I work at Thomson Reuters as an NLP/ML applied research scientist, leading research initiatives to enhance the search relevance of Practical Law search engine.

I have a PhD in computer science from the University of Waterloo, with a focus in information retrieval, particularly modeling user behavior with search systems. I also worked on machine learning projects related to efficient high-recall document retrieval and annotation systems, and misinformation in web search.

Since 2013, I have written internal and hobby projects in Python. Some of my code is open-source and available in my Github account.

Education


University of Waterloo
PhD in Computer Science (Information Retrieval). 2017-2021
Masters in Computer Science (Information Retrieval). 2015-2017

University of Victoria
Bachelors in Computer Science (Honors). 2010-2014

Papers

Learning Trustworthy Web Sources to Derive Correct Answers and Reduce Health Misinformation in Search. [DOI] [PDF] [SIGIR'22]
Dake Zhang, Amir Vakili Tahami, Mustafa Abualsaud, and Mark D. Smucker.

The Dark Side of Relevance: The Effect of Non-Relevant Results on Search Behavior. [DOI] [PDF] [CHIIR'22]
Mustafa Abualsaud, and Mark D. Smucker.

Visualizing Searcher Gaze Patterns. [POSTER] [PDF] [CHIIR'21]
Mustafa Abualsaud, Mark D. Smucker, and Charles L. A. Clarke.

The Effect of Queries and Search Result Quality on the Rate of Query Abandonment in Interactive Information Retrieval. [DOI] [PDF] [CHIIR'20]
Mustafa Abualsaud.

Overview of the TREC 2019 Decision Track. [PDF] [TREC'19]
Mustafa Abualsaud, Christina Lioma, Maria Maistro, Mark D. Smucker, and Guido Zuccon.

UWaterlooMDS at the TREC 2019 Decision Track. [PDF] [TREC'19] [Top Performing Run]
Mustafa Abualsaud, Fuat C. Beylunioğlu, Mark D. Smucker, and P. Robert Duimering.

Patterns of Search Result Examination: Query to First Action. [DOI] [PDF] [CIKM'19]
Mustafa Abualsaud and Mark D. Smucker.

Exposure and Order Effects of Misinformation on Health Search Decisions. [POSTER] [PDF] [SIGIR - ROME'19]
Mustafa Abualsaud and Mark D. Smucker.

Dynamic Sampling Meets Pooling. [DOI] [SIGIR'19]
Gordon V. Cormack, Haotian Zhang, Nimesh Ghelani, Mustafa Abualsaud, Mark D. Smucker, Maura R. Grossman, Shahin Rahbariasl, and Amira Ghenai.

UWaterlooMDS at the TREC 2018 Common Core Track. [PDF] [TREC'18] [Top Performing Run]
Mustafa Abualsaud, Gordon V. Cormack, Nimesh Ghelani, Amira Ghenai, Maura R. Grossman, Shahin Rahbariasl Haotian Zhang, and Mark D. Smucker.
  • Again! our submission received highest score among 72 runs.

A System for Efficient High-Recall Retrieval. [DEMO] [PDF] [SIGIR'18]
Mustafa Abualsaud, Nimesh Ghelani, Haotian Zhang, Mark Smucker, Gordon Cormack and Maura Grossman.

Effective User Interaction for High-Recall Retrieval: Less is More. [DOI] [PDF] [CIKM'18]
Haotian Zhang, Mustafa Abualsaud, Nimesh Ghelani, Mark Smucker, Gordon Cormack and Maura Grossman.

A Study of Immediate Requery Behavior in Search. [DOI] [PDF] [CHIIR'18]
Haotian Zhang, Mustafa Abualsaud, and Mark D. Smucker.

Overview of the TREC 2017 Real-Time Summarization Track. [PDF] [TREC'17]
Jimmy Lin, Salman Mohammed, Royal Sequiera, Luchen Tan, Nimesh Ghelani, Mustafa Abualsaud, Richard McCreadie, Dmitrijs Milajevs, Ellen M. Voorhees

UWaterlooMDS at the TREC 2017 Common Core Track. [PDF] [TREC'17] [Top Performing Run]
Haotian Zhang, Mustafa Abualsaud, Nimesh Ghelani, Angshuman Ghosh, Mark Smucker, Gordon Cormack and Maura Grossman.
  • Our submission received highest score among 75 runs!

WaterlooClarke: TREC 2015 Microblog Track. [PDF] [TREC'15]
Mustafa Abualsaud, Milad Ghaznavi, Daniel Recoskie, and Charles L. A. Clarke.

Talks


Users, Queries, and Abandonment in Web Search. Etsy, Brooklyn (virtual). Feb 2021.
Understanding Query Abandonment Behavior in Web Search. Google, Mountain View. Dec 2017.

Service


PC member SIGIR ('24, '23, '22), CIKM('23).
Student representative in the Graduate Recruitment Committee. UWaterloo, Cheriton School of Computer Science.
Student representative in the School Advisory Committee on Appointments. UWaterloo, Cheriton School of Computer Science. Winter 2020.

Code


HiCAL: A System for Efficient High-Recall Retrieval. [Github]

Githeat: Visualizing git commits in your terminal. [Github]