π Final Year PhD Student at Cardiff University specializing in Embedded Machine Learning (TinyML), Anomaly Detection, and Predictive Maintenance.
- π― Embedded Machine Learning (TinyML):
Optimizing models for edge devices using techniques like quantization, pruning, and compression. - π§ Anomaly Detection:
Leveraging AI/ML for real-time detection on IoT and resource-constrained hardware. - βοΈ IoT and Edge Computing:
Building scalable edge-to-cloud architectures integrating BLE and sensor fusion. - π οΈ Adversarial Robustness:
Enhancing the reliability of ML models against adversarial challenges.
- Edge AI for Anomaly Detection:
Real-time anomaly detection on IoT devices using LSTM, 1D-CNN, and 2D-CNN models. - Optimizing TinyML Models:
Applying quantization and compression for resource-constrained hardware like STM32-based PCBs. - Adversarial Robustness:
Improving ML model resilience on edge devices against adversarial attacks.
π Portfolio Website
π» GitHub
π§ Email
π LinkedIn