Frnaz Akbar | Neuroscience | Best Researcher Award

Dr. Frnaz Akbar | Neuroscience | Best Researcher Award

Dr. Frnaz Akbar, National University Of Modern Languages, Pakistan

Dr. Frnaz Akbar is a dedicated computer science and software engineering educationist, researcher, and web developer with over a decade of experience in teaching and web development. She has consistently contributed to building student knowledge in computer science and is committed to high-quality education. Her expertise spans artificial intelligence, data mining, precision agriculture, IoT, and blockchain. Dr. Akbar is currently pursuing a PhD in Artificial Intelligence at Air University, Islamabad, and has a strong publication record, including studies on deep learning, pattern recognition, and EEG-based Alzheimer’s research. She has worked as a lecturer at NUML University and held teaching positions at prestigious institutions. Her technical proficiency includes MERN, Python, C++, and ASP.Net. Recognized for academic excellence, she has received multiple honors, including a Best Teacher Trophy and High Achiever Scholarships. Passionate about research and innovation, she continues to contribute significantly to computer science and AI.

Publication Profile

Scopus

Education 🎓

Dr. Frnaz Akbar is currently pursuing a PhD in Artificial Intelligence at Air University, Islamabad, focusing on machine learning and deep learning applications. She holds an MS in Software Engineering (2018-2020) from Bahria University, Islamabad, and a Master’s in Information Technology (2015-2017) from PMAS ARID University, Rawalpindi, both with first-division honors. Her Bachelor’s in Computer Science (2013-2015) was completed at Punjab University, Lahore, where she received a Role of Honor Certificate. Additionally, she earned a B.Ed. (2020-2022) from Sarhad University, Islamabad Campus, further strengthening her educational expertise. Her academic journey began with HSSC and SSC from Islamabad College F-6/2, where she maintained outstanding academic performance. Throughout her education, she has demonstrated excellence, securing High Achiever Scholarships and academic awards. With expertise in AI, IoT, and software development, her education reflects a strong foundation in research, programming, and innovative computing technologies.

Experience 👩‍🏫

Dr. Frnaz Akbar has extensive experience in academia and industry, specializing in computer science and software engineering. She is currently a Visiting Lecturer at NUML University, Islamabad, in the Department of Software Engineering. Previously, she served as a Senior Computer Science Teacher at IMCG F-10/2 (2017-2023) and ISS, G-13/1, Islamabad (2013-2017), where she mentored students and designed curricula. She has also been a Computer Tutor at Allama Iqbal Open University since 2020, providing part-time instruction. In addition to teaching, she worked as a Software Developer at K-Soft, Ministry of Defense, focusing on MIS applications. With expertise in AI, IoT, and software development, she has contributed significantly to research and education. Her teaching philosophy emphasizes innovation and hands-on learning, ensuring students acquire both theoretical and practical skills. She is passionate about integrating emerging technologies into education and has a proven track record of academic excellence.

Awards and Honors 🏆

Dr. Frnaz Akbar has been recognized for her outstanding contributions to education and research. She received the Best Teacher Trophy from IMCG F-10/2, Islamabad, for her exemplary performance in student development and academic excellence. During her MS at Bahria University, she was appointed as a Teacher Assistant, reflecting her strong command over software engineering concepts. She secured a High Achiever Scholarship in every semester of her MSc IT at PMAS ARID University, Rawalpindi, showcasing her dedication to academic excellence. Her bachelor’s degree at Punjab University earned her a Role of Honor Certificate, highlighting her exceptional academic performance. In her early education, she was awarded a certificate for high attendance at IMCG F-7/2 and secured the second position in SSC. These accolades demonstrate her commitment to education, mentorship, and research, reinforcing her position as a leader in computer science and software engineering.

Research Focus 🔬

Dr. Frnaz Akbar’s research interests revolve around cutting-edge technologies in artificial intelligence and data science. She specializes in AI-driven applications, including deep learning, data mining, and pattern recognition. Her work extends to precision agriculture, where she leverages AI for optimizing crop health analysis. She is also actively engaged in research on the Internet of Things (IoT) and edge computing, focusing on real-time data processing. Blockchain technology and its integration with AI for secure computing systems form another critical aspect of her research. One of her notable contributions is in healthcare AI, particularly Alzheimer’s disease detection using EEG signal analysis. She has published and submitted multiple research papers on AI applications in medical diagnostics and agricultural automation. Her research is highly interdisciplinary, combining machine learning, neural networks, and computational modeling to solve real-world problems, making significant contributions to AI and software engineering domains. 🚀

Publication Top Notes

📖 Optimized Approach in Requirements Change Management in Geographically Dispersed Environment (GDE), International Journal of Foundations of Computer Science, 2020

🌿 Identifying Lesions in Cotton Leaves Unconstrained Images using Deep Neural Network, Computers in Biology and Medicine, 2023 (Under Review)

🧠 Unlocking the Potential of EEG in Alzheimer’s Disease Research: Current Status and Pathways to Precision Detection, Foundations and Trends in Machine Learning, 2024 (Under Review)

📊 Assessing the Effects of Alzheimer Disease on EEG Signals using the Entropy Measure: A Meta-analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 (Under Review)

Kiyohisa KAMIMURA | Neuroscience | Best Researcher Award

Assoc. Prof. Dr. Kiyohisa KAMIMURA | Neuroscience | Best Researcher Award

Assoc. Prof. Dr. Kiyohisa KAMIMURA, Kagoshima University Graduate School of Medical and Dental Sciences, Japan

Dr. Kiyohisa Kamimura is a renowned radiologist and Specially Appointed Associate Professor at the Department of Advanced Radiological Imaging, Kagoshima University, Japan. He holds an M.D. and Ph.D. from Kagoshima University, with over two decades of experience in radiology, including leadership roles such as Chief Radiologist at Kirishima Medical Center. Dr. Kamimura is a board-certified member of multiple prestigious radiology societies, specializing in advanced imaging techniques. His active research collaborations with Shin Nippon Biomedical Laboratories (SNBL) highlight his commitment to medical innovation. He is recognized for his expertise in neuroradiology and magnetic resonance imaging. 🌟📡

 

Publication Profile

Orcid

Education Journey

Dr. Kiyohisa Kamimura pursued his extensive medical education at Kagoshima University, Japan. He began with a premedical program (1992–1994) before advancing to an undergraduate degree in medicine (1994–1998). He further honed his expertise by completing an M.D. and Ph.D. at Kagoshima University Graduate School of Medical and Dental Science (2000–2008). His academic journey reflects a steadfast dedication to medical excellence and radiological research, laying the foundation for his impactful career in advanced imaging and radiology. 🩺📖

 

Professional Experience

Dr. Kiyohisa Kamimura has an illustrious career in radiology spanning over two decades. Starting at Kagoshima University Medical and Dental Hospital (1998–2000), he worked at several esteemed institutions, including Kagoshima Prefectural Oshima Hospital and Nanpuh Hospital. He served as Chief Radiologist at Kirishima Medical Center (2013–2014) and Assistant Professor at Kagoshima University (2014–2023). Currently, he is a Specially Appointed Associate Professor in the Department of Advanced Radiological Imaging at Kagoshima University. His roles demonstrate expertise in radiology and a commitment to advancing medical imaging technologies. 🌟📡

 

Research Focus

Dr. Kiyohisa Kamimura specializes in advanced radiological imaging, with a focus on brain and tumor imaging. His research includes time-dependent MRI diffusion for differentiating pituitary tumors, glioblastomas, brain metastases, and primary CNS lymphomas. He also explores MR amide proton transfer imaging and dynamic contrast-enhanced MRI for tumor evaluation. Dr. Kamimura’s work contributes significantly to neuroimaging, oncology diagnostics, and imaging biomarkers. His expertise extends to pancreatic ductal adenocarcinoma imaging and intravoxel incoherent motion studies in the pituitary gland, advancing precision diagnostics and treatment planning. 🌟🩺📈

 

Publication Top Notes 📚

 

  • Time‐dependent MR diffusion analysis of functioning and nonfunctioning pituitary adenomas/pituitary neuroendocrine tumors (2025) – DOI: 10.1111/jon.13254 🧠📅
  • Differentiating primary CNS lymphoma from glioblastoma by time-dependent diffusion using oscillating gradient (2023) – DOI: 10.1186/s40644-023-00639-7 🧠📈
  • Differentiating brain metastasis from glioblastoma by time-dependent diffusion MRI (2023) – DOI: 10.1186/s40644-023-00595-2 🧠🔍
  • Differentiation of hemangioblastoma from brain metastasis using MR amide proton transfer imaging (2022) – DOI: 10.1111/jon.13019 🩻🔬
  • Consistency of Pituitary Adenoma: Prediction by Pharmacokinetic Dynamic Contrast-Enhanced MRI (2021) – DOI: 10.3390/cancers13153914 🧠⚡
  • Visual enhancement pattern during the delayed phase of enhanced CT as a prognostic factor in stage IV pancreatic ductal adenocarcinoma (2020) – DOI: 10.1016/j.pan.2020.07.009 🩺✨
  • Large Intraosseous Schwannoma in Petrous Apex Presenting with Intratumoral Hemorrhage (2019) – DOI: 10.1016/j.wneu.2019.07.179 🦴🩹
  • Amide proton transfer imaging of tumors: theory, clinical applications, pitfalls, and future directions (2019) – DOI: 10.1007/s11604-018-0787-3 🔍💡
  • Intravoxel Incoherent Motion in Normal Pituitary Gland: Initial Study with Turbo Spin-Echo Diffusion-Weighted Imaging (2016) – DOI: 10.3174/ajnr.A4930 🧠🌀
  • Contrast-enhanced CT and diffusion-weighted MR imaging as prognostic factors in pancreatic ductal adenocarcinoma (2014) – DOI: 10.1016/j.ejrad.2013.12.016 🩻📊