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  short_description: Fani's Lab! at HF
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- ## Hi there 👋
 
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  [`Fani's Lab`<em>`!`</em>](https://fani-lab.github.io) launched in 2020 at the School of Computer Science, University of Windsor, with generous support from the Natural Sciences and Engineering Research Council of Canada ([``NSERC``](https://www.nserc-crsng.gc.ca/Professors-Professeurs/Grants-Subs/DGIGP-PSIGP_eng.asp)), performs research in the broad area of Social Network Analytics with special attention to temporal analysis and its synergy to Information Retrieval. Particularly, our research concerns ``user community detection``, ``user interest modelling``, ``team formation``, ``information retrieval``, ``text mining`` and ``machine learning``.
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  <img src="https://raw.githubusercontent.com/fani-lab/.github/refs/heads/main/profile/open_access.png" width="20" height="20"/> We believe in [``Open Access``](https://en.wikipedia.org/wiki/Open_access) principles. We apply a range of practices through which the research outputs will be accessible online in a public repo with reduced and/or no copyright, free of cost or other access barriers for the purpose of publicly peer review and reuse.
 
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  short_description: Fani's Lab! at HF
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  ---
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  [`Fani's Lab`<em>`!`</em>](https://fani-lab.github.io) launched in 2020 at the School of Computer Science, University of Windsor, with generous support from the Natural Sciences and Engineering Research Council of Canada ([``NSERC``](https://www.nserc-crsng.gc.ca/Professors-Professeurs/Grants-Subs/DGIGP-PSIGP_eng.asp)), performs research in the broad area of Social Network Analytics with special attention to temporal analysis and its synergy to Information Retrieval. Particularly, our research concerns ``user community detection``, ``user interest modelling``, ``team formation``, ``information retrieval``, ``text mining`` and ``machine learning``.
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  <img src="https://raw.githubusercontent.com/fani-lab/.github/refs/heads/main/profile/open_access.png" width="20" height="20"/> We believe in [``Open Access``](https://en.wikipedia.org/wiki/Open_access) principles. We apply a range of practices through which the research outputs will be accessible online in a public repo with reduced and/or no copyright, free of cost or other access barriers for the purpose of publicly peer review and reuse.