SaveFood — Behavioral ML for Food Waste Reduction
Trained XGBoost on IoT time-series to predict spoilage (F1: 0.89). Dashboard visualizes waste reduction impact.
Methods: Time-series forecasting, SHAP interpretability
AI for Social Integrity
I develop interpretable machine learning frameworks to detect social engineering, model behavioral risk, and predict socio-technical system failures. Champion, NASA International Space Apps Champion, Global Nominee & Honorable Mention.
Team Polaris — NASA Space Apps Challenge 2025 Champions, Global Nommine & Honarable Mention
I was part of Team Polaris, which won the Barisal Division championship. Our team combined expertise in ML, full-stack development, data analysis, and UI/UX design to create a winning solution.
Research Vision
I work at the intersection of Artificial Intelligence, behavioral modeling, and socio-technical system resilience. My research focuses on:
- Detecting social engineering through interpretable behavioral anomaly modeling
- Predicting system failures (e.g., programmer attrition, food spoilage) using socio-economic and IoT data
- Building continual learning frameworks for dynamic environments
I aim to develop AI systems that are not only accurate but explainable, fair, and grounded in real human behavior.
Research Projects
SafeRoads — Geospatial Risk Prediction
ML model to identify high-risk urban segments using traffic + accident history (Precision: 84%).
Methods: Geospatial ML, ensemble modeling
MeteorShield — Planetary Defense
NASA NEO data platform with real-time 3D visualization. Champion, NASA Space Apps 2025.
Tech: NASA APIs, Three.js, data storytelling
AgroHub — IoT & ML Smart Agriculture
Real-time farm monitoring with ML decision support for smallholder farmers.
Tech: IoT, Python, ML
SciGenie — One-click EDA & AutoML
Accelerates research prototyping with automated EDA and AutoML (Random Forest, XGBoost, Auto-Sklearn).
Tech: Python, Auto-Sklearn, Pandas
Publications
- Hasan, M. M., Rakib, R., Molla, M. A., et al. — A Socio-Economic ML Framework for Predicting Programmer Retention (Feature Set A). BIM 2025. [Accepted]
- Hasan, M. M., Mahin, A. A., Chakraborty, S., et al. — Behavioral & Demographic Fusion for Developer Attrition Modeling (Feature Set B). BIM 2025. [Accepted]
- Molla, M. A., Rakib, R., Hasan, M. M., et al. — ML for Earthquake Magnitude Prediction using USGS Data. IDAA 2025. [Under Review]
- Mahin, A. A., Hasan, M. M., et al. — A Modular Framework for Continual Reinforcement Learning. IDAA 2025. [Under Review]
Technical Skills
Languages
ML & Data
Tools
Professional Memberships
- IEEE — Student Member (Valid through Dec 2026)
- IEEE Computer Society — Student Member (Valid through Dec 2026)
- BASIS Students' Forum (DIU Chapter) — Executive Member
Research Collaboration
I am actively seeking **research internships** in AI, behavioral modeling, and social engineering detection.