I build intelligent systems where deep learning meets power hardware — from EV battery estimation to real-time embedded control. Published at IEEE ECCE, with experience across defense, aerospace, and energy.
I'm a graduate researcher at the University of Akron pursuing an M.Sc. in Electrical & Computer Engineering. My work sits at the intersection of artificial intelligence and power electronics — applying deep neural networks to real-world energy systems and electric vehicle battery management.
Before grad school, I developed AI-driven ADAS systems at ASELSAN, Turkey's largest defense electronics company, and built flight-critical avionics at Turkish Aerospace Industries for UAV platforms including ANKA and AKSUNGUR.
I'm drawn to problems that demand both algorithmic precision and hardware intuition — where a CNN-LSTM model meets a CAN bus, or a sensor fusion pipeline runs in real time on a DSP.
PyTorch, TensorFlow, CNN-LSTM, GANs, self-attention
FOC, DAB converters, SVPWM, PMSM control
Kalman filtering, anomaly detection, INS fusion
Defense, aerospace, and graduate research — systems built for the real world.
Hands-on projects spanning ML, power electronics, and embedded systems.
CAN bus interface between a TI DSP 3-phase inverter and host PC with live Python GUI for real-time telemetry, fault states, and PMSM angle offset calibration.
Implemented FOC on DSP with Clarke/Park transforms and SVPWM generation. Designed and tuned PI controllers for d-axis and q-axis current loops with oscilloscope validation.
Task-specific CNN-LSTM architecture with self-attention for real-time battery State-of-Charge estimation. Published at IEEE ECCE 2025, Philadelphia.
Computer vision system with ResNet50, CNN, and YOLOv5 for identifying chess pieces and analyzing board positions from images.
Implemented clinical diabetes prediction using k-NN, Logistic Regression, and Random Forest classifiers with AdaBoost for robust ensemble classification.
Whether you're looking for an engineer, a research collaborator, or want to talk deep learning and power electronics — reach out.