# Md. Mehedi Hasan > CSE graduate and AI/ML researcher with experience in biomedical AI, medical imaging, brain MRI analysis, deep learning, graph based learning, and Explainable AI. My research interests span computational neuroimaging, medical AI, and computational modeling, with a growing focus on understanding complex biological and cognitive processes through machine learning. Role: AI Researcher & Engineer Location: Dhaka, Bangladesh Open to: MSc / PhD positions; Research collaboration; AI/ML engineering roles Contact: https://mdmehehedihasan.vercel.app/contact ## Research directions - [Computational Neuroimaging & Neuroscience](https://mdmehehedihasan.vercel.app/research/computational-neuroimaging-neuroscience): Exploring machine learning and computational modeling for neuroimaging and neuroscience, with an interest in understanding neural representations underlying cognition and emotion. - [Healthcare AI & Medical Imaging](https://mdmehehedihasan.vercel.app/research/healthcare-ai-medical-imaging): Developing machine learning and deep learning methods for medical image analysis, clinical decision support, and explainable healthcare AI. - [Bioinformatics & Graph-Based Learning](https://mdmehehedihasan.vercel.app/research/bioinformatics-graph-based-learning): Graph and transformer architectures applied to biological interaction data. Evidenced by X-GNN, published at IEEE ICECTE 2026, on human protein–protein interaction prediction. - [Explainable AI](https://mdmehehedihasan.vercel.app/research/explainable-ai): Making model decisions inspectable, which is a precondition for clinical use rather than an add-on. Evidenced by Grad-CAM in NeuroVision AI and RetinaVision AI, SHAP in the Parkinson's work, and "Explainable" in the title of the published paper. - [Data-Centric AI & Annotation](https://mdmehehedihasan.vercel.app/research/data-centric-ai-annotation): Dataset quality as the object of study rather than a preliminary step. Evidenced by the Data Annotation Analyst role at Rooya AI, the CVAT annotation portfolio, and dataset analysis work at AMIRL. ## Publications - [X-GNN: An Explainable Ensemble Graph–Transformer Framework for Human Protein–Protein Interaction Prediction](https://ieeexplore.ieee.org/document/11429277): 2026 5th International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE). 2026. published ## Projects - [DeshiA: Open-Source Image Annotation Workstation](https://mdmehehedihasan.vercel.app/projects/deshia): DeshiA is an open-source image annotation workstation designed for structured computer vision dataset creation. Inspired in part by CVAT, it provides a professional annotation workflow through both a web interface and a Tauri desktop application, with local filesystem storage and SQLite-based persistence. - [MedLoop AI: A Local Human-in-the-Loop Explainable Medical Imaging System](https://mdmehehedihasan.vercel.app/projects/medloop-ai): MedLoop AI is a fully local Human-in-the-Loop medical imaging research system that explores how validated human feedback can be incorporated into successive AI model versions. It combines medical image classification, explainable AI, interactive annotation, human validation, iterative retraining, and model versioning within a single workflow. - [Cardio Vision AI](https://mdmehehedihasan.vercel.app/projects/cardiovision-ai): A research prototype integrating trained AI models for echocardiography, CCTA, and 12 lead ECG analysis with explainability, evidence aggregation, and MedGemma assisted reporting. - [Tello AI Smart Learning Toy](https://mdmehehedihasan.vercel.app/projects/tello-ai-smart-learning-toy): An undergraduate IoT project that integrates ESP32-CAM based object detection, Edge Impulse machine learning, OLED visual feedback, and text-to-speech audio interaction into a portable interactive learning device. - [NeuroVision AI](https://mdmehehedihasan.vercel.app/projects/neurovision-ai): End-to-end deep learning system for three-class brain tumor classification using an ImageNet-pretrained EfficientNet-B0 model. - [RetinaVision AI](https://mdmehehedihasan.vercel.app/projects/retinavision-ai): End-to-end deep learning system for multi-label retinal disease classification, retinal vessel segmentation, and Grad-CAM explainability. - [CVAT Data Annotation & Computer Vision Portfolio](https://mdmehehedihasan.vercel.app/projects/cvat-data-annotation-portfolio): Practical CVAT annotation work across bounding boxes, polygons, segmentation, keypoints, and object tracking. - [Machine Learning Approaches for Early Detection of Parkinson's Disease](https://mdmehehedihasan.vercel.app/projects/parkinsons-disease-early-detection): Machine learning models for early Parkinson's disease detection from voice features. - [RecycleAPP](https://mdmehehedihasan.vercel.app/projects/recycleapp): Flutter-based Android application for recycling awareness and management with Firebase integration. - [Deshi Gadgets](https://mdmehehedihasan.vercel.app/projects/deshi-gadgets): Full-stack e-commerce website built on Java Servlets, JSP and Bootstrap with MySQL integration. ## Experience - Data Annotation Analyst, Rooya AI (current) - Research Assistant, Advanced Machine Intelligence Research Lab (AMIRL) (current) - Teaching Assistant, Department of CSE, BUBT - Research Intern, Advanced Machine Intelligence Research Lab (AMIRL) ## Education - Bachelor of Science in Engineering in Computer Science and Engineering, Bangladesh University of Business and Technology (BUBT) (CGPA 3.82 / 4.00) - Higher Secondary Certificate (H.S.C.), Begum Sheikh Fazilatun Nessa Mujib Govt. College (GPA 4.00 / 5.00) - Secondary School Certificate (S.S.C.), Parzowar Kalindi High School (GPA 4.11 / 5.00) ## Pages - [Home](https://mdmehehedihasan.vercel.app/) - [About](https://mdmehehedihasan.vercel.app/about) - [Research](https://mdmehehedihasan.vercel.app/research) - [Projects](https://mdmehehedihasan.vercel.app/projects) - [Publications](https://mdmehehedihasan.vercel.app/publications) - [Experience](https://mdmehehedihasan.vercel.app/experience) - [Education](https://mdmehehedihasan.vercel.app/education) - [Awards](https://mdmehehedihasan.vercel.app/awards) - [Certifications](https://mdmehehedihasan.vercel.app/certifications) - [Memberships](https://mdmehehedihasan.vercel.app/memberships) - [Referees](https://mdmehehedihasan.vercel.app/referees) - [Writing](https://mdmehehedihasan.vercel.app/blog) - [Research methods](https://mdmehehedihasan.vercel.app/skills) - [Technical stack](https://mdmehehedihasan.vercel.app/stack) - [Leadership](https://mdmehehedihasan.vercel.app/activities) - [Gatherings](https://mdmehehedihasan.vercel.app/gatherings) - [Contact](https://mdmehehedihasan.vercel.app/contact) ## Profiles - [Google Scholar](https://scholar.google.com/citations?user=uvPkYv4AAAAJ&hl=en) - [ORCID](https://orcid.org/0009-0009-0025-0062) - [IEEE Xplore](https://ieeexplore.ieee.org/author/108442987319016) - [ResearchGate](https://www.researchgate.net/profile/Md-Mehedi-Hasan-73) - [GitHub](https://github.com/0mehedihasan) - [LinkedIn](https://www.linkedin.com/in/0mehedihasan/) - [Kaggle](https://www.kaggle.com/mdmehedihasansr) - [Streamlit Community Cloud](https://share.streamlit.io/user/0mehedihasan) - [OpenTrain AI](https://app.opentrain.ai/profile/user-cmu5ke4z) - [X](https://x.com/mdmehedihasansr) - [Instagram](https://www.instagram.com/0mehedihasan) - [Facebook](https://www.facebook.com/mehedihasansr0) ## Optional - [Sitemap](https://mdmehehedihasan.vercel.app/sitemap.xml) - [Writing](https://mdmehehedihasan.vercel.app/blog)