EAI provides an incredible platform for me to lend my expertise in AI to collaborate with experts across different disciplines. As an early stage researcher this platform is invaluable for me to build my research career and to contribute to important interdisciplinary research problems.
– Zulqarnain Khan, Research Scientist, EAI
Zulqarnain Khan is a research scientist with the Institute for Experiential AI at Northeastern University. He has been part of the university for around six years, and was a research assistant at the Center for Signal Processing, Imaging, Reasoning, and Learning (SPIRAL) before switching to his current position in September 2022.
Khan holds a BA in Electrical and Electronics Engineering from the National University of Science and Technology in Pakistan, an MS in Electrical Engineering from Northeastern University. The latter was achieved as a Fulbright Scholar at professor Octavia Camps’ Robust Systems Lab, with Khan gaining his Ph.D in Machine Learning in a NU program led by professor Jennifer Dy.
As part of his academic studies, he focused on applying and building interpretable machine learning models for neuroscience and psychophysiology, in addition, Khan has engaged in theoretical work that relates to explanation-based learning methods for model training.
Khan’s research has been published in major ML, neuroscience and psychology journals, including but not limited to Psychophysiology, Neuroinformatics and Scientific Reports. In addition, his work and theories have also been presented at conferences such as NeurIPS.
His research interests at the institute continue along the same lines, with a defined goal to develop machine learning models for practical problems (ideally in healthcare). Khan collaborates closely with domain experts, and is currently also working towards improving interpretability of existing machine learning models.
A keen cricketer, Khan has represented the university in the American College Cricket league and considers himself to be an effective off spin bowler.