Alnur Ali

  • Program Year: 4
  • Academic Institution: Carnegie Mellon University
  • Field of Study: Machine Learning
  • Academic Advisor: Zico Kolter
  • Practicum(s):
    Lawrence Berkeley National Laboratory (2015)
  • Degree(s):
    B.S. Computer Science, University of Southern California, 2004
  • Personal URL:


9) The Generalized Lasso Problem and Uniqueness. Alnur Ali and Ryan J. Tibshirani. Presented at the Joint Statistical Meetings (JSM) 2017.

8) A Semismooth Newton Method for Fast, Generic Convex Programming. Alnur Ali, Eric Wong, and J. Zico Kolter. Proceedings of the 34th International Conference on Machine Learning (ICML), 2017.

7) Generalized Pseudolikelihood Methods for Inverse Covariance Estimation. Alnur Ali, Kshitij Khare, Sang-Yun Oh, Bala Rajaratnam. Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS), 2017.

6) The Multiple Quantile Graphical Model. Alnur Ali, J. Zico Kolter, and Ryan J. Tibshirani. Advances in Neural Information Processing Systems 29 (NIPS), 2016.

5) Disciplined Convex Stochastic Programming: A New Framework for Stochastic Optimization. Alnur Ali, J. Zico Kolter, Steven Diamond, and Stephen Boyd. Proceedings of 31st Conference on Uncertainty in Artificial Intelligence (UAI), 2015.

4) Active Learning with Model Selection. Alnur Ali, Rich Caruana, and Ashish Kapoor. Proceedings of 28th AAAI Conference on Artificial Intelligence (AAAI), 2014.

3) Learning Lexicon Models from Search Logs for Query Expansion. Jianfeng Gao, Shasha Xie, Xiaodong He, and Alnur Ali. Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), 2012.

2) Experiments with Kemeny Ranking: What Works When? Alnur Ali and Marina Meila. Mathematical Social Sciences, 2012.

1) Preferences in College Applications: a Nonparametric Bayesian Analysis of Top-10 Rankings. Alnur Ali, Thomas Brendan Murphy, Marina Meila, and Harr Chen. Proceedings of the Neural Information Processing Systems 23 (NIPS) Workshop on Computational Social Science, 2010.


- 2016: Interviewed on a podcast by the World Affairs Council; podcast title: "Big Data for Social Good"
- 2016: Steering committee member for a workshop at NIPS (a top machine learning conference); workshop title: "Interpretable Machine Learning for Complex Systems"
- 2016: Reviewer for Biometrika (a top statistics journal)
- 2016: Reviewer for JMLR (a top machine learning journal)
- 2015-present: Reviewer for NIPS
- 2015-present: Reviewer for ICML (a top machine learning conference)
- 2015-present: Reviewer for AISTATS (a top machine learning conference)
- 2014-present: received a Dept. of Energy Computational Science Graduate Fellowship
- 2012: received a President's Volunteer Service Award at the AmeriCorps silver level (for teaching & service)
- 2011: Reviewer for SIGIR (a top information retrieval conference)
- 2009: received a Vice President's Gold Star Award at Microsoft 3 times (for various technical achievements)
- 2003-2004: received a Langston Scholarship at USC
- 2002-2004: member of Tau Beta Pi at USC (an engineering honor society)
- 2000-2004: was on the Dean's List at USC (for academic achievement)
- 2002: received a Schaefer Scholarship at USC