Negar Soheili
Associate Professor
Department of Information and Decision Sciences
Contact
Building & Room:
UH 2416
Office Phone:
Email:
About
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 Interests
- Design and analysis of algorithms
- Algorithms for convex optimization
- Optimization in machine learning
- Complexity and computation
Selected 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.
Education
PhD in Operations Research at the Tepper School of Business, Carnegie Mellon University