My name is Mickey Gabel, a researcher in the Computer Science Department at the Technion. I recently finished my Ph.D. in Computer Science. My advisors were Assaf Schuster and Danny Keren.

My research interests include machine learning and data mining in distributed settings, and applications on systems research. I work on learning and monitoring models of large, distributed data streams. I've also worked on deep neural network compression and runtime optimization, monitoring health of cloud datacenters and other large distributed systems, analyzing storage logs for SSD, and clinical gait analysis.

I also have extensive professional background on diverse platforms and fields from my days in the industry.

Refereed Publications

  • Anarchists, Unite: Practical Entropy Approximation for Distributed Streams. M. Gabel, D. Keren, and A. Schuster. 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017.
    [full text] [3 minute video]
  • One for All and All for One: Simultaneous Approximation of Multiple Functions over Distributed Streams. A. Lazerson, M. Gabel, D. Keren, and A. Schuster. 11th ACM International Conference on Distributed and Event-Based Systems (DEBS), 2017.
    [full text]
  • On the Equivalence of the LC-KSVD and the D-KSVD Algorithms. I. Kviatkovsky, M. Gabel, E. Rivlin, and I. Shimshoni. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 39(2):411-416, 2017.
    [full text]
  • Avoiding the Streetlight Effect: I/O Workload Analysis with SSDs in Mind. G. Yadgar, M. Gabel. 8th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage), 2016.
    [full text]
  • Monitoring Least Squares Models of Distributed Streams. M. Gabel, D. Keren, and A. Schuster. 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2015.
    [full text]
  • Latent Fault Detection With Unbalanced Workloads. M. Gabel, K. Sato, D. Keren, S. Matsuoka, and A. Schuster. Event Processing, Forecasting and Decision-Making in the Big Data Era (EPForDM) workshop, held in conjunction with EDBT, 2015.
    [full text]
  • Communication-efficient Distributed Variance Monitoring and Outlier Detection for Multivariate Time Series. M. Gabel, D. Keren, and A. Schuster. 28th IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2014.
    [full text]
  • Communication-efficient Outlier Detection for Scale-out Systems. M. Gabel, D. Keren, and A. Schuster. First International Workshop on Big Dynamic Distributed Data (BD3), held at the 39th International Conference on Very Large Data Bases (VLDB), 2013.
  • Full Body Gait Analysis With Kinect. M. Gabel, R. Gilad-Bachrach, E. Renshaw, and A. Schuster. 34th Annual International Conference of the IEEE in Engineering in Medicine and Biology Society (EMBC), 2012.
    [full text]
  • Latent Fault Detection in Large Scale Services. M. Gabel, A. Schuster, R.-G. Bachrach, and N. Bjørner. 42nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), 2012.
    [full text] [master thesis]

Academic Activities

...include reviewing conference papers, participation in EU research projects, internships at Microsoft Research, and some talks.

Contact me for a full CV.

Teaching Assistant

Industry Experience

In past life, I was a professional software developer for 10 years.

My experience includes embedded development, computer graphics, file system and kernel development, DSP development, image processing, and more. The range of duties is similarly diverse: coding, algorithm R&D, API design, performance optimization, management roles, and project planning.

Contact me for a full CV.


The best way is email.