Ali Ayub
email: ali.ayub@concordia.ca
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I am an Assistant Professor in CIISE and co-affiliated with CSSE in the Gina Cody School of Engineering and Computer Science at Concordia University. I am also an Adjunct Professor in SYDE at the University of Waterloo. My research interests lie at the intersection of Machine Learning (ML) and human-robot Interaction (HRI) and focus on interactive/human-in-the-loop learning. My research goal is to enable long-term personalization for autonomous robots in real-world environments. I develop continual/lifelong learning techniques that can allow robots to interact with and learn from their users and then use the learned knowledge to assist users over the long term. These techniques are backed by rigorous testing in simulation and physical testing on robotic platforms with human users.
I graduated with a PhD degree in Electrical Engineering from Penn State with Alan Wagner. Afterwards, I was a Post-Doctoral fellow at the University of Waterloo with Kerstin Dautenhahn and Chrystopher Nehaniv and worked at Thales, Canada. Before my graduate studies, I obtained my BS in Electrical Engineering at the University of Engineering and Technology, Lahore.
I am recruiting MS and PhD students! Please check this page for more information.
Note: if you want me to review for your venue, please see this page.
News
Sept 2024: I have been appointed as an Adjunct Professor in SYDE at the University of Waterloo!
August 2024: I have joined CIISE (co-affiliated with CSSE) in the Gina Cody School of Engineering and Computer Science at Concordia University!
March 2024: Our paper on a human-centered view of continual learning has been accepted at ACM Transactions on Human-Robot Interaction (THRI)!
Jan 2024: Our work on interactive continual learning for long-term personalization was accepted to ICRA 2024!
June 2023: Our paper on CBCL-PR was accepted to IEEE Transactions on Cognitive and Developmental Systems!
June 2023: Three papers were accepted to IEEE ROMAN, 2023!
May 2023: New paper on continual learning through HRI: a long-term user study to understand human perceptions of a continual learning robot in repeated interactions.
May 2023: Our paper "Active Class Selection for Few-Shot Class-Incremental Learning" was accepted to CoLLAs 2023!
May 2023: Invited to talk about my current and past research on human-robot interaction on the TrainCheck podcast.
April 2023: Selected for the DAAD AInet Postdoc Fellowship.