AI-Driven Battery Intelligence · Solar PV Design · Power Electronics
Ufa University of Science & Technology, Russia
Building the mind inside the battery — teaching machines, converters, and grid systems to anticipate energy needs before they arise. From Bangladesh to Sweden to Russia, one question drives everything: how do we make renewable energy reliably intelligent?
Md. Nafeez Rahman is a PhD candidate at Ufa University of Science and Technology (UUST), Russia, where he also serves as Head of the Servo Motor Laboratory under the Advanced Engineering School — Motors for the Future.
His research sits at the intersection of AI-driven battery management, solar PV infrastructure design, and precision power electronics. He is the creator of the NeuroBatt ecosystem — five Russian Federal patents covering battery classification, life prediction, and autonomous swarm energy management for UAV and robotic platforms.
A recipient of the Russian Government Scholarship twice consecutively (MSc 2022–2024, PhD 2024–2028), he graduated with the highest academic honour: a RED DIPLOM (97%). His 23 publications span IEEE, Scopus Q1, Springer Nature, and SPIE, across 9+ countries of publication.
The international arc — Bangladesh → Sweden → Russia → Global — is not incidental. It is the research strategy.
Random Forest SoC prediction (MAE = 8.31%), NeuroBatt Classifier & Predictor, CNN-LSTM for temporal health modelling. The deepest and most patent-dense strand — bridging electrochemistry and edge AI.
150 kW DC PV station design at Ufa Airport; seasonal adaptive sizing (233 kWh summer / 200 kWh winter); techno-economic LCOE/NPV/IRR analysis. Designed for real infrastructure, not theory.
RL agent for second-life EV battery grid buffering (reward converges –60 to –70 after 1000 episodes); ARIMA-SLSQP real-time dispatch; 60.7 t CO₂ saved per electric bus annually.
Phase-current balancing in multiphase DC converters (Scopus Q1); variable-input buck converter design; PLC for EV networks; HTS motor propulsion for electric aircraft. The mathematical foundation of everything above.
Rural Bangladesh net-zero hybrid systems; garment industry solar-diesel optimisation; Russian EV market policy review; early bioelectrochemistry — the biographical thread connecting where he comes from to what he solves.
Five Russian Federal patents registered 2024–2025 form a complete AI battery management architecture: Classify → Predict → Swarm. From the MSc-era aircraft BESS foundation to UAV and robotic fleet deployment — a commercially mature IP portfolio at TRL 4–5.
Total: 6 years 4 months 28 days · Bangladesh · Sweden · Russia
Open to research collaboration, academic positions, fellowship applications, and industry partnerships in battery AI, solar PV systems, and electric vehicle infrastructure.
The NeuroBatt patent suite is available for technology transfer discussions with industrial partners in EV, UAV, robotics, and grid-edge storage sectors.
Available for peer review, editorial work, and conference programme committees in energy storage, power electronics, and AI-driven energy systems.