Dan Kushnir

Ph.D. in Applied Mathematics, Thesis: Multiscale tools for data analysis, Advisors: Prof. Achi Brandt and Prof. Edriss Titi, Weizmann Institute of Science, Rehovot, Israel. 2004-2008

M.Sc. in Applied Mathematics, Thesis: A fast multi-scale clustering algorithm with application to cold and dark matter simulations, Advisor: Prof. Achi Brandt, Weizmann Institute of Science, Rehovot,Israel, 2001-2004

B.Sc. in Computer Science, The Hebrew University, Jerusalem, Israel, 1997-2001

Member of the Center for Discrete Mathematics and Computer Science (DIMACS) at Rutgers University

Organizer of the Applied Mathematics Seminar at Yale University

Member of the Society of Industrial and Applied Mathematics (SIAM)

Review Writer for Mathematical Reviews (MR) of the American Mathematical Society (AMS)

PhD thesis examiner

Reviewer in the following journals:

• IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI)
• Applied and Computational Harmonic Analysis (ACHA)
• SIAM Journal on Scientific Computing (SISC)
• Journal of Machine Learning Research (JMLR)
• Numerical Linear Algebra
• Journal of Global Optimization
• Bell Labs Technical Journal
• Computer Communications (Elsevier)
• IEEE Signal Processing Letters
• IEEE Intelligent Systems

D. Kushnir, S. Jalali, I. Saniee, Linear Time Clustering for High Dimensional Mixtures of Gaussian Clouds, submitted

V. Gurbani, D. Kushnir, V. Mendiratta, C. Phadke, E. Falk, R. State, Detecting and Predicting Outage in Mobile Networks with Log Data, ICC, 2017

D. Kushnir, M. Goldstein, Causality inference for Failures in NFV, INFOCOM workshops, 929-934 ,2016

A. Akyamac, C. Phadke, D. Kushnir, H. Uzunalioglu, Predicting Home Network Problems Using Diverse Data, Sarnoff Symposium, 1-6, 2015

D. Kushnir, Efficient Active Learning with Label-Adapted Kernels, ACM 20th conference on Knowledge Discovery and Data Mining (ACM SIGKDD 2014), NYC.  

C. Phadke, H. Uzunalioglu, V. Mendiratta, D. Kushnir, D. Doran, Prediction of Subscriber Churn Using Social Network Analysis, Bell Labs Technical Journal, (BLTJ), 17(4), 63-75, 2013  

R. Talmon, D. Kushnir, R. R. Coifman, Israel Cohen, Sharon Gannot, Parametrization of Linear Systems Using Diffusion Kernels, IEEE Transactions on Signal Processing, 60(3), (2012) 

A. Haddad, D. Kushnir, R. R. Coifman, Filtering via a reference set, revised for Applied and Computational Harmonic Analysis (ACHA) (2011)  

D. Kushnir, A. Haddad, R. R. Coifman, Anisotropic diffusion on sub-manifolds with application to
Earth structure classification, Applied and Computational Harmonic Analysis (ACHA), 32(2), 280–294 (2012) 

D. Kushnir, V. Rokhlin, A highly accurate stiff ODEs solver, SIAM Journal on Scientific Computing
(SISC), 34(3), 1296–1315 (2012) 

D. Kushnir, M. Galun, A. Brandt, Efficient multilevel eigensolvers with applications to data analysis tasks, IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI), vol. 32(8), 1377–1391 (2010)  

Y. Goldberg, A. Zakai, D. Kushnir, Y. Ritov, Manifold Learning: the price of normalization, Journal of Machine Learning Research (JMLR), vol. 9, 1909-1939 (2008)  

D. Kushnir, M. Galun, A. Brandt, Fast multiscale clustering and manifold identification, special issue on similarity-based pattern recognition, Pattern Recognition, 39(10), 1876–1891 (2006)  

D. Kushnir, J. Schumacher, A. Brandt, Geometry of intensive scalar dissipation events in turbulence, Physical Review Letters 97, 124502 (2006) (cover page)  

J. Schumacher, D. Kushnir, A. Brandt, K. R. Sreenivasan, and H. Zilken, Statistics and geometry in high-Schmidt number scalar mixing, Proceedings of the iTi Conference in Turbulence, Progress in Turbulence II, Springer Proceedings in Physics (2005)

NC104131 Actively Learning Smooth Functions, filed

NC103295 Active Learning Framework and Architecture for IoT Analytics Services, filed

820588-EP-EPA A Method for Identifying Causality Objects, filed

818893-US-NP Alarm Causality Templates for Network Function Virtualization

816508-US-NP Root Cause Analysis For Service Degradation In Computer Networks (US9424121)

818347-US-NP Optimized Radio Frequency Signal Strength Sampling Of A Broadcast Area For Device Localization, (US9571976)

812168US-NP System and Method for Generating Subscriber Churn Predictions, (US8804929)

814019US-NP Data Classifier Using Proximity Graphs, Edge Weights, And Propagation Labels (US20140317034)

814359US-NP Adaptive Polling of Information from a Device (US9032119)

810349US-NP Method and Apparatus for Deriving Composite Tie Metric for Edge Between Nodes of Telecommunication Call Graph, (US9159077)

815307-US-NP Classification Of Device Problems Of Customer Premises Devices, (US20150278823)

Distinguished Member of Technical Staff, 2017

Eshkol scholarship - 200,000 NIS for two years postdoctoral research on fast numerical algorithms for machine learning tasks, 2011

Full funding for participation in the workshop on Large Graphs: Modeling, Algorithms and Applications/Mathematics of Information, Institute for Mathematics and its Application (IMA), University of Minnesota, 2011

Full funding for participation in the workshop on High Dimensional Phenomena/Mathematics of
Information, Institute for Mathematics and its Application (IMA), University of Minnesota, 2011

Full funding from the Hausdorff Research Institute for Mathematics at Bonn University, Germany, for giving a talk and participation in the workshop on Manifold Learning, 2011 

Society for Industrial and Applied Mathematics (SIAM) early career travel award, 2009 

Full funding for participation in the workshop on Multi-Manifold Data Modeling and Applications, Institute for Mathematics and its Application (IMA), University of Minnesota, 2008