جستجوی استاد راهنمای دانشگاهی

• Materials Science
• Nanomaterials
• Optoelectronics
• +۷ مورد دیگر

Abdullah A. A. Ahmed is an Associate Professor in the Department of Physics at Thamar University, Yemen. He earned his Ph.D. from Universiti Putra Malaysia (UPM) in 2012 and served as a postdoctoral fellow there before returning to Yemen in 2013. He has been actively contributing to materials science research, particularly in nanomaterials, optoelectronics, energy storage, and hydrogen storage applications. Ph.D.: Universiti Putra Malaysia (UPM), 2012 Postdoctoral Fellowship: Universiti Putra Malaysia Appointment: Assistant Professor, Thamar University (2013) Promotion: Associate Professor (2019–2020) Dr. Ahmed's research spans advanced materials for energy and medical applications. His work includes the development of biopolymer electrolytes for supercapacitors, DFT studies on perovskite materials, photocatalytic nanocomposites, and nanomaterials for anticancer therapy. He frequently employs techniques such as co-precipitation, electrodeposition, and spectroscopic analysis. His recent publications (2021–2025) show a strong trend toward sustainable energy materials, including hydrogen storage in perovskite hydrides, supercapacitors using biopolymers, and photocatalytic nanocomposites for environmental remediation. There is also a growing interest in biomedical applications of nanomaterials and brain interfacing technologies. Dr. Ahmed serves as a Review Editor for Frontiers in Chemistry in the field of Medicinal and Pharmaceutical Chemistry, contributing to peer review and academic discourse. He has advised graduate students such as Annas Al-Sharabi and Ahmed Al-osta, both affiliated with Thamar University. While no specific grants are mentioned, his extensive publication record suggests active research funding and collaboration. His work is conducted within a collaborative network involving researchers from Malaysia, Saudi Arabia, India, and other international institutions, focusing on cutting-edge materials for energy, environment, and health applications.

• Brain-Computer Interfaces
• Data Mining
• Artificial Intelligence
• +۲ مورد دیگر

Robertas Damaševičius serves as a Professor at Vytautas Magnus University's Department of Applied Informatics within the Faculty of Informatics. Holding a Doctor of Sciences degree, he maintains active academic engagement at the institution. His research expertise spans critical domains in modern computing: Brain-Computer Interfaces Data Mining methodologies Artificial Intelligence applications Digital Signal Processing techniques Physiological Computing systems Professor Damaševičius supervises advanced research in applied informatics, with recent Master's theses focusing on nature-inspired recommendation algorithms, convolutional neural networks for industrial defect detection, and innovative approaches to zero-day cyberattack prevention. His academic supervision bridges theoretical computer science with practical implementations across multiple industries. Professional academic profiles: ORCID: 0000-0001-9990-1084 Scopus Author ID: 6603451290 Researcher ID: E-1387-2017 Google Scholar: N9ZrcVIAAAAJ&hl

• Medical Image Analysis
• Machine Learning
• Computer Vision
• +۵ مورد دیگر

Dr. Jolita Bernatavičienė serves as a Senior Researcher at Vilnius University's Institute of Data Science and Digital Technologies within the Image and Signal Analysis Group. With a Doctorate in Technological Sciences (Informatics), she has established herself as a leading researcher in medical image analysis and artificial intelligence applications in healthcare. Her extensive research portfolio spans over 15 years of continuous contributions to the field. Dr. Bernatavičienė's research interests primarily focus on medical image analysis, particularly in ophthalmology and oncology applications. Her work integrates advanced machine learning techniques with medical diagnostics, specializing in eye fundus image analysis for glaucoma detection and prostate MRI analysis for cancer identification. She has made significant contributions to deep learning architectures, signal processing methodologies, and data analysis frameworks applicable to biomedical challenges. Her publication record demonstrates strong trends in applying cutting-edge AI techniques to solve concrete medical problems, with a noticeable shift toward more sophisticated deep learning architectures in recent years. The research spans multiple medical domains including ophthalmology, cardiology, oncology, and renewable energy systems monitoring, reflecting her interdisciplinary approach to data science applications. Leader of International Conference 'Data Analysis Methods for Software Systems (DAMSS)' 2015-2024 Member of IEEE Computer Society section (since 2022) Member of the Council of the Lithuanian Computer Association, Artificial Intelligence Section Member of the Lithuanian Operations Research Society Expert at the Science, Innovation and Technology Agency (MITA) (2020-2022) Dr. Bernatavičienė actively supervises doctoral and master's students, with current doctoral student Roman Surkant working on prostate MRI analysis. She leads multiple significant research projects including 'Developing Talents in Artificial Intelligence to Solve Disruptive Environmental Problems' and serves as scientific leader for the Research Council of Lithuania funded project on cardiac MRI texture analysis. Her work has been supported by various national and international funding mechanisms including COST activities, EuroHPC programs, and Lithuanian national research grants. She is principal investigator for the long-term project developing a database of depersonalized fundus images (2018-2030) and has led numerous projects related to medical image analysis, AI applications in healthcare, and data science methodologies. Her research group maintains strong international collaborations through COST actions and other European research networks.