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projects
Immigration in the Age of Artificial Intelligence Permalink
Published:
A critical overview of how AI and digital technologies are reshaping immigration systems, from risk assessment and border control to application processing and integration support.
Data Observatory for Immigration: An AI-Assisted Scraping and Analysis Platform Permalink
Published:
Building an AI-assisted, human-in-the-loop data pipeline to collect, structure, and analyze immigration-related texts from parliamentary debates, news, and online platforms.
Migrant Bias in Web-Scale Search Datasets Permalink
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Studying how immigration-related queries and passages are framed in large-scale IR benchmarks (e.g., MS MARCO) to uncover biases in how migrants and immigration are represented.
Immigrant Journeys on Reddit: Mental Health, Integration, and Everyday Life Permalink
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A longitudinal analysis of Reddit posts by immigrants to Canada, reconstructing pre- and post-arrival timelines to study mental health trajectories, integration challenges, and everyday concerns.
publications
Switching GAN-Based Image Filters to Improve Perception for Autonomous Driving
Published in University of Waterloo Thesis, 2019
A dissertation exploring GAN-based image enhancement techniques for improved autonomous driving perception.
Sinophobia on Twitter: Integrating Theory, Humans, and Machines
Published in ACM CSCW Workshop on Addressing Challenges and Opportunities in Online Extremism Research, 2021
This workshop paper explores Sinophobic discourse on Twitter by integrating social theory, human annotation, and machine learning. It highlights the value of interdisciplinary approaches for studying online extremism and racialized hate.
The Role of Artificial Intelligence in Immigration: From Automation to Accountability
Published in In Ana Beduschi (Ed.), Handbook on Migration and Artificial Intelligence, Edward Elgar Publishing, 2026
This chapter provides a critical overview of how artificial intelligence is deployed across immigration systems, from application processing to border enforcement. It highlights risks related to bias, opacity, and accountability, and outlines pathways for rights-respecting and transparent AI governance in migration contexts.
How Information Retrieval Systems Construct and Amplify Immigration Narratives
Published in European Conference on Information Retrieval (ECIR 2026), IR-for-Good Track, 2026
This paper examines how modern information retrieval systems shape, construct, and amplify dominant narratives around immigration. Using large-scale IR datasets and qualitative framing analysis, we show how retrieval pipelines can systematically privilege particular viewpoints, raising concerns for fairness, accountability, and responsible AI.
Where Journalism Silenced Voices: Indigenous Communities in Bangladeshi Media
Published in arXiv, 2025
This study examines how mainstream Bangladeshi journalism marginalizes Indigenous communities through framing, omission, and narrative silencing. It combines computational text analysis with critical media theory.
Partisan perspectives on AI and immigration: An analysis of Canadian parliamentary discourse (2014–2024)
Published in Canadian Ethnic Studies (in press), 2025
This paper analyzes how Canadian parliamentarians frame artificial intelligence and immigration between 2014 and 2024, revealing partisan divides in discourse.
SAFFRON: A Semi-Automated Framework for Software Requirements Prioritization
Published in International Journal of Advanced Computer Science and Applications, Vol. 8, No. 12, 2017
This paper presents SAFFRON, a semi-automated framework that integrates natural language processing and stakeholder feedback to improve the prioritization of software requirements. It addresses scalability and subjectivity challenges in traditional requirement analysis workflows.
Stemming: The Evolution and Current State with a Focus on Bangla
Published in arXiv, 2025
This paper surveys the evolution of stemming algorithms with a particular focus on Bangla. It reviews linguistic challenges, existing methods, and open research problems in low-resource language processing.
Switching GAN-Based Image Filters to Improve Perception for Autonomous Driving
Published in Master's Thesis, University of Waterloo, 2019
This thesis investigates the use of generative adversarial networks to improve visual perception in autonomous driving systems by dynamically switching image filters under varying environmental conditions.
State-of-the-Art Translation of Text-to-Gloss Using mBART: A Case Study of Bangla
Published in arXiv, 2025
This paper presents a state-of-the-art neural approach for translating Bangla text into gloss representations using mBART. It contributes to low-resource sign language processing and accessibility research.
talks
Talk 1 on Relevant Topic in Your Field
Published:
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Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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