Sidrah Liaqat
Machine learning engineer — deep learning, computer vision, and video understanding.
I am a machine learning engineer and PhD candidate at the University of Kentucky, advised by Dr. Samson Cheung. I build deep learning and computer vision pipelines for action recognition and behavior interpretation from video — most recently for autism spectrum disorder behavior detection from infant videos. I work in Python with PyTorch, TensorFlow, and OpenCV. Check out my resume.
Featured Projects
ASD Behavioral Analysis from Video
Deep learning + computer vision pipelines for autism-related behavior detection from infant video. PyTorch/TensorFlow, OpenCV.
Predicting Autism in Children from Eye-Gaze Patterns
Predicting autism in children from how they visually explore images — combining gaze-fixation heatmaps with synthetically generated saccades to augment scarce clinical data. Published in Signal Processing: Image Communication (2021).
Bird Audio Detection (DCASE 2018)
A CNN ensemble that detects bird calls in field recordings — UKYSpeechLab's submission to the DCASE 2018 Bird Audio Detection Challenge, built to generalize across mismatched acoustic domains.
Earlier Research
Radar Ground-Target Recognition & Micro-Doppler Analysis
Recognizing ground-surveillance-radar targets (pedestrians, vehicles) from their micro-Doppler signatures — a fast real-time feature-based classifier paired with high-resolution time-frequency signal representations. EuRAD 2013 / INISTA 2011.