Tahsin Abrar Nabil is an enthusiastic and smart engineer with hands-on experience in electrical engineering, academic research, and teaching. Currently, he serves as a Research Assistant and Faculty Member at Uttara University, contributing significantly to engineering education and research. His expertise spans sustainability, machine learning, and electrical system design, with a strong passion for innovation and academic excellence. Nabil completed his BSc in Electrical and Electronic Engineering (EEE) from Uttara University in 2021, earning a CGPA of 3.57 out of 4.00. During his academic journey, he actively engaged in research, student leadership, and technical competitions, securing the Dean Award (2019) and becoming the Champion of the Math Olympiad (2018). His research contributions include solar photovoltaic optimization, artificial intelligence in healthcare, and power system enhancements, with multiple publications in renowned journals and conferences. Currently, Nabil is a member of the Center for Clean Energy Research (CCER) at Uttara University and is actively involved in various departmental committees, including exam and routine management, program organization, alumni engagement, and research promotion. He also serves as an Adjunct Faculty in the Department of Textile Engineering at Uttara University, further expanding his impact on multidisciplinary education. Nabil’s professional experience extends beyond academia. He previously worked as a Trainee Engineer at KOZ Everfast Engineering (2021-2022), where he gained practical insights into engineering processes, substation installations, and power system operations. He also completed an industrial training program at Nexgen Power & Engineering Ltd (2019), focusing on transformer manufacturing and installation. These experiences have enriched his technical and problem-solving skills, making him a well-rounded professional in both industry and academia. His technical expertise includes electrical planning, CAD-based technical design, and industrial power system implementation. He is proficient in Python, MATLAB, AutoCAD, and Proteus, with a keen interest in machine learning, deep learning, and artificial intelligence applications in engineering. His research has been recognized through publications such as: A Hybrid Pre-Processing Technique for Stacking Ensemble with Random Forest as a Meta Classifier for Heart Disease Classification (Published in UU Journal of Science, Engineering & Technology). A Study on Different SVM Kernels with Suitable Preprocessing Technique and Parameter Optimization for Cardiovascular Disease Prediction (Under Review for BIM 2023). Optimizing Solar Photovoltaic Systems for Sustainable Energy in Academic Buildings: Environmental and Economic Perspectives (Submitted for ECCE – 2025). Early Detection of Heart Disease Using Machine Learning Algorithms (Submitted for ECCE – 2025). Beyond his academic and professional commitments, Nabil is deeply involved in mentorship, career development initiatives, and student counseling. He has served as the Chairperson of the IEEE Uttara University Student Branch, actively promoting technical knowledge sharing and innovation among students. Passionate about continuous learning, research, and sustainable development, Nabil aims to further explore machine learning applications in power systems and renewable energy technologies. With a strong foundation in academic leadership, electrical engineering, and interdisciplinary research, he is committed to making meaningful contributions to engineering education and innovation in Bangladesh and beyond.