon-EDGE, INNERVATE, and FabLab collaborations (QuFabLab, QuMiniLabs), demonstrating strong grant acquisition capabilities. He directs the LASIMM research laboratory equipped for PCB prototyping (reflow/SMD assembly), 3D printing, and advanced measurement (Impedance/Network Analyzers). His team comprises six scientific staff members including Anika Nietert, Christine Bremer, and Thomas Thuilot, supporting both academic research and student projects.

Jun Wangمشاهده پروفایل

استادیار

• Civil Engineering
• Structural Engineering
• Infrastructure Sustainability
• +۴ مورد دیگر

Jun Wang is an Assistant Professor in the Department of Civil, Environmental, and Construction Engineering at the University of Hawaii at Manoa since 2024. His research advances infrastructure sustainability through simulating multi-hazard infrastructure behavior, machine learning for structural health monitoring, and innovative repair techniques using advanced materials. His educational background includes: Ph.D. in Civil Engineering from the University of Colorado, Denver (2020) M.S. in Civil Engineering from the University of Colorado, Denver (2014) B.S. in Civil Engineering from Northeast Forestry University (2014) Dr. Wang specializes in structural engineering with emphasis on infrastructure resilience under seismic and fire events, CFRP/UHPC strengthening systems, and machine learning applications for structural assessment. His work bridges computational modeling with experimental validation to enhance infrastructure longevity and sustainability, particularly in bridge engineering and concrete technology. Analysis of his 13 recent publications (2019-2024) reveals dominant research streams in ultra-high performance concrete (UHPC) behavior, fiber-reinforced polymer (CFRP) strengthening systems, and machine learning applications for recycled concrete and crack detection. Key interdisciplinary themes include multi-hazard resilience, sustainable materials, and computational structural analysis, with strong industry relevance to bridge engineering standards. His scientific awards include: BEI-2023 Rome, Italy Travel Fellowship (2023) Outstanding Presentation Award at the 1st Annual Symposium of TriDurLE Rocky Mountain Section Society of Women Engineers Scholarship (Pioneer, 2020) Rocky Mountain Chapter American Concrete Institute Graduate Scholarship (2017) Dr. Wang actively contributes to the academic community as a reviewer for the Journal of Materials in Civil Engineering (ASCE), American Concrete Institute journals, Structures, Materials & Design, and Journal of Cleaner Production. He serves on the Diversity, Equity, and Inclusion Committee of the Bridge Engineering Institute (BEI) and teaches CEE 381: Structural Analysis at the University of Hawaii.