Brief Bio

Mourad Khayati is a Senior researcher at the Department of Computer Science of the University of Fribourg, Switzerland. He did his PhD at University of Zurich, Switzerland, under the supervision of Prof. Michael Böhlen. He is leading the technical committee of the H2020 European project FashionBrain and is the principal investigator of the D-A-CH ProvDS project.

Research Interests

Time Series, recovery of missing values, and matrix decomposition techniques.

Current Projects

• FashionBrain (H2020 European project):
  • Role: Technical lead
  • Period: 1.1.2017-31.12.2019
• ProvDS (D-A-CH project):
  • Role: Principal investigator
  • Period: 1.06.2018-31.05.2020

Tools

• ReviVal: Recovery of Missing Blocks in Time Series Data (paper, ICDE’14)
• RecovDB: Recovery of Missing Values inside a Database (paper, ICDE’19)

Teaching

• Spring 2019: Social Media Analytics
• Fall 2018: Data Science Seminar
  • Topic: Graph Embedding
• Spring 2018: Social Media Analytics
• Fall 2017: Data Science Seminar
  • Topic: Social Networks
• Spring 2017: Social Media Analytics
• Fall 2016: Data Science Seminar
  • Topic: Predictive Analytics
• Fall 2015: Data Science Seminar
  • Topic: Scalable Machine Learning

Student Projects

• Available proposals:
  • MSc Thesis: Real-time Clustering of Time Series Streams (open).
  • BSc/MSc Thesis: Time series prediction using latent space (taken).
• Completed Thesis:
  • MSc Thesis: Trend prediction using fashion datasets.
  • MSc Thesis: Correlation-based LISA anomaly detection for time series.
  • MSc Thesis: Graphical Interface for Real Time Recovery of Missing Values.
  • MSc Thesis: Centroid Decomposition using Big Data Platforms (completed).

Selected Publications

• DBLP server.
• Internal Server:

1. Artem Lutov, Mourad Khayati, and Philippe Cudré-Mauroux. “Accuracy Evaluation of Overlapping and Multi-Resolution Clustering Algorithms on Large Datasets.” In Proceedings of the 6th IEEE International Conference on Big Data and Smart Computing (BigComp 2019), 2019. Bibtex PDF

   Accuracy Evaluation of Overlapping and Multi-resolution Clustering Algorithms on Large Datasets

   Artem Lutov, Mourad Khayati, and Philippe Cudré-Mauroux. “Accuracy Evaluation of Overlapping and Multi-Resolution Clustering Algorithms on Large Datasets.” In Proceedings of the 6th IEEE International Conference on Big Data and Smart Computing (BigComp 2019), 2019.

   @inproceedings{lutov19bigcomp,
     title = {Accuracy Evaluation of Overlapping and Multi-resolution Clustering Algorithms on Large Datasets},
     author = {Lutov, Artem and Khayati, Mourad and Cudré-Mauroux, Philippe},
     booktitle = {Proceedings of the 6th IEEE International Conference on Big Data and Smart Computing (BigComp 2019)},
     year = {2019},
     url = {https://exascale.info/assets/pdf/bigcomp19r2-xmeasures.pdf}
   }
   

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2. Ines Arous, Mourad Khayati, Philippe Cudré-Mauroux, Ying Zhang, Martin Kersten, and Svetlin Stalinlov. “RecovDB: Accurate and Efficient Missing Blocks Recovery for Large Time Series.” In 35th IEEE International Conference on Data Engineering (ICDE 2019). Macau, China, 2019. Bibtex PDF Source Code Poster Tool

   RecovDB: accurate and efficient missing blocks recovery for large time series

   Ines Arous, Mourad Khayati, Philippe Cudré-Mauroux, Ying Zhang, Martin Kersten, and Svetlin Stalinlov. “RecovDB: Accurate and Efficient Missing Blocks Recovery for Large Time Series.” In 35th IEEE International Conference on Data Engineering (ICDE 2019). Macau, China, 2019.

   @inproceedings{recovdb2019,
     title = {RecovDB: accurate and efficient missing blocks recovery for large time series},
     author = {Arous, Ines and Khayati, Mourad and Cudr{\'e}-Mauroux, Philippe and Zhang, Ying and Kersten, Martin and Stalinlov, Svetlin},
     booktitle = {35th IEEE International Conference on Data Engineering (ICDE 2019)},
     year = {2019},
     address = {Macau, China},
     url = {https://exascale.info/assets/pdf/recovdb19.pdf},
     code = {https://github.com/eXascaleInfolab/2018-RecovDB},
     poster = {https://exascale.info/assets/pdf/recovdb2019poster.pdf},
     tool = {http://revival.exascale.info}
   }
   

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3. Artem Lutov, Soheil Roshankish, Mourad Khayati, and Philippe Cudré-Mauroux. “StaTIX - Statistical Type Inference on Linked Data.” In IEEE International Conference on Big Data, Big Data 2018, Seattle, WA, USA, December 10-13, 2018, 2253–62, 2018. Bibtex PDF

   StaTIX - Statistical Type Inference on Linked Data

   Artem Lutov, Soheil Roshankish, Mourad Khayati, and Philippe Cudré-Mauroux. “StaTIX - Statistical Type Inference on Linked Data.” In IEEE International Conference on Big Data, Big Data 2018, Seattle, WA, USA, December 10-13, 2018, 2253–62, 2018.

   @inproceedings{statix18,
     author = {Lutov, Artem and Roshankish, Soheil and Khayati, Mourad and Cudr{\'{e}}{-}Mauroux, Philippe},
     title = {StaTIX - Statistical Type Inference on Linked Data},
     booktitle = {{IEEE} International Conference on Big Data, Big Data 2018, Seattle, WA, USA, December 10-13, 2018},
     pages = {2253--2262},
     year = {2018},
     doi = {10.1109/BigData.2018.8622285},
     url = {https://exascale.info/assets/pdf/bigdata18_statix.pdf}
   }
   

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4. Artem Lutov, Mourad Khayati, and Philippe Cudré-Mauroux. “Clubmark: A Parallel Isolation Framework for Benchmarking and Profiling Clustering Algorithms on NUMA Architectures.” In 2018 IEEE International Conference on Data Mining Workshops, ICDM Workshops, Singapore, Singapore, November 17-20, 2018, 1481–86, 2018. Bibtex Slides PDF

   Clubmark: A Parallel Isolation Framework for Benchmarking and Profiling Clustering Algorithms on NUMA Architectures

   Artem Lutov, Mourad Khayati, and Philippe Cudré-Mauroux. “Clubmark: A Parallel Isolation Framework for Benchmarking and Profiling Clustering Algorithms on NUMA Architectures.” In 2018 IEEE International Conference on Data Mining Workshops, ICDM Workshops, Singapore, Singapore, November 17-20, 2018, 1481–86, 2018.

   @inproceedings{clubmark18,
     author = {Lutov, Artem and Khayati, Mourad and Cudr{\'{e}}{-}Mauroux, Philippe},
     title = {Clubmark: {A} Parallel Isolation Framework for Benchmarking and Profiling Clustering Algorithms on {NUMA} Architectures},
     booktitle = {2018 {IEEE} International Conference on Data Mining Workshops, {ICDM} Workshops, Singapore, Singapore, November 17-20, 2018},
     pages = {1481--1486},
     year = {2018},
     doi = {10.1109/ICDMW.2018.00212},
     url = {https://exascale.info/assets/pdf/icdm18_clubmark.pdf},
     note = {https://www.slideshare.net/ArtemVL/clubmark-a-parallel-isolation-framework-for-benchmarking-and-profiling-clustering-algorithms-icdm18-demo-poster}
   }
   

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5. Andrea Martini, Artem Lutov, Valerio Gemmetto, Andrii Magalich, Alessio Cardillo, Alex Constantin, Vasyl Palchykov, et al. “ScienceWISE: Topic Modeling over Scientific Literature Networks.” ArXiv e-Prints, 2016. Bibtex PDF

   ScienceWISE: Topic Modeling over Scientific Literature Networks

   Andrea Martini, Artem Lutov, Valerio Gemmetto, Andrii Magalich, Alessio Cardillo, Alex Constantin, Vasyl Palchykov, et al. “ScienceWISE: Topic Modeling over Scientific Literature Networks.” ArXiv e-Prints, 2016.

   @article{ScienceWISE16a,
     title = {ScienceWISE: Topic Modeling over Scientific Literature Networks},
     author = {Martini, Andrea and Lutov, Artem and Gemmetto, Valerio and Magalich, Andrii and Cardillo, Alessio and Constantin, Alex and Palchykov, Vasyl and Khayati, Mourad and Cudré-Mauroux, Philippe and Boyarsky, Alexey and Ruchayskiy, Oleg and Garlaschelli, Diego and Rios, Paolo De Los and Aberer, Karl},
     journal = {ArXiv e-prints},
     archiveprefix = {arXiv},
     eprint = {1612.07636},
     primaryclass = {cs.DL},
     url = {https://arxiv.org/pdf/1612.07636},
     year = {2016}
   }
   

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6. Laura Rettig, Mourad Khayati, Philippe Cudré-Mauroux, and Michal Piorkowski. “Online Anomaly Detection over Big Data Streams.” In 2015 IEEE International Conference on Big Data, Big Data 2015, Santa Clara, CA, USA, Oct 27- Nov 01, 2015. Bibtex PDF

   Online Anomaly Detection over Big Data Streams

   Laura Rettig, Mourad Khayati, Philippe Cudré-Mauroux, and Michal Piorkowski. “Online Anomaly Detection over Big Data Streams.” In 2015 IEEE International Conference on Big Data, Big Data 2015, Santa Clara, CA, USA, Oct 27- Nov 01, 2015.

   @inproceedings{OnlineAnomaly,
     author = {Rettig, Laura and Khayati, Mourad and Cudr{\'e}-Mauroux, Philippe and Piorkowski, Michal},
     title = {Online Anomaly Detection over Big Data Streams},
     booktitle = {2015 {IEEE} International Conference on Big Data, Big Data 2015, Santa Clara, CA, USA, Oct 27- Nov 01},
     year = {2015},
     url = {https://exascale.info/assets/pdf/Rettig_BigData-15.pdf}
   }
   

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7. Mourad Khayati, Philippe Cudré-Mauroux, and Michael H. Böhlen. “Using Lowly Correlated Time Series to Recover Missing Values in Time Series: a Comparison between SVD and CD.” In Advances in Spatial and Temporal Databases - 15th International Symposium, SSTD 2015, Seoul, South Korea, August 26-28, 2015. Proceedings, 2015. Bibtex PDF

   Using Lowly Correlated Time Series to Recover Missing Values in Time Series: a Comparison between SVD and CD

   Mourad Khayati, Philippe Cudré-Mauroux, and Michael H. Böhlen. “Using Lowly Correlated Time Series to Recover Missing Values in Time Series: a Comparison between SVD and CD.” In Advances in Spatial and Temporal Databases - 15th International Symposium, SSTD 2015, Seoul, South Korea, August 26-28, 2015. Proceedings, 2015.

   @conference{DBLP:conf/ssd/KhMB15,
     title = {Using Lowly Correlated Time Series to Recover Missing Values in Time Series: a Comparison between SVD and CD},
     booktitle = {Advances in Spatial and Temporal Databases - 15th International Symposium, {SSTD} 2015, Seoul, South Korea, August 26-28, 2015. Proceedings},
     year = {2015},
     author = {Khayati, Mourad and Cudr{\'e}-Mauroux, Philippe and B{\"o}hlen, Michael H.},
     url = {https://exascale.info/assets/pdf/khayati_sstd15.pdf}
   }
   

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8. Mourad Khayati, Michael H. Böhlen, and Johann Gamper. “Memory-Efficient Centroid Decomposition for Long Time Series.” In IEEE 30th International Conference on Data Engineering, Chicago, ICDE 2014, IL, USA, March 31 - April 4, 2014, 100–111, 2014. Bibtex PDF

   Memory-efficient centroid decomposition for long time series

   Mourad Khayati, Michael H. Böhlen, and Johann Gamper. “Memory-Efficient Centroid Decomposition for Long Time Series.” In IEEE 30th International Conference on Data Engineering, Chicago, ICDE 2014, IL, USA, March 31 - April 4, 2014, 100–111, 2014.

   @conference{DBLP:conf/icde/KhayatiBG14,
     title = {Memory-efficient centroid decomposition for long time series},
     booktitle = { {IEEE} 30th International Conference on Data Engineering, Chicago, {ICDE} 2014, IL, USA, March 31 - April 4, 2014},
     year = {2014},
     pages = {100{\textendash}111},
     doi = {10.1109/ICDE.2014.6816643},
     url = {https://exascale.info/assets/pdf/khayati_ICDE14.pdf},
     author = {Khayati, Mourad and B{\"o}hlen, Michael H. and Gamper, Johann}
   }
   

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9. Mourad Khayati, and Michael H. Böhlen. “REBOM: Recovery of Blocks of Missing Values in Time Series.” In Proceedings of the 18th International Conference on Management of Data, COMAD 2012, 2012, Pune, India, 44–55, 2012. Bibtex PDF

   REBOM: Recovery of Blocks of Missing Values in Time Series

   Mourad Khayati, and Michael H. Böhlen. “REBOM: Recovery of Blocks of Missing Values in Time Series.” In Proceedings of the 18th International Conference on Management of Data, COMAD 2012, 2012, Pune, India, 44–55, 2012.

   @conference{DBLP:conf/comad/KhayatiB12,
     title = {REBOM: Recovery of Blocks of Missing Values in Time Series},
     booktitle = {Proceedings of the 18th International Conference on Management of Data, {COMAD} 2012, 2012, Pune, India},
     year = {2012},
     pages = {44{\textendash}55},
     url = {https://exascale.info/assets/pdf/khayati_comad12.pdf},
     author = {Khayati, Mourad and B{\"o}hlen, Michael H.}
   }
   

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• PhD Thesis: Mourad Khayati. Recovery of Missing Values using Matrix Decomposition Techniques, University of Zurich, Switzerland. PDF