Trustworthy health-AI research and full-stack AI engineering
Peer-reviewed methods for leakage-aware, calibrated clinical-risk modeling—and production RAG, agentic systems, and MCP-backed platforms. Interested in a funded Ph.D. in CS / health informatics.
Academia · Health AI researchPh.D. · Funded researchIndustry · Full-stack AI
I work across academic research and industrial engineering: leakage-aware, calibrated, explainable methods for EHR risk and medical imaging, and grounded RAG and agent platforms in production.
As a Senior Full Stack Engineer at Volkswagen Group of America, I deliver LangChain/LangGraph retrieval systems, multi-step agents, MCP tool wiring, LangSmith tracing, chat assistants, and task automation on Spring Boot and Angular platforms.
Independently, I publish peer-reviewed health-AI work, maintain the open EHR Risk Framework, and serve as a peer reviewer—including Web of Science–verified journal reviews. That scholarly record is separate from employer product ownership.
Healthcare methods are research and education only—not a medical device and not bedside deployment.
Research
Health AI methods & open software
Agenda: honest temporal evaluation of EHR and imaging models—index-time contracts, patient-level splits, calibration, and SHAP—released as papers and inspectable tools.
Artificial Intelligence in Healthcare: Early Disease Detection and Clinical Risk Prediction from Electronic Health Records — lead author, First Edition 2026.
Harithpatra Prokashon, Dhaka · ISBN 978-984-29284-1-3
Doctoral research interests
I am interested in a funded Ph.D. focused on trustworthy clinical prediction from real-world health data. Proposed dissertation anchor:
How much do leakage and miscalibration inflate reported performance in EHR risk studies—and can automated index-time audits plus calibration benchmarks reduce that inflation on credentialed cohorts?
Temporal integrity / leakage audits for EHR risk models
Probability calibration and reliability under shift
Open, reproducible research software for multi-site evaluation
Selected work first. Author roles match publisher lists. Full indexed record: Google Scholar.
Selected
Co-author Asad, M., Khan, M., Hossain, M.R., et al. CRuSE-Heart: Explainable AI for Risk-Controlled Selective Ensembles in Heart-Attack Screening. Discover Artificial Intelligence (Springer Nature), 2026. doi:10.1007/s44163-026-01378-x
First authorHossain, M.R. et al. Hybrid Deep Learning Framework for Knee Osteoporosis Diagnosis Using CNNs and Fine-Tuned Multimodal Large Language Models. ICSADL, IEEE, 2026. doi:10.1109/ICSADL67539.2026.11451868
Lead authorHossain, M.R.Artificial Intelligence in Healthcare: Early Disease Detection and Clinical Risk Prediction from Electronic Health Records. First Edition, Harithpatra Prokashon, 2026. ISBN 978-984-29284-1-3.
Co-author Early Diagnosis of Diabetic Retinopathy Through AI-Based Optimized Ensemble Classification. ICARC, IEEE, 2026. doi:10.1109/ICARC68737.2026.11453518
Co-author Optimizing Transfer Learning: A Deep Learning Approach for High-Accuracy Classification of Alzheimer’s Disease Stages. AISEI, IEEE, 2026. doi:10.1109/AISEI68628.2026.11572889
Additional peer-reviewed
Co-author Advancing Public Safety with Real-Time Life Jacket Detection and Demographic Profiling Using YOLOv8 and Age Classification. EAI Endorsed Transactions on AI and Robotics, 2025. doi:10.4108/airo.9785
Co-author Enhanced Colorectal Cancer Image Classification Using a Custom Deep Convolutional Neural Network. ICSADL, IEEE, 2026. doi:10.1109/ICSADL67539.2026.11452002
Co-author Hybrid Vision Transformer and CNN Architectures for Multi-Class Classification in Gastrointestinal Endoscopy. AISEI, IEEE, 2026. doi:10.1109/AISEI68628.2026.11572866
Co-author Revolutionizing Drug Discovery: A Systematic Review of AI and Machine Learning Application. ICSSAS, IEEE, 2025. doi:10.1109/ICSSAS66150.2025.11081368
Co-author Bangladeshi License Plate Detection and Recognition Using YOLO Variants and Enhanced OCR. RTIP2R, Marrakech, 2025.
Co-author Transparency in Fabric Defect Detection by Leveraging Explainable AI. RTIP2R, Marrakech, 2025.
Co-author Image Recognition for Early Diagnosis and Prognosis of Alzheimer’s Disease Using Multimodal Brain Imaging. ICEFronT 2026. Accepted (DOI forthcoming).
Under review
FWC-TabXAI++: Feature-Weighted Calibrated Tabular Explainable AI for Heart Disease Prediction. Discover Artificial Intelligence (Springer). Co-author.
Enhanced Brain Tumor Diagnosis Through Multi-Modal Feature Analysis and Hyperparameter-Tuned XGBoost. Expert Systems With Applications (Elsevier). Co-author.
Integrating Custom CNN and Explainable AI for Evaluating GNNs and CNNs in Brain Tumor MRI Classification. Healthcare Analytics (Elsevier). Co-author.
Industry
Professional experience
U.S. production AI and full-stack delivery, with prior platform and FinTech leadership.
Senior Full Stack Engineer
Volkswagen Group of America · Auburn Hills, MI · Apr 2024 – present · Hybrid
Production LangChain / LangGraph RAG for repair-manual search with cited answers (Solr chunking and indexing) on dealer and technician platforms.
Specialist (2021): microservices split of high-traffic recharge (Spring Boot, Node.js, AWS); QR payments, Kafka, ELK, eKYC banking integrations.
Associate (2018–2020): Angular / Spring Boot payments and banking; legacy modernization.
Employee of the Month, December 2020.
Also independent contractor / freelance work with treffio.com (event platforms), Last Call Media (time-tracking and Next.js/NestJS/AWS), and VioResume (AI resume and job-matching product).
Engineering
Production AI stack
Summary of systems used in professional delivery—detail lives under Experience.
RAG & agents: LangChain / LangGraph, grounded retrieval with citations, MCP tool wiring, LangSmith tracing, Solr indexing and vector search where needed.