Fattane Zarrinkalam

Headshot of Fattane Zarrinkalam
Assistant Professor
School of Engineering
Email: 
fzarrink@uoguelph.ca
Phone number: 
(519) 824-4120 ext. 56907
Office: 
THRN 2405
Website links: 
Google Scholar
Personal Website
Seeking academic or industry partnerships in the area(s) of: 
Social Media Mining, Semantic Technologies, User Modeling, Machine Learning/Deep Learning
Available positions for grads/undergrads/postdoctoral fellows: 
Enquire by e-mail

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Information retrieval, Semantic Technologies, Social Media Mining, User Modeling

Education and Employment Background

Dr. Fattane Zarrinkalam received her PhD from Ferdowsi University of Mashhad, Iran. She went on to hold a Postdoctoral Research Fellow position at Ryerson University between 2018 and 2020. She is now an Assistant Professor in the University of Guelph’s School of Engineering, which she joined in 2021.

Research Themes

Zarrinkalam’s research is focused on social media mining and semantic technologies, with specific attention to semantics of user-generated content, user interactions and temporal behavioral patterns of users, for the purpose of extracting actionable insights. The impact of her research is reflected in some interdisciplinary projects that aim at solving real-world problems in different fields such as healthcare, telecommunication, legal tech, and e-commerce. Key areas of focus include:

  1. Semantic interpretation of social content. Zarrinkalam investigates the complexity of analysing the semantics of social media content to extract the underlying meaning of user content. She aims to develop efficient domain-independent entity linking techniques that can automatically infer semantics of user-generated social media content by linking them to knowledge graphs.
  2. User modeling from social media. Zarrinkalam explores semantic techniques for analyzing the historical social content of users to extract their explicit and implicit interests, which contributes to the field of recommender systems. She is particularly interested in using temporal user modeling to predict future user interests.
  3. Social media mining for social good. Zarrinkalam examines social analytics from the lens of the potential threats to fairness and the inclusion of more transparency in the design of social media mining approaches to impact social good.

Highlights

  • Vector Institute Postgraduate Affiliate Program, Vector Institute, 2021
  • Editorial Board, Information Processing & Management, Special Issue on Dis/Misinformation Mining from Social Media, 2021
  • Editorial Board, IEEE Transactions on Network Science and Engineering, Healthcare Social Analytics, 2021
  • Co-chair, International Workshop on Mining Actionable Insights from Social Network (MAISoN), since 2020.