Rashik Shahriar Akash | Composite Modeling | Best Researcher Award Posted on 18/11/202418/11/2024 by ScienceFather Rashik Shahriar Akash | Composite Modeling | Best Researcher Award Mr. Rashik Shahriar Akash, Health Informatics Research Lab, Bangladesh. Rashik Shahriar Akash is a motivated Computer Science student from Dhaka, Bangladesh, specializing in Artificial Intelligence (AI) and Machine Learning (ML). He currently serves as a Research Assistant at the Health Informatics Research Lab, focusing on Computer Vision, particularly in medical imaging. With a strong academic background and a passion for technology, Rashik is committed to developing cutting-edge AI solutions for real-world problems. He has contributed to multiple high-impact research papers in the fields of medical imaging, deep learning, and AI. Outside of academics, Rashik is actively involved in extracurricular activities and mentoring fellow students. Publication profile Scopus Orcid Googlescholar Education BSc in Computer Science and Engineering, Daffodil International University, Dhaka (CGPA: 3.93/4.00) HSC, Collectorate School & College, Rangpur (GPA: 4.83/5.00) SSC, Sundarganj Abdul Mazid Govt Boys High School (GPA: 5.00/5.00) Experience Research Assistant, Computer Vision, Health Informatics Research Lab, Dhaka (Jul 2024 – Present) Research Assistant, Computer Vision, Apurba-DIU Research and Development LAB, Dhaka (Apr 2023 – Jun 2024) Trainer, Advance Machine Learning and Deep Learning Bootcamp, DIU NLP & ML Research Lab, Dhaka (May 2023 – Dec 2023) Lab Prefect, Computer Science and Engineering, Daffodil International University (May 2022 – Dec 2022) Suitability For The Award Mr. Rashik Shahriar Akash is an exceptional candidate for the Best Researcher Award based on his strong academic background, extensive research experience, and demonstrated commitment to advancing the field of Artificial Intelligence (AI) and Machine Learning (ML). As a research assistant in the fields of Computer Vision and Health Informatics, he has contributed significantly to cutting-edge research projects, particularly in medical imaging and disease prediction. Professional Development Rashik Shahriar Akash has actively pursued opportunities for professional development throughout his academic journey. As a Trainer for the Advance Machine Learning and Deep Learning Bootcamp, he mentored students and enhanced his skills in machine learning frameworks such as TensorFlow and PyTorch. He has also collaborated on several cutting-edge research projects, published impactful papers, and has a strong focus on AI and computer vision in healthcare. His passion for learning and teaching has enabled him to refine his skills in AI and machine learning, particularly in medical applications. Research Focus Rashik’s research primarily focuses on the application of Artificial Intelligence and Machine Learning in the fields of medical imaging and computer vision. He has worked on innovative AI models, such as deep learning algorithms for medical diagnoses, including brain tumor detection and breast cancer prediction. His other areas of interest include computer vision-based solutions for polyp segmentation, cervical cell abnormalities, and taxonomic classification using DNA analysis. Through his work, Rashik aims to enhance the efficiency and accuracy of AI applications in healthcare, contributing to meaningful advancements in the field. Awards and Honors Level 2 (FE) passer of Information Technology Engineers Examination 2023 Performance-based scholarship at Daffodil International University (2020–2024) Government scholarship in Junior School Certificate Examination 2013 Government scholarship for High School Entrance Publications A Comprehensive Review on Family Budget Management (2023) – International Conference on Intelligent Computing & Optimization, 379-391 (Cited by 1) SAMU-Net: A Dual-Stage Polyp Segmentation Network with a custom attention-based U-Net and Segment anything Model for Enhanced Mask Prediction (2024) – Array, 100370 (Cited by 0) CerviXpert: A multi-structural convolutional neural network for predicting cervix type and cervical cell abnormalities (2024) – Digital Health, 10, 20552076241295440 (Cited by 0) A Review on the Impacts of Social Media on the Mental Health (2023) – International Conference on Intelligent Computing & Optimization, 181-195 (Cited by 0)