Nadine Hussami


Stanford University

Advisor: Professors Robert Tibshirani and Anshul Kundaje

You can find more information in my Resume.

Research Interests

My main research interests include statistical learning and convex optimization, with applications in genomics. I'm interested in developing methods that are able to deal with correlated features. My work has been focused on exploiting sparsity and variable clustering in high-dimensional regression problems such as phenotypic expression modeling. Moreover, I worked on developing a hierarchical boosting method to model gene regulatory networks in different cell types.


  • Software and algorithm development engineer, Bina Technologies (Acquired by Roche, 2014).

  • Intern in the algorithms research group, Mitsubishi Electric Reasearch Laboratories (MERL).


  • Aaron B. Wagner, Amine Laourine and Nadine Hussami, Degradedness and secrecy in memoryless queues, Submitted to IEEE Transactions on Information Theory, 2016.

  • Nadine Hussami and Robert Tibshirani, A Component Lasso, The Canadian Journal of Statistics, 2015.


Teaching Assistant at Stanford:
  • CS273B Deep Learning in Genomics and Biomedicine
  • STATS 345 Statistical and Machine Learning Methods for Genomics
  • EE278B Introduction to Statistical Signal Processing
  • EE178/278A Probabilistic Systems Analysis
  • CS262 Computational Genomics
  • CS224W Social and Information Network Analysis