جست‌وجوی استاد و پژوهشگر

Yan Zhuمشاهده پروفایل

پژوهشگر ارشد

• Photovoltaic systems
• Solar cell technology
• Semiconductor characterization
• +۳ مورد دیگر

Dr. Yan Zhu is a Research Fellow at the University of New South Wales (UNSW), affiliated with the School of Photovoltaic and Renewable Energy Engineering. She is currently part of the ACDC research team, focusing on advanced characterization techniques for photovoltaic materials and devices. Dr. Zhu holds a PhD in Photovoltaic Engineering from UNSW, complemented by international education including a Master's from École Polytechnique (France) and a Bachelor's from Shanghai Jiao Tong University. Her research specializes in photovoltaic systems and semiconductor characterization, with expertise in: Development of novel characterization methods for solar materials Defect analysis in silicon and semiconductors using photoluminescence Performance optimization of monocrystalline and multijunction solar cells Advanced metrology for photovoltaic device quality improvement Her publication portfolio demonstrates strong focus on photovoltaic innovation (60% of recent works), complemented by interdisciplinary contributions in computer vision applications for biometrics (25%) and medical imaging (15%). The research shows consistent emphasis on measurement accuracy, material reliability, and efficiency enhancement in renewable energy systems. Awards and Honors: Dean's Award for Outstanding PhD Theses (UNSW) Best Student Award - 7th World Conference on Photovoltaic Energy Conversion Steve Robinson Memorial Prize (UNSW) Dr. Zhu leads research within the ACDC photovoltaics characterization laboratory at UNSW, collaborating on projects developing next-generation solar cell diagnostic techniques. Her work bridges fundamental semiconductor research and industrial applications for renewable energy solutions.

• Biometrics
• Computer Vision
• Image Processing
• +۴ مورد دیگر

Prof. Dr. Önsen Toygar is a full Professor of Computer Engineering at the Faculty of Engineering, Eastern Mediterranean University. He holds a PhD in Computer Engineering from the same institution (2004). His primary research interests include Biometrics, Computer Vision, Image Processing, and Digital Forensics. He has over 18 years of academic experience, including roles as Vice Chair of the Computer Engineering Department and committee memberships in various university bodies. Education PhD in Computer Engineering, Eastern Mediterranean University (2004) MSc in Computer Engineering, Eastern Mediterranean University (1999) BSc in Computer Engineering, Eastern Mediterranean University (1997) Research Interests His work focuses on advanced biometric systems (e.g., face, ear, palm vein recognition), deep learning applications in medical imaging (e.g., Alzheimer’s/Parkinson’s disease classification), and robust feature extraction methods under occlusions/spoof attacks. Notable contributions include multimodal fusion techniques and anti-spoofing mechanisms for biometric security. Recent Publications Trends Recent work emphasizes deep learning in medical diagnostics (e.g., Alzheimer’s classification via 3D CNNs), multimodal biometric fusion (hand/finger vein recognition), and spoof detection in ear/facial systems. Cross-disciplinary efforts include plant disease detection and underwater image enhancement. Awards Publons Top Peer Reviewer (2019) EMU Research Incentive Awards (2017–2022) EMU Citation Awards (2017–2022) Best Paper Award (SIP2009) Grants & Supervision Directed over 30 graduate theses (PhD/MS) including projects on vein recognition systems, anti-spoofing methods, and disease classification. Active in research grants such as Deep Learning for Neurological Disease Diagnosis (2022–2023). Labs & Teams Leads the Biometrics Research Group focusing on multimodal systems, and collaborates with the Underwater Research and Imaging Center on image enhancement techniques.

• Forensic Genetics
• Population Genetics
• Ancient DNA Analysis
• +۳ مورد دیگر

Ronny Decorte is an Associate Professor at the Faculty of Medicine , KU Leuven , affiliated with the Department of Imaging & Pathology under the Forensic Biomedical Sciences unit. His research bridges forensic genetics , population genetics , and ancient DNA analysis , focusing on Y-chromosome evolution, familial kinship estimation, and post-mortem molecular processes. As Promotor of projects like 'An interdisciplinary mission to unravel historical mysteries through the Y-chromosome' (2025-2026) and 'The genetics behind historical socio-demography in Flanders' (2021-2025), Decorte integrates genetic data with historical narratives. His publications emphasize Y-chromosomal phylogeny , forensic DNA profiling , and microbiome applications in forensics . His contributions include developing tools like YMrCA for Y-ancestor time estimation and CSYseq for high-resolution Y-SNP/STR typing. He also explores post-mortem molecular dynamics (e.g., thanatotranscriptome DNA repair) and serves on institutional councils including the Faculty of Medicine Council and Biomedical Sciences Library Council .

Mazdak Zamaniمشاهده پروفایل

دانشیار

• Cybersecurity
• Artificial Intelligence
• Digital Watermarking
• +۵ مورد دیگر

Dr. Mazdak Zamani is an Associate Professor of Cybersecurity and Associate Dean of Computer Science and Cybersecurity at Felician University , NJ. He earned his PhD in Computer Science from Universiti Teknologi Malaysia in 2011. His research focuses on Cybersecurity and Artificial Intelligence , with publications spanning video watermarking , IoT authentication , mobile cloud security , and digital forensics . His recent work addresses heterogeneous device authentication and optimized steganography for secure data transmission. 2019 : Video watermarking performance evaluation, data mining for energy systems 2018 : LSB image steganalysis, spatial domain watermarking 2017 : Botnet forensics, illumination normalization for face recognition 2016 : Mobile cloud authentication, image/video watermarking techniques At Felician, he teaches Network Security , Digital Forensics , and Advanced Cryptography . Previously, he served as a Senior Lecturer at Universiti Teknologi Malaysia and as an Assistant Professor at Wenzhou-Kean University .

Xingjie Weiمشاهده پروفایل

دانشیار

• Business Analytics
• Unstructured Data Mining
• Social Computing
• +۱۲ مورد دیگر

Dr. Xingjie Wei is an Associate Professor in Business Analytics and Machine Learning at the Centre for Decision Research (CDR), Leeds University Business School, University of Leeds. Her research bridges data science and business management, focusing on understanding human behavior through unstructured data such as images, text, and digital footprints using machine learning and big data analytics. She leads and advises on multiple funded research initiatives and supervises PhD students in related areas. PhD in Computer Science, University of Warwick Research Associate, Psychometrics Centre, Cambridge Judge Business School, University of Cambridge Lecturer, University of Bath Visiting Researcher, National Lab of Pattern Recognition (NLPR), Chinese Academy of Sciences Her research interests include business analytics, unstructured data mining, social computing, human trait analysis, multimodal data, financial risk analytics, and initial coin offerings. She develops algorithms to extract psychological and behavioral insights from digital footprints, with applications in policy, finance, and public services. Her work emphasizes human-centered decision-making and service optimization. The recent publications reflect a strong trend in using machine learning to analyze human traits from visual and textual data, with applications in finance, marketing, and behavioral science. Topics include CEO image analysis, emotion from EEG, facial similarity in films, and tabular data visualization. Her work spans computer vision, affective computing, and behavioral finance, demonstrating interdisciplinary depth. Winner of the 2014 IGI Global's Excellence in Research Journal Award Published in Journal of Corporate Finance , IEEE Transactions on Affective Computing , Annals of Operations Research , and International Marketing Review Active editorial roles in Sensors and Discover Analytics Xingjie Wei has secured and led multiple research grants, including ESRC, Innovate UK, and LUBS Challenge Fund projects. She supervises PhD students and hosts postdoctoral researchers. Her collaborative work includes partnerships with SR Mailing, Katchr, KAIST, and interdisciplinary teams across Leeds. She actively mentors early-career researchers and contributes to academic service through reviewing, conference organization, and public engagement. She is involved in the Centre for Decision Research and leads projects on digital footprints for policy, climate change impacts, and AI-driven decision support. Her team includes current PhD students and research associates working on topics like credit risk, problem gambling, and life quality measurement. She promotes interdisciplinary collaboration and knowledge transfer between academia and industry.

• Biometrics
• Fingerprint Recognition
• Security Systems
• +۳ مورد دیگر

Raffaele Cappelli is an Associate Professor at the Department of Computer Science and Engineering, University of Bologna. His research focuses on fingerprint biometrics, emphasizing anti-spoofing, segmentation, and synthetic data generation. He contributes to the Fingerprint Verification Competition (FVC) and has pioneered tools like SFinGe for synthetic fingerprint databases. His work addresses security vulnerabilities in biometric systems and forensic applications. Education and affiliations include roles at the University of Bologna, with expertise in computer science and engineering. His research integrates machine learning, pattern recognition, and hardware acceleration to enhance biometric system performance and reliability. Key areas of study include presentation attack detection, fingerprint orientation estimation, and large-scale database management. He has authored over 70 publications, with notable contributions to forensic science and secure authentication protocols.

• Artificial Intelligence
• Biomedical Imaging
• Computer Vision
• +۵ مورد دیگر

Andreas Uhl is a University Professor in Artificial Intelligence and Human Interfaces at the Department of Computer Science, University of Salzburg. With a prolific research career spanning from 1996 to present, he has authored or co-authored 534 publications and led or participated in 59 research projects. His work demonstrates sustained academic productivity with recent publications and projects extending through 2025. Professor Uhl's research interests span multiple domains at the intersection of artificial intelligence and practical applications. His primary focus areas include computer vision, biometrics, biomedical imaging, and digital forensics, with significant contributions to pattern recognition and image analysis. His work bridges theoretical computer science with practical applications in cultural heritage preservation, medical diagnostics, and security systems, demonstrating a versatile research portfolio that addresses both fundamental challenges and real-world problems. His recent publications reveal a strong emphasis on temporal image forensics, biomedical image analysis, and biometric security. The research shows a clear trajectory toward increasingly sophisticated applications of AI in specialized domains, with particular attention to validation methodologies and limitations of current approaches. His work on cultural heritage applications demonstrates an innovative application of computer vision techniques to historical artifacts. Best paper award @ 25th ACM Symposium on Applied Computing (Applications Track), 2010 Best Paper award @ 2nd European Workshop on Visual Information Processing (EUVIP'10), 2010 IEEE Biometrics Council Best Paper Award (TBIOM), 2022 Kurt Zopf Preis, 2023 Professor Uhl actively leads multiple significant research initiatives, including the CDL-POSA project on People and Object Surface Authentication (2025-2032), Artificial Intelligence driven Biomedical Imaging Innovation (2025-2029), and the AIBIA Research and Transfer Junior Lab (2023-2025). His research group maintains active collaborations with institutions like Carnegie Mellon University, as evidenced by his recent research stay there in September 2024. The scope and duration of his current projects indicate substantial grant funding and institutional support for his research agenda. His laboratory activities focus on AI applications in biomedical imaging, border security through vehicle-integrated technologies (AutoBorder project), and cultural heritage analysis. The research environment appears to integrate academic inquiry with practical transfer through initiatives like the FFG Student Internships program, suggesting a strong commitment to both fundamental research and real-world implementation.

Serkan Özbayمشاهده پروفایل

دانشیار

• Electrical and Electronics Engineering
• Signal Processing
• Computer Vision
• +۴ مورد دیگر

Serkan Özbay serves as an Associate Professor in the Department of Electrical and Electronics Engineering at Gaziantep University's Faculty of Engineering, Turkey. With academic appointments since 2003, he progressed from Lecturer to his current position (2024), maintaining continuous affiliation with the institution where he also completed all his degrees. His career demonstrates deep institutional integration and vertical advancement within the same department. His academic credentials were entirely earned at Gaziantep University: Doctorate (2007-2015): Institute of Science, Electrical and Electronic Engineering Master's (2003-2006): Institute of Science, Electrical and Electronics Engineering (Thesis) Licence (1997-2002): Faculty of Engineering, Electrical and Electronics Engineering Özbay's research centers on signal processing and machine learning applications, with significant contributions to computer vision for medical diagnostics (sinus segmentation, lung cancer detection) and security systems (image/video forgery analysis). His work bridges theoretical algorithms with practical implementations in edge computing and biomedical devices, evidenced by projects like real-time fall detection systems and metamaterial antennas. Recent publications show intensified focus on deep learning since 2020, particularly convolutional neural networks for medical imaging and object tracking. His publication trajectory reveals strategic interdisciplinary expansion: early work (2007-2015) concentrated on spectrum sensing and wireless communications, while post-2020 output pivoted toward AI-driven medical applications and digital forensics. Approximately 70% of his 22 publications (2019-2023) involve deep learning implementations, with strong institutional collaboration patterns—85% co-authored with Gaziantep University researchers. Journal publications predominantly appear in Q2-Q4 SCI-indexed engineering journals, while conference papers target international venues in computer vision and biomedical engineering. As an academic advisor, Özbay has supervised 16 graduate theses (1 PhD, 15 Master's) between 2017-2025, with 11 completed in 2020-2023 alone. Current advisees include students developing Raspberry Pi-based plate recognition systems and real-time fall detection solutions. He additionally mentors 15 undergraduate students in senior design projects annually, as evidenced by 2024 EEE498/499 project meetings. Administrative leadership includes Deputy Head of Department (2016), Erasmus Coordinator (2015-2016), and Institute Board membership (2020-2023).

İbrahim Korkmazمشاهده پروفایل

استادیار

• Criminal Law
• Cyber Law
• Military Law
• +۳ مورد دیگر

İbrahim Korkmaz serves as an Assistant Professor in the Department of Criminal and Criminal Procedure at Beykent University's Faculty of Law, holding OrcID 0000-0002-5690-432X with contact email ibrahimkorkmaz@beykent.edu.tr. His academic career commenced in 2017 following doctoral completion after a 23-year tenure as a Military Judge at Turkey's Ministry of National Defense (1994-2017). Education: Doctorate in Law, Ankara University (2017) - Thesis: Protection of personal data within the scope of criminal law LLM in International Law (Military Law Specialty), The Judge Advocate General's School (2013) MSc, Gazi University (2007) - Thesis: Use of analytical hierarchy process in military personnel assignment MBA, Naval Postgraduate School (2005) - Thesis: Survival patterns of U.S. naval officers Law Degree, Dicle University (2002) - Thesis: The crime of money laundering Law Degree, Ankara University (1998) Military Academy, Turkish Army School Command (1994) Korkmaz's research centers on criminal law with specialized focus on cybercrime legislation, military interventions, and data protection frameworks. His work bridges legal theory and practical applications in digital forensics, counterterrorism operations, and privacy compliance, reflecting interdisciplinary expertise developed through military service and legal scholarship. Recent publications analyze Turkish cybercrime statutes and European data protection standards. His 2016-2018 publications demonstrate a clear trajectory toward contemporary digital legal challenges, particularly cybercrime mechanisms and data sovereignty issues. Earlier work (2008) reveals foundational expertise in military operations research, showing consistent thematic evolution from defense logistics to cyber warfare jurisprudence. Current conference presentations indicate expanding research into human trafficking and narcotics offenses within Turkish penal code. No scientific awards were documented in available materials. Since 2017, Korkmaz has supervised graduation theses while teaching 15+ annual courses including Criminal Procedure Law, Constitutional Law, and specialized seminars on cybercrime applications. His administrative duties at Beykent University include curriculum development for criminal law programs, though specific grant funding details were not disclosed.

• Computer Vision
• Image Analysis
• Machine Learning
• +۴ مورد دیگر

Dr Shahana Bano is a Lecturer in the School of Computing, Engineering & Technology at Robert Gordon University, specializing in interdisciplinary applications of Artificial Intelligence. Her research spans biomedical imaging, environmental monitoring, infrastructure analytics, and socio-technical systems through the Machine Vision Research Group and Cybersecurity Research Group. Her educational background includes a PhD in Computer Science and Engineering, M.Tech in Computer Science and Engineering, MSc in Information Systems, and BCA - all completed full-time. Her research philosophy centers on convergence, bringing together diverse data types, technologies, and disciplines to create impactful, adaptive systems that bridge academic innovation with societal relevance. Dr Bano's research interests focus on Computer Vision, Image Analysis, Machine Learning, Data Analytics, Internet of Things, Text to Speech Systems, and Social Media Threat Intelligence. Her recent work demonstrates strong application of these interests to medical diagnostics (CAR-T cell classification), environmental monitoring (geothermal reservoir modeling), infrastructure analytics (pipeline defect detection), and social systems (hate detection in football communities). Her publication record shows consistent output with 32 research outputs from 2015-2025, demonstrating increasing focus on medical and environmental applications of AI in recent years. The work spans theoretical computer vision advancements to practical implementations addressing UN Sustainable Development Goals. Associate Fellow (AFHEA) 2023 from Advance HE Dr Bano actively supervises PhD students and mentors interns on diverse projects. Current PhD supervision includes research on morphological classification of CAR-T cell images for leukemia diagnosis and acoustic emission-based pipeline defect detection. She also guides students on projects involving AR-based navigation, NDVI vegetation mapping, hate detection in football communities, multimodal sensor fusion, and airport runway object detection. Her lab resources are supported through university research groups and collaborations focused on machine vision and cybersecurity applications.

• Forensic Genetics
• Population Genetics
• Molecular Genetics
• +۳ مورد دیگر

Bo Thisted Simonsen serves as Deputy Director of the Section of Forensic Genetics within the Department of Forensic Medicine at the University of Copenhagen's Faculty of Health and Medical Sciences. With a career spanning over three decades at the institution, he has progressed from PhD student (1994-1997) to his current leadership role since 2007, contributing extensively to forensic genetics research and education. Education: PhD in Population Genetics (1997) MSc in Population Biology (1993) BSc in Ecology (1990) Simonsen's research centers on molecular markers for forensic identification of individuals and family relationships, ethnic identification, and the analysis of genetic variation in large terrestrial mammals. His work integrates population genetics, evolutionary biology, and ecology to understand patterns of genetic diversity and their historical origins, with direct applications in forensic science and conservation. Recent publications (2022-2025) demonstrate a strong focus on advancing forensic genetic methodologies, including accreditation standards (ISO/IEC 17025), contamination control in laboratories, nationwide criminal case analyses, and international relationship testing workshops. His research bridges human forensic applications and wildlife conservation genetics, particularly in primate populations. Scientific Awards: No specific awards are mentioned in the available information. As an educator, Simonsen teaches forensic genetics to medical students, biology students, and judicial personnel. He also delivers pre- and postgraduate instruction in evolution, population biology, and genetics. While specific grant details are not provided, his leadership in the Section of Forensic Genetics and active research output indicate significant institutional and collaborative funding support. Simonsen operates within the Section of Forensic Genetics at the University of Copenhagen, collaborating closely with the English Speaking Working Group of the International Society for Forensic Genetics. His work involves national forensic databases and international workshops, contributing to global standards in forensic genetic analysis.