JAD KABBARA

News: I graduated from McGill and will be starting a postdoc at the MIT CCC with Prof. Deb Roy in November 2022!

My research advisor is Prof. Jackie C.K. Cheung. I am a member of the Reasoning and Learning lab (RL-Lab) and the Montreal Institute for Learning Algorithms (Mila). I am broadly interested in artificial intelligence and natural language processing. Currently, my research focus is on computational pragmatics and natural language understanding. I am particularly interested in the application of deep learning to these problem domains.

Our group organizes the CompLing meetings, a series of weekly research seminars in which we host researchers from the industry and academia working in different areas of natural language processing and computational linguistics. To join the CompLing mailing list, please send an email to compling-owner@cs.mcgill.ca.

Before getting into AI, I worked on wireless sensor networks for healthcare (@McGill -- ECE department), wireless sensor networks for water monitoring in rivers (@UC-Berkeley -- Floating Sensor Network project) and WiMAX networking (@Mobinets).

PUBLICATIONS

	Investigating the Performance of Transformer-Based NLI Models on Presuppositional Inferences Jad Kabbara and Jackie C.K. Cheung.   COLING 2022, Gyeongju, Republic of Korea, October 2022. [PAPER]     Best Short Paper Award
	Post-Editing Extractive Summaries by Definiteness Prediction Jad Kabbara and Jackie C.K. Cheung.   Findings of EMNLP 2021, Punta Cana, Dominican Republic, November 2021. [PAPER]
	Computational Investigations of Pragmatic Effects in Natural Language Jad Kabbara   NAACL Student Reseserch Workshop 2019, Minneapolis, Minnesota, USA, June 2019. [PAPER]
	Let's do it "again": A First Computational Approach to Detecting Adverbial Presupposition Triggers Andre Cianflone (co-primary), Yulan Feng (co-primary), Jad Kabbara (co-primary) and Jackie C.K. Cheung   ACL 2018, Melbourne, Australia, July 2018. [Oral] [PAPER]     [SLIDES]     [DATA]     Best Paper Award
	Relevance Effect: Exploiting Bayesian Networks to Improve Supervised Learning Ardavan S. Nobandegani (co-primary), Jad Kabbara (co-primary) and Ioannis N. Psaromiligkos.   IJCNN 2017, Anchorage, Alaska, USA, May 2017. [PAPER]     [POSTER]
	Capturing Pragmatic Knowledge in Article Usage Prediction using LSTMs Jad Kabbara, Yulan Feng and Jackie C.K. Cheung.   COLING 2016, Osaka, Japan, December 2016. [Oral] [PAPER]     [SLIDES]
	Stylistic Transfer in Natural Language Generation Systems Using Recurrent Neural Networks Jad Kabbara and Jackie C.K. Cheung.   UBLP 2016 (@ EMNLP 2016), Austin, Texas, USA, November 2016. [PAPER]     [POSTER]
	Kernel Subspace Pursuit for Sparse Regression Jad Kabbara and Ioannis N. Psaromiligkos.   Pattern Recognition Letters, January 2016. [PAPER]
	Improving the tracking ability of KRLS using kernel subspace pursuit Jad Kabbara and Ioannis N. Psaromiligkos.   IEEE ICASSP 2014, Florence, Italy, May 2014. [PAPER]     [POSTER]     Kernel adaptive filtering algorithms with improved tracking ability Jad Kabbara.   [PDF]     Master's Thesis, McGill ECE, April 2014.

AWARDS

Reasoning and Learning Lab
School of Computer Science, McGill University
3480 University Street, Room 111
Montreal, QC H3A 0E9
(514) 398-7071
jad@cs.mcgill.ca

Last Modified: October 2022