Abrar Majeedi

I'm a PhD candidate at the University of Wisconsin-Madison, working on sequential deep learning including timeseries analysis and video machine learning.

I am fortunate to be advised by Prof. Yin Li. I have previously done research internships at Amazon, Microsoft and Dell EMC.

Email  /  CV  /  Scholar  /  Github

Research

I'm interested broadly in deep learning. I mostly work on multimodal sequential data such as video data, sensor data (time series) and text data.

Publications

Action quality assessment in videos by incorporating human designed scoring rubrics while providing calibrated uncertainty estimates.

Auotmatically detect the glottic opening during neonatal intubation using video laryngoscopy to improve intubation outcomes.

Automatically quantify care manipulation activities in neonatal intensive care units (NICUs), while integrating physiological signal data to monitor neonatal stress in NICUs.

Assess perceptual quality of videos encoded by Machine Learning-based Video Codecs.

Placed 2nd in the Egocentric action detection challenge