Md. Shahariar Sarkar is a dedicated professional with a strong background in Computer Science and Engineering. He earned his B.Sc. degree from a prestigious institution in China, where he gained valuable international exposure and a global perspective on technology. His passion for learning and advancing his knowledge led him to pursue an M.Sc. in Computer Science at JU (Jahangirnagar University).
Md. Shahariar Sarkar's expertise spans a wide range of topics within computer science and engineering, including programming languages, software development methodologies, database management, Artificial Intelligence, Machine Learning, Deep Learning and more . He stays updated with the latest advancements in technology, integrating relevant industry trends into his teaching to prepare students for the challenges of tomorrow's digital landscape.
He has been actively involved in cutting-edge research projects throughout his career. His research contributions have been published in reputable conferences and journals, showcasing his commitment to advancing knowledge in his field. He has a strong analytical mindset and is skilled in applying theoretical concepts to solve real-world problems, making his research relevant and impactful.
In addition to his individual research endeavors, Md. Shahariar Sarkar is also passionate about collaborating with fellow researchers and industry professionals. He believes in the power of interdisciplinary collaboration and the exchange of ideas to drive innovation forward.
Beyond the classroom, Md. Shahariar Sarkar is known for his dedication to mentorship and supporting students in their academic and career pursuits. He believes in fostering a supportive learning environment that encourages curiosity, innovation, and collaboration among students.
Overall, Md. Shahariar Sarkar is a passionate educator and technologist committed to empowering the next generation of computer scientists and engineers with the skills and knowledge they need to succeed in a rapidly evolving technological world.
M. S. Sarkar, M. A. S. Lifat, R. Hasan and M. M. Hassan, "Discovering the Depths of Cotton Leaf Disease Detection: Integrating Hypertuned Residual Networks with GradCAM XAI for Enhanced Understanding and Diagnosis," doi:10.1109/ICAEEE62219.2024.10561737.
A Robust Deep Learning Based Hybrid Model to Detect Covid-19 Using Chest X-ray. Conference: 2nd International Conference on Big Data, IoT and Machine Learning (BIM 2023)
Comparative Evaluation of Structural Diffusion Tensor and Perfusion MRI for MGMT Methylation Prediction in Glioblastoma Using Deep Learning Approach. 27th International Conference on Computer and Information Technology (ICCIT 2024) [IEEE Conference ID: 64611]