Electrical Engineer — Signal Processing & Applied Machine Learning 

Implemented autocorrelation-based estimation to recover wind velocity from Doppler frequency shifts in backscattered LiDAR returns. Signal chain covered band-pass and notch filtering, FFT spectral analysis, and sliding-window processing for time-resolved velocity extraction. Validated against known reference conditions and characterised under degraded signal quality. 

An algorithm in MATLAB for automatic melanoma segmentation in dermoscopic images: morphological hair removal, Otsu thresholding for initial masking, and dilation for boundary refinement. Validated against expert ground truth at Dice 0.938 and Jaccard 0.884.

Comparison of envelope-spectrum and time-domain feature families for rolling- element bearing fault classification on the CWRU dataset, under a leave-one-load- out protocol that tests generalisation across operating conditions. Noise and window-length sweeps showed time-domain features outperforming envelope features down to 0 dB SNR, contradicting my initial hypothesis, and identified a hard physical limit: below 256 samples, FFT resolution exceeds the separation between inner- and outer-race defect frequencies, making the two faults indistinguishable in principle. 

Blind modulation classifier using higher-order cumulants and instantaneous signal statistics with an RBF-kernel SVM. Signals are generated rather than downloaded, so the channel model is explicit and each impairment can be swept independently. Full transmit-receive chain with root-raised-cosine pulse shaping, matched filtering and symbol-rate decimation. 

Simulated a visible light communication link using ASK modulation with wavelength division multiplexing across two wavelengths, evaluating BER and Q-factor under varying ambient light conditions. Modelled a 10 Gbps link over a 2 m line-of-sight channel in OptiSystem.