Maliheh Izadi

Maliheh Izadi is a PhD candidate of Software Engineering and a research assistant at Automated Software Engineering Lab (ASE), computer engineering department at Sharif University of Technology, supervised by Dr. Abbas Heydarnoori.

She is currently working on applied data mining and machine learning techniques and tools for software engineering.

She received her M.Sc. degree in IT engineering from Sharif University of Technology in 2014. Her master thesis focused on finding a novel and unified approach for evaluation of recommender systems in different contexts.

 

Her research interests include (but are not limited to)

  • Applied data mining and machine learning,
  • Mining Software Repositories
  • Software Engineering for Mobile Applications
  • Big data
  • Recommender systems

 

Her publications are listed below:

  • Izadi, M., Javari, A., & Jalilii, M. (2014). Unifying inconsistent evaluation metrics in recommender systems. InRecSys conference, REDD workshop.
  • Javari, A., Izadi, M., & Jalili, M. (2016). Recommender systems for social networks analysis and mining: precision versus diversity. In Complex Systems and Networks (pp. 423-438). Springer Berlin Heidelberg.

 

Research Interests

  • Mining Software Repositories
  • Software Engineering for Mobile Applications
  • Data mining and applied machine learning
  • Big data
  • Recommender systems