About Me

I hold a PhD in Electrical Engineering from the University of Kentucky (October 2026), specializing in the application of deep learning techniques to video analysis. My research involves building machine learning pipelines for behavior recognition, with a focus on autism-related behavior detection. I led the release of ASD-FEAT, a multi-modal infant video dataset and benchmark (code · dataset DOI). I have extensive experience in data preprocessing, feature engineering, and utilizing libraries like OpenCV for video processing and analysis. I am proficient in Python and frameworks such as TensorFlow and PyTorch. Before and during my PhD, I spent six years teaching undergraduate electrical engineering (see Teaching).

Education

• PhD Electrical Engineering (Oct 2026) University of Kentucky
• MS Electrical Engineering (2011) National University of Sciences and Technology (NUST), Pakistan
• BE Electrical Engineering (2007) National University of Sciences and Technology (NUST), Pakistan

Teaching

Six years of teaching undergraduate electrical engineering: four years as a Lecturer at NUST and two as a Graduate Teaching Assistant at the University of Kentucky, across six courses in total.

Lecturer, Electrical Engineering (Jul 2011 – Jun 2015) National University of Sciences and Technology (NUST), Islamabad, Pakistan

• Taught three undergraduate courses: Signals & Systems, Radar Systems, and Microprocessor & Digital Systems.
• Designed the lectures, assignments, and assessments for these courses.
• Set and applied assessment standards across cohorts for exams, lab work, and project defenses.
• Advised final-year capstone projects from problem framing through to working prototypes, including:
  • a real-time 3D sound-source localization system for a humanoid robot, using a microphone array (TDOA / GCC-PHAT);
  • through-the-wall motion detection using UWB radar.

Graduate Teaching Assistant (Jan 2018 – Dec 2019) University of Kentucky, USA

• Supported three undergraduate courses: AC Circuits, Power Electronics, and Design of Logic Circuits.
• Ran labs and office hours.

Publications

• Sidrah Liaqat et al. “ASD-FEAT: A Multi-Modal Infant Video-Derived Dataset for Early ASD Risk Prediction.” Data-centric Machine Learning Research (DMLR), under review. Code · Dataset (DOI 10.5281/zenodo.22261227)
• Sidrah Liaqat, Chongruo Wu, Prashanth Reddy Duggirala, Sen-ching Samson Cheung, Chen-Nee Chuah, Sally Ozonoff, and Gregory Young. “Predicting ASD diagnosis in children with synthetic and image-based eye gaze data.” Signal Processing: Image Communication, vol. 94, 2021.
• Chongruo Wu, Sidrah Liaqat, Halil Helvaci, Sen-ching Samson Cheung, Chen-Nee Chuah, Sally Ozonoff, Gregory Young. “Machine Learning Based Autism Spectrum Disorder Detection from Videos.” IEEE International Conference on E-health Networking, Application & Services (HEALTH-COM), pp. 1-6, 2020.
• Sidrah Liaqat, Chongruo Wu, Sen-ching Cheung, Chen-Nee Chuah, and Sally Ozonoff. “Predicting Autism Diagnosis using Image with Fixations and Synthetic Saccade Patterns.” In IEEE International Conference on Multimedia & Expo Workshops (ICMEW), pp. 647-650, 2019.
• Sidrah Liaqat, Narjes Bozorg, Neenu Jose, Patrick Conrey, Antony Tamasi, and Michael T. Johnson. “Domain Tuning Methods for Bird Audio Detection.” In Detection and Classification of Acoustic Scenes and Events (DCASE), 2018.
• Sidrah Liaqat, Mojeeb B. Ihsan, S. Zeeshan Asghar, Aqib Ejaz, Aamir Javed. “High resolution 2D time frequency representation of radar micro-Doppler pedestrian signal.” In 10th European Radar Conference (EuRAD), 2013.
• Aamir Javed, Sidrah Liaqat, Mojeeb B. Ihsan. “Support vector machine based micro-Doppler signature classification of ground targets.” In 10th European Radar Conference (EuRAD), 2013.
• Aamir Javed, Aqib Ejaz, Sidrah Liaqat, Adnan Ashraf, Mojeeb B. Ihsan. “Automatic target classifier for a ground surveillance radar using linear discriminant analysis and logistic regression.” In 9th European Radar Conference (EuRAD), pp 302-305, 2012.
• Sidrah Liaqat, Shoab A. Khan, Aamir I. Bhatti, Mojeeb B. Ihsan, S. Zeeshan Asghar, Aqib Ejaz. “Automatic recognition of ground radar targets based on target RCS and short time spectrum variance.” In International Symposium on Innovations in Intelligent Systems and Applications (INISTA), pp 164-167, 2011.

Service & Mentorship

• Volunteer Classroom Lead, YMCA Project Cornerstone (2025-Present) Delivered structured social-emotional asset-building curricula to local classrooms. Focused on fostering inclusive environments, public speaking, and mentoring youth in conflict resolution and digital citizenship.

• Peer Reviewer for ICIP, TMM, TAFFC, ICASSP, AAAI

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