Mr. Nadeem Zaidkilani | Artificial Intelligence | Cutting-edge Technology Research Award

Mr. Nadeem Zaidkilani, University Rovira i Virgili, Spain

Mr. Nadeem Zaidkilani is a Ph.D. student in the Doctoral Program in Computer Engineering and Mathematics at the University Rovira i Virgili (URV), Spain. His research focuses on computer vision and medical image analysis, leveraging deep learning techniques to enhance automated diagnostic systems. With a strong background in software engineering and artificial intelligence, he has extensive experience in text mining, natural language processing, and biomedical data analysis. His work integrates advanced machine learning methodologies with practical applications in healthcare and technology.

Profile

Scopus

🎓 Early Academic Pursuits

Nadeem Zaidkilani embarked on his academic journey with a passion for computer science, earning his Bachelor’s degree in Computer Science from Birzeit University in 2005. His thirst for knowledge and drive for excellence led him to further his studies, culminating in a Master’s degree in Software Engineering from the same institution in 2019. During his master’s, he honed his expertise in requirements engineering, business analysis, software design, and other fundamental software engineering disciplines. His thesis on Automatic Classification of Apps Reviews for Requirement Engineering provided significant insights into customer needs in healthcare applications, demonstrating his analytical skills and research prowess.

Currently, Nadeem is pursuing a Ph.D. at URV University in Spain, specializing in Computer Vision for Medical Image Analysis. His research integrates deep learning, image processing, and natural language processing (NLP) to develop advanced solutions in medical imaging.

💼 Professional Endeavors

Throughout his career, Nadeem has gained extensive experience in various roles, each contributing to his growth as a seasoned software engineer, researcher, and educator.

🌟 Part-Time Lecturer at Al-Zaytoonah University of Science and Technology (2024–Present)

Nadeem’s teaching portfolio includes courses in Python, C++, and Human-Computer Interaction (HCI). His expertise extends to Agile and Scrum methodologies, emphasizing collaborative design, iterative feedback, and efficient software development cycles. His commitment to academia ensures that students receive industry-relevant knowledge and skills.

🧪 Text Mining Engineer (2023–2024)

Nadeem played a pivotal role in a biomedical research project, leveraging text mining to streamline the classification of PubMed literature. His contributions included:

Text Classification: Implementing advanced algorithms to categorize biomedical research papers.
Entity Relationship Mapping: Utilizing INDRA to identify connections between biomedical entities.
Workflow Development: Designing a student-teacher analogy model, where experts guide AI-driven literature analysis.

🛠️ Senior Application Specialist at Paltel (2012–2022)

In this role, Nadeem managed and optimized multiple business applications, ensuring seamless integration and high efficiency. Key projects included:

Paltel Portal & Business Portal: Facilitating customer and corporate service management.
Electronic Document Management System (EDMS): Enhancing document storage and retrieval processes.
E-Pay System: Implementing a secure electronic payment solution.
Vendor Management System (VMS): Streamlining vendor relations.
Bulk and Pull SMS System: Enhancing customer communication strategies.

🏆 Senior Software Developer at Hulul Company (2009–2012)

Nadeem worked on network provisioning, donor management systems, and document archiving while implementing Agile methodologies. His experience with Struts 2, JEE, HTML, and JavaScript strengthened his software development capabilities.

📝 IT Manager at Ministry of Finance (2007–2009)

As an IT manager, he successfully led projects within budget and time constraints, ensuring efficient system analysis, testing, and quality assurance.

📚 Junior Java Developer & Software Engineer Roles (2005–2007)

Nadeem contributed to the Palestinian Authority Tax Administration Computer System (PATACS), implementing J2EE-based solutions. His training in Spain on J2EE and XML web services further solidified his technical foundation.

📚 Contributions and Research Focus

Nadeem’s research is centered on deep learning, computer vision, and medical image analysis. His ongoing Ph.D. work aims to revolutionize medical imaging techniques by integrating AI-driven models. His past research efforts in text mining for biomedical literature and software requirement engineering have also contributed valuable insights to their respective fields.

🏅 Accolades and Recognition

Nadeem’s expertise has earned him recognition across academic and professional spheres. His extensive contributions to biomedical text mining, software engineering, and AI-driven medical imaging have established him as an innovator in the field. He has collaborated with leading experts and institutions, further solidifying his influence in software development and research.

Publication Top Notes

CoAtUNet: A symmetric encoder-decoder with hybrid transformers for semantic segmentation of breast ultrasound images

Author: N., Zaidkilani, Nadeem, M.Á., García, Miguel Ángel, D.S., Puig, Domenec Savi

Journal: Neurocomputing,

Year: 2025

Mr. Morteza Karimian Kelishadrokhi | Artificial Intelligence | Best Researcher Award

Deep Learning Researcher at Islamic Azad University (IAU) Najafabad Branch, Iran.

Morteza Karimian Kelishadrokhi is a distinguished researcher specializing in artificial intelligence and data science, holding a master’s degree in Artificial Intelligence from Islamic Azad University (IAU), Najafabad Branch, Iran. He excels in deep learning, focusing on EEG signal analysis and time series classification. Morteza is recognized for his development of advanced neural network architectures, including memory-augmented models, to enhance the classification of brain activities. His research extends to signal processing and computer vision, where he explores novel techniques for content-based image retrieval and real-time data analysis. Morteza’s contributions significantly advance AI methodologies, impacting both academic research and practical applications across various industries. His dedication and expertise position him as a key figure in the field, bridging theoretical advancements with tangible solutions in artificial intelligence and data-driven technologies.

Professional Profiles:

Education

Morteza Karimian Kelishadrokhi holds a Master of Science in Artificial Intelligence from the Islamic Azad University (IAU), Najafabad Branch, Iran, graduating in 2024. He excelled academically, achieving first place among students of the computer faculty with an outstanding GPA of 19.42 out of 20.00. His dedication and excellence were recognized by the dean, who honored him as the “Top Scientific Student.” Morteza also holds a Bachelor of Science in Computer Science from the same institution, graduating in 2021. During his undergraduate studies, he secured first place in the academic year 2019-2020 and second place in 2018-2019. Additionally, he served as a Teaching Assistant for the “Deep Learning Course” in both the Fall and Winter semesters of 2021 and 2022. Morteza’s educational journey highlights his exceptional academic performance and strong focus on artificial intelligence and deep learning.

Professional Experience

Morteza Karimian Kelishadrokhi is a Deep Learning Researcher and Senior Data Analyst at the Islamic Azad University (IAU), Najafabad Branch, Iran. He coordinates with industries and participates in workshops, such as the “Application of Deep Learning in the Industry.” Morteza has contributed to various research projects, including the development of a Security Framework for AI-Enhanced Microarchitectural Analysis and a Multi-Class EEG Brain Activity Classification system using the TD-MANN architecture. He has served as a Teaching Assistant for the “Deep Learning Course” in the Fall and Winter semesters of 2021 and 2022, where he designed course materials and assisted students with projects. Morteza’s work also extends to consultancy and industry projects, applying his expertise in AI, machine learning, and data analytics to solve real-world problems. His professional journey is marked by innovative research and practical applications in artificial intelligence.

Research Interest

Morteza Karimian Kelishadrokhi’s research interests span several cutting-edge domains within artificial intelligence and data science. He is particularly focused on deep learning, exploring its applications in time series classification and EEG signal analysis. His work aims to develop advanced neural network architectures, such as memory-augmented neural networks, to improve the classification of brain activities. Additionally, Morteza is interested in signal processing and computer vision, seeking innovative solutions for content-based image retrieval and real-time data analysis. His research contributes to the advancement of AI methodologies and their practical implementation in various scientific and industrial applications.

Award and Honors

Morteza Karimian Kelishadrokhi has received multiple accolades for his academic excellence and contributions to the field of artificial intelligence. In 2022, he was honored and awarded by the dean of the Islamic Azad University, Najafabad branch, as the “Top Scientific Student.” He secured the 1st place position in the academic years 2019-2020 and 2018-2019, and 2nd place in the academic year 2018-2019. Additionally, Morteza has served as a teaching assistant for the “Deep Learning Course” during the winter semester of 2022 and the fall semester of 2021. He also played a key role in coordinating with industries and participating as a speaker in the workshop “Application of Deep Learning in the Industry” in 2022.

Research Skills

Morteza Karimian Kelishadrokhi possesses a diverse skill set in research methodologies and advanced data analysis. His expertise includes developing and implementing deep learning models, particularly for EEG signal classification and time series analysis. He is proficient in designing neural network architectures, including memory-augmented neural networks, and applying machine learning algorithms to solve complex problems. Morteza is skilled in signal processing techniques and has experience with computer vision applications, such as content-based image retrieval. His research capabilities extend to conducting comprehensive literature reviews, data preprocessing, and statistical analysis, ensuring the integrity and reliability of his findings. Additionally, he is adept at using various programming languages and tools essential for AI research, including Python, TensorFlow, and MATLAB.