Ehsan Kazemi

Education

  • Ph.D., Computer, Communication and Information Sciences (2011-2016), Thesis title: “Network Alignment: Theory, Algorithms, and Applications”, Laboratory for computer Communications and Applications (LCA4), EPFL, Lausanne, Switzerland.
  • Ph.D. candidate, Computer, Communication and Information Sciences (2010-2011), Unaffiliated Ph.D. student, EPFL, Lausanne, Switzerland, Laboratory for computer Communications and Applications (LCA1).
  • MS.c., Electrical Engineering and Communication Systems (2008-2010), Sharif University of Technology, Tehran, Iran.
  • BS.c., Electrical Engineering and Communication Systems (2004-2008), Sharif University of Technology, Tehran, Iran.

Projects

  • Submodular optimization: In this project, we studied the problem of scalable submodular maximization under the unifying umbrella of robust computation, where the dataset may change over time (i.e., some portion of data or sensitive features are deleted) or the utility function is not fully known.
  • Deep learning in computational biology: We utilized several computational methods based on convolutional neural networks (CNN) and build a stand-alone pipeline to effectively classify different histopathology images across different types of cancer and classify the morphological quality of blastocysts.
  • Fairness in machine learning: Nowadays, many sensitive decision-making tasks rely on predictions from automated statistical and machine learning algorithms. In this project, we answered the question of how to control for latent discrimination in predictive models and how to provably remove it.
  • Network alignment: In this project, the goal was to merge information from different sources where the data provides two (or more) partial views of the network, and where the node labels are sometimes ambiguous. We studied this problem form information theoretic, algorithmic and application perspectives.
  • Mobility modeling and location privacy: The goal was to model the mobility from individual and collective perspectives. We also investigated the privacy of users for a location-based service system based on the mobility of users.

Publications

PRess