Hassan Ashtiani

David Cheriton School of Computer Science
University of Waterloo
Office: DC3519
mhzokaei at uwaterloo.ca

I study computer science as a PhD student at University of Waterloo. Broadly speaking, my research interest is machine learning. I am advised by Professor Shai Ben-David.

A Nice Photo of Mine

Current Research

I am interested to extend the classical results of learning theory to non-standard learning tasks -- e.g., clustering and semi-supervised learning. This can involve defining a learning model, making assumptions about the task/data, and studying the computational, statistical and information-theoretic aspects of learning in that model.


  1. Sample-Efficient Learning of Mixtures [paper]
    Hassan Ashtiani, Shai Ben-David, Abbas Mehrabian
    Under Review

  2. Online Nearest Neighbor Search in Hamming Space
    Sepehr Eghbali, Hassan Ashtiani, Ladan Tahvildari
    Accepted for ICDM'17

  3. Clustering with Same-Cluster Queries [paper, slides, video]
    Hassan Ashtiani, Shrinu Kushagra, Shai Ben-David
    NIPS 2016, Oral Presenattion

  4. A Dimension-Independent Generalization Bound for Kernel Supervised Principal Component Analysis [paper]
    Hassan Ashtiani, Ali Ghodsi
    JMLR Workshop and Conference Proceedings, Volume 44: NIPS Workshop on Feature Extraction: Modern Questions and Challenges, 2015

  5. Representation Learning for Clustering: A Statistical Framework [paper, poster, presentation]
    Hassan Ashtiani, Shai Ben-David
    UAI 2015, Oral Presnetation

  6. Bandit-Based Local Feature Subset Selection [paper]
    Hassan Ashtiani, Majid Nili Ahmadabadi, Babak Nadjar Araabi
    Neurocomputing, 2014

  7. Bandit-Based Structure Learning for Bayesian Network Classifiers [paper]
    Sepehr Eghbali, Hassan Ashtiani, Majid Nili Ahmadabadi, Babak Nadjar Araabi
    ICONIP, 2012

  8. Assessment of input variables determination on the SVM model performance using PCA, Gamma test, and forward selection techniques for monthly stream flow prediction [paper]
    Noori, R., A. R. Karbassi, A. Moghaddamnia, D. Han, Hassan Ashtiani, A. Farokhnia, and M. Ghafari Gousheh
    Journal of Hydrology, 2011

  9. A Disaster Invariant Feature for Localization [paper]
    Behdad Soleimani, Hassan Ashtiani, Behrouz Haji Soleimani, Hadi Moradi
    IROS, 2010

  10. An attention-based approach for learning how to fuse decisions of local experts
    Maryam S. Mirian, Majid Nili Ahmadabadi, Babak Nadjar Araabi and Hassan Ashtiani
    NIPS Workshop on Understanding Multiple Kernel Learning Methods, 2009

  11. Graph signature for self-reconfiguration planning of modules with symmetry [paper]
    Masoud Asadpour, Hassan Ashtiani, Alexander Sprowitz, Auke Ijspeert
    IROS, 2009


  • I did an internship at Google (Winter 2017).
  • Watch my talk on "Clustering with same-cluster queries" at NIPS'16.
  • I was awarded the Cheriton Scholarship for 2016-2017.
  • I was invited to give a talk about Clustering with Advice at university of Tehran, December 2015 [Presentation]
  • Check out my guest lectures for the machine learning course at UWaterloo [Lecture 5, Lecture 6]
  • Thanks to Zokaei part of my last name, I was the last name in the list of reviewers for COLT'14 and COLT'15 :-) [2014, 2015]
  • I had an invited talk about ''distribution specific learnability'' at university of Tehran, December 2013 [Slides]
  • I got Cheriton Scholarship (Type II) for 2012 to 2014