As of July 2021, I'm a Sr. Applied AI Research Scientist at Intel's R&D division known as Intel TD (Technology Development).
I work on various aspects of statistical learning algorithms and their confluence with problems in highdimensional data analysis,
statistical pattern recognition, and computer vision. More broadly, I am interested in computational, statistical, and information(al)
aspects related to learning algorithms and learning from highdimensional data.
Topics I've worked on include (see publications below):
 Robust estimation of highdimensional covariance matrices for applications such as anomaly detection
and outofdistribution detection.
 Stability of learning algorithms for deriving strong guarantees on the generalization performance of
learning algorithms. In particular, I've worked on the concentration of risk estimates, developed in terms of LOOCV and KFCV,
around the expected risk of a learning algorithm under different notions of algorithmic stability.
 Dimensionality reduction and lowdimensional embedding; this includes supervised and unsupervised
algorithms for linear/nonlinear dimensionality reduction using models and techniques from discriminant analysis, kernel methods,
manifold learning algorithms, and graph embedding algorithms. This line of work was complemented with the development of scalable
and distributed algorithms for feature selection and interaction detection between predictor variables for regression and
classification problems during my time at SAS Inc.
 GenerativeDiscriminative models for timeseries data classification.
At Intel, I lead projects on (i) anomaly detection and outofdistribution detection for image data and highdimensional data
in general, and (ii) active learning from severely imbalanced datasets.

[Refereed Publications]

Karim AbouMoustafa
"Shrinkage Coefficient Estimation for Regularized Tyler's MEstimators: A LeaveOneOut Approach",
Proceedings of IEEE Information Theory Workshop (ITW), SaintMalo, France, pp. 335340, 2023.
[Online Link]
[BibTeX]
[PDF]

Karim AbouMoustafa and Csaba Szepesvári
"An Exponential EfronStein Inequality for Lq Stable Learning Rules",
Algorithmic Learning Theory (ALT), Proceedings of Machine Learning Research, Vol. 98, pp. 3163, 2019.
[Online Link]
[BibTeX]
[PDF]

Karim AbouMoustafa and Csaba Szepesvári
"An Exponential Tail bound for the Deleted Estimate",
ThirtyThird AAAI Conference on Artificial Intelligence, 2019.
[BibTeX]
[PDF]

Karim AbouMoustafa and Frank Ferrie
"Local Generalized Quadratic Distance Metrics: Application to the knearest neighbors classifier",
Journal of Advances in Data Analysis and Classification (ADAC), Vol. 12, No. 2, pp. 341363, 2018.
[Online Link]
[BibTeX]
[PDF]

Karim AbouMoustafa and Dale Schuurmans
"Generalization in Unsupervised Learning",
European Conference on Machine Learning (ECML), 2015.
[BibTeX]
[PDF]

Karim AbouMoustafa, Fernando De La Torre, and Frank Ferrie
"Pareto Models for Multiclass Discriminative Linear Dimensionality Reduction",
Pattern Recognition, Vol. 48, No. 5, pp. 18631877, 2015.
[BibTeX]
[PDF]

Karim AbouMoustafa, Dale Schuurmans, and Frank Ferrie
"Learning a Metric Space for Neighbourhood Topology Estimation",
Asian Conf. on Machine Learning, JMLR W&CP 29: pp. 341356, 2013.
[BibTeX]
[PDF]

Karim AbouMoustafa, Frank Ferrie and Dale Schuurmans
"Divergence Based Graph Estimation for Manifold Learning",
IEEE Global Conf. on Signal and Information Processing, Austin, TX, Dec. 2013.
[BibTeX]
[PDF]

Karim AbouMoustafa and Frank Ferrie,
"A Note on Metric Properties for Some Divergence Measures: The Gaussian Case",
Asian Conf. on Machine Learning, JMLR W&CP 25: pp. 115, 2012.
[BibTeX]
[PDF]

Karim AbouMoustafa and Frank Ferrie,
"Modified Divergence Measures for Gaussian Densities",
LNCS 7626, Proc. of the IAPR Int. Workshop on Structural, Syntactic, Statistical Pattern Recognition (S+SSPR),
pp. 426436, Springer 2012.
[BibTeX]
[PDF]

Karim AbouMoustafa and Frank Ferrie,
"A Framework for Hypothesis Learning Over Sets of Vectors",
Proc. of ACM's SIGKDD 9th Workshop on Mining and Learning with Graphs, 2011.
[BibTeX]
[PDF]

Karim AbouMoustafa, Mohak Shah, Fernando De La Torre, and Frank Ferrie,
"Relaxed Exponential Kernels for Unsupervised Learning",
LNCS 6835, Pattern Recognition, Proc. of the 33rd DAGM Symposium, pp. 184195, Springer, 2011.
[BibTeX]
[PDF]

Karim AbouMoustafa, Fernando De La Torre, and Frank Ferrie,
"Designing a Metric for the Difference Between Two Gaussian Densities",
Advances in Intelligent and Soft Computing;
J. Angeles, B. Boulet, J. Clark, J. Kovecses and K. Siddiqi (Eds.),
Vol. 83, pp. 57  70, Springer, Dec. 2010.
[BibTeX]
[PDF]

Karim AbouMoustafa, Fernando De La Torre, and Frank Ferrie,
"Pareto Discriminant Analysis",
IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 3602  3609, 2010.
[BibTeX]
[PDF]
[and here]

Karim AbouMoustafa and Frank Ferrie,
"Local Metric Learning on Manifolds with Applications to Querybased Operations",
LNCS 5342, Proc. of the IAPR Int. Workshop on Structural, Syntactic, Statistical Pattern Recognition (S+SSPR),
pp. 872  838, Springer, 2008.
[BibTeX]
[PDF]

Karim AbouMoustafa and Frank Ferrie,
"Fast and Regularized Local Metric for Querybased Operations",
IEEE Proc. of the 19th Int. Conf. on Pattern Recognition (ICPR), 2008.
[BibTeX]
[PDF]

Karim AbouMoustafa and Frank Ferrie,
"The Minimum Volume Ellipsoid Metric",
LNCS 4713, Pattern Recognition, Proc. of the 29th DAGM Symposium, pp. 335  344, Springer, 2007.
[BibTeX]
[PDF]

Karim AbouMoustafa, Mohamed Cheriet, and Ching Suen,
"Classification of TimeSeries Data Using a Generative/Discriminative Hybrid",
IEEE Proc. of the 9th Int. Workshop on Frontiers in Handwriting Recognition (IWFHR), pp. 51  56, 2004.
[BibTeX]
[PDF]

Karim AbouMoustafa, Mohamed Cheriet, and Ching Suen,
"A GenerativeDiscriminative Hybrid for Sequential Data Classification",
IEEE Proc. of the Int. Conf. on Acoustics, Speech & Signal Processing (ICASSP), Vol. 5, pp. 805  808, 2004.
[BibTeX]
[PDF]

Karim AbouMoustafa, Mohamed Cheriet, and Ching Suen,
"On The Structure of Hidden Markov Models",
Pattern Recognition Letters, Vol. 25, pp. 923  931, June 2004.
[BibTeX]
[PDF]
[NonRefereed Publications]

Karim AbouMoustafa and Csaba Szepesvári
"An a Priori Exponential Tail Bound for kFolds CrossValidation",
[arXiv:1706.05801], 2017.

Karim AbouMoustafa,
"What is The Distance Between Objects in a Data Set?",
IEEE Pulse Magazine, Vol. 7, No. 2, pp. 4147, MarchApril, 2016.
[BibTeX]
[link]

Karim AbouMoustafa,
"On Derivatives of Eigenvalues and Eigenvectors of the Generalized Eigenvalue Problem",
McGill Tech. Report No. TRCIM1009, 2009.
[BibTeX]
[PDF]
[Theses]

Karim T. AbouMoustafa,
"Metric Learning Revisited. New Approaches for Supervised and Unsupervised Metric Learning with Analysis
and Algorithms",
Ph.D. Thesis, McGill University, Montréal, QC, Canada, 2011.

Karim T. AbouMoustafa,
"A GenerativeDiscriminative Framework for TimeSeries Data Classification",
Masters Thesis, Concordia University, Montréal, QC, Canada, 2004.
