Research Engineer · ML Researcher · Industrial AI · Elsevier Reviewer
📍 Rajshahi, Bangladesh | 🏛️ IUT EEE Alumni | ⚡ Assistant Engineer @ PRAN Agro Limited
I work at the intersection of physics-informed machine learning, renewable energy forecasting, and trustworthy AI — building models that remain reliable under uncertainty and distribution shift for applications where unreliable predictions carry real consequences.
| # | Title | Venue | Status |
|---|---|---|---|
| 1 | A Hybrid XGBoost-LSTM Model with Physics-Informed Features for Solar Power Forecasting | Energy Reports, Elsevier (IF 5.1) | ✅ Published 2026 |
| 2 | Physics-Informed Residual Learning for Sensorless Torque Estimation in PMSMs (PIRL-Net) | IEEE Access (IF 3.6) | 🔄 Under Review |
| 3 | PV-Clean4: A Contamination-Free Benchmark for Solar PV Fault Detection | Applied Energy, Elsevier (IF 11.2) | 📝 Working Paper |
| 4 | Renewable Energy Penetration and Flexibility Stress in European Electricity Markets | Energy Economics, Elsevier (IF 14.2) | 📝 Working Paper |
📋 Peer Reviewer — Computers & Electrical Engineering, Elsevier (IF 4.9) · 2 reviews completed (2026)
7+ Industry 4.0 automation projects deployed independently at PRAN Agro Limited:
- PLC-HMI Addressable Fire Alarm System → 2+ years zero breakdown
- Web-integrated OEE monitoring via Siemens S7-200 PLC
- WTP automation, VFD retrofits, paperless meter reading (83% time reduction)
- 🌐 Industrial Engineering Web App for electrical calculations
PyTorch TensorFlow XGBoost Physics-Informed NNs Conformal Prediction
Uncertainty Quantification PLC Programming HMI Design SCADA Python MATLAB
