Electronics engineer researching reinforcement learning for the optimization and control of RF, wireless, and autonomous physical systems. First-author published research in embedded fall detection.
My work spans the full stack, PCB design and firmware up through model training and on-device deployment. Currently extending that foundation into computational electromagnetics and AI-accelerated antenna design
- RL for wireless systems: reinforcement learning for spectrum access and antenna optimization (see
dqn-dynamic-spectrum-access,rl-dipole-tuning) - Wearable health-IoT: embedded ML for real-time sensor data (fall detection, activity recognition)
PhD opportunities and research collaboration in reinforcement learning for intelligent wireless and autonomous physical systems, spanning RF/antenna optimization, spectrum access, edge AI, and simulation-driven digital twins for physical systems.
Khatri, S. K., Parajuli, D., Mane, P. M., Chaulagain, B., & Thapa, S. (2026). Fall Detection System for Elderly People Using LSTM. Journal of Engineering Issues and Solutions, 5(1), 210-220.
Bachelor in Electronics, Communication & Information Engineering, Pulchowk Campus, Institute of Engineering, Tribhuvan University (First Division with Distinction). Registered Engineer, Nepal Engineering Council.
| Project | What it is |
|---|---|
rl-dipole-tuning |
RL environment wrapping NEC2 for automated dipole antenna resonant-frequency optimization |
dqn-dynamic-spectrum-access |
PyTorch replication of Wang et al. (2018) DQN for dynamic multichannel access; benchmarked against the analytical optimal policy and a Whittle Index heuristic on a correlated-channel POMDP |
Fall-Detection-System |
Wearable fall-detection device + double-layer LSTM model (97.8% accuracy) - collaborative project; companion code to the publication above; designed the wearable PCB, collected the training dataset |
Startracker-Simulator-for-Attitude-Determination-of-Spacecrafts |
Synthetic star-image simulator and visualization layer for spacecraft attitude determination - collaborative project; built the image generation & visualization layer |
Languages: Python C/C++ VHDL
Embedded: STM32 ESP32 RP2040
ML/DL: PyTorch TensorFlow
Hardware: KiCAD PyNEC
Cloud/Dev: AWS Git Linux