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Negar Soheili

Negar Soheili headshot
  • Assistant Professor of Information and Decision Sciences

Education

  • PhD in Operations Research at the Tepper School of Business, Carnegie Mellon University

Classes Taught

  • Statistics for Management (IDS 570), Liautaud Graduate School of Business, University of Illinois at Chicago (Fall 2014, Spring 2015)
  • Business Data Mining (IDS 472), Liautaud Graduate School of Business, University of Illinois at Chicago (Spring 2015)
  • Probability and Statistics for Business Application (36(70)-207), Tepper School of Business, Carnegie Mellon University (Summer 2013)

Research & Publications

Research Interests
  • Design and analysis of algorithms
  • Algorithms for convex optimization
  • Optimization in machine learning
  • Complexity and computation

 

Publications
  • A deterministic rescaled perceptron algorithm (with J. Pena). To Appear to Mathematical Programming.
  • J. Pena, N. Soheili, and V. Roshchina, "Some preconditioners for systems of linear inequalities", Optimization Letters 8 (2014) pp. 2145--2152.
  • N. Soheili and J. Pena, "A condition-based algorithm for solving polyhedral feasibility problems", Journal of Complexity 30 (2014) pp. 673--682.
  • N. Soheili and J. Pena, "A primal-dual smooth perceptron-von Neumann algorithm", Discrete Geometry and Optimization. Springer, Fields Institute Communications (2013). Volume 69, 303-320.
  • N. Soheili and J. Pena, "A smooth perceptron algorithm", SIAM Journal on Optimization 22 (2012) pp. 728--737.