Brief Bio

Mourad Khayati is a Senior Researcher and a Senior Lecturer (Maitre Assistant–Oberassistent) respectivey with the eXascale Infolab group and the Advanced Software Engineering group at the Department of Computer Science of the University of Fribourg, Switzerland. He obtained his PhD from the University of Zurich, Switzerland, under the supervision of Prof. Michael Böhlen. His research interests include Time Series analytics and data cleaning/repair with a special focus on recovery of missing values. His ImputeBench benchmark on missing values recovery in time series won the VLDB 2020 Most Reproducible Paper Award.

Open Source Software

• Time Series Repair :
  • ORBITS : Online Recovery of Missing Values in Time Series Streams [PDF (pvldb’21) | code | repro | GUI]
  • ImputeBench : Time Series Imputation Benchmark [PDF (pvldb’20) | code | repro]
  • RecovDB : Time Series Repair inside MonetDB [PDF (icde’19) | code | GUI ]
  • CDRec : Recovery of Missing Blocks in Time Series [PDF (kais’20) | code | repro | GUI]
• Time Series Analytics :
  • VADETIS : Explainable Evaluator for Anomaly Detection [PDF (icde’21) | GUI]
  • CORAD : Correlation-Aware Compression of Massive Time Series Using Sparse Dictionary Coding [PDF (BigData’19) | code]

Teaching & Projects

• Teaching:
  • Spring 2022:
    • Social Media Analytics (MSc)
  • Fall 2021:
    • Data Science Seminar (MSc)
    • Advanced Software Engineering (MSc)
• Projects:
  • ProvDS (D-A-CH project): Main lead, 1.06.2018-31.05.2021
  • FashionBrain (H2020 European project), Technical lead, 1.1.2017-31.12.2019

Selected Publications (DBLP)

1. Ines Arous, Jie Yang, Mourad Khayati, and Philippe Cudré-Mauroux. “Peer Grading the Peer Reviews: A Dual-Role Approach for Lightening the Scholarly Paper Review Process.” In Proceedings of the Web Conference (WWW 2021). Ljubljana, Slovenia, 2021. Bibtex PDF Code

   Peer Grading the Peer Reviews: A Dual-Role Approach for Lightening the Scholarly Paper Review Process

   Ines Arous, Jie Yang, Mourad Khayati, and Philippe Cudré-Mauroux. “Peer Grading the Peer Reviews: A Dual-Role Approach for Lightening the Scholarly Paper Review Process.” In Proceedings of the Web Conference (WWW 2021). Ljubljana, Slovenia, 2021.

   @inproceedings{arous2021www,
     title = {Peer Grading the Peer Reviews: A Dual-Role Approach for Lightening the Scholarly Paper Review Process},
     author = {Arous, Ines and Yang, Jie and Khayati, Mourad and Cudr{\'e}-Mauroux, Philippe},
     booktitle = {Proceedings of the Web Conference (WWW 2021)},
     year = {2021},
     address = {Ljubljana, Slovenia},
     url = {https://exascale.info/assets/pdf/arous2021www.pdf},
     code = {https://github.com/eXascaleInfolab/pgpr}
   }
   

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2. Abdelouahab Khelifati, Mourad Khayati, Philippe Cudré-Mauroux, Adrian Hänni, Qian Liu, and Manfred Hauswirth. “VADETIS: An Explainable Evaluator for Anomaly Detection Techniques.” In Proceedings of the IEEE International Conference on Data Engineering (ICDE 2021). Demo Track. Greece, 2021. Bibtex PDF Code

   VADETIS: An Explainable Evaluator for Anomaly Detection Techniques

   Abdelouahab Khelifati, Mourad Khayati, Philippe Cudré-Mauroux, Adrian Hänni, Qian Liu, and Manfred Hauswirth. “VADETIS: An Explainable Evaluator for Anomaly Detection Techniques.” In Proceedings of the IEEE International Conference on Data Engineering (ICDE 2021). Demo Track. Greece, 2021.

   @inproceedings{khelifati2021icde,
     title = {VADETIS: An Explainable Evaluator for Anomaly Detection Techniques},
     author = {Khelifati, Abdelouahab and Khayati, Mourad and Cudr{\'{e}}{-}Mauroux, Philippe and Hänni, Adrian and Liu, Qian and Hauswirth, Manfred},
     booktitle = {Proceedings of the IEEE International Conference on Data Engineering (ICDE 2021). Demo Track},
     year = {2021},
     address = {Greece},
     url = {https://exascale.info/assets/pdf/vadetis-icde2021.pdf},
     code = {https://github.com/eXascaleInfolab/vadetis.git}
   }
   

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3. Mourad Khayati, Ines Arous, Zakhar Tymchenko, and Philippe Cudré-Mauroux. “ORBITS: Online Recovery of Missing Blocks in Multiple Time Series Streams.” In Proceedings of the VLDB Endowment, Vol. 14, 2021. Bibtex PDF Code Poster

   ORBITS: Online Recovery of Missing Blocks in Multiple Time Series Streams

   Mourad Khayati, Ines Arous, Zakhar Tymchenko, and Philippe Cudré-Mauroux. “ORBITS: Online Recovery of Missing Blocks in Multiple Time Series Streams.” In Proceedings of the VLDB Endowment, Vol. 14, 2021.

   @inproceedings{khayati2021vldb,
     author = {Khayati, Mourad and Arous, Ines and Tymchenko, Zakhar and Cudr{\'{e}}{-}Mauroux, Philippe},
     title = {ORBITS: Online Recovery of Missing Blocks in Multiple Time Series Streams},
     booktitle = {Proceedings of the VLDB Endowment},
     volume = {14},
     number = {3},
     year = {2021},
     code = {https://github.com/eXascaleInfolab/orbits},
     poster = {https://exascale.info/assets/pdf/khayati2021vldb_poster.pdf},
     url = {http://www.vldb.org/pvldb/vol14/p294-khayati.pdf}
   }
   

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4. Mourad Khayati, Philippe Cudré-Mauroux, and Michael H. Böhlen. “Scalable Recovery of Missing Blocks in Time Series with High and Low Cross-Correlations.” In International Journal of Knowledge and Information Systems (KAIS), 2020. Bibtex PDF Code

   Scalable Recovery of Missing Blocks in Time Series with High and Low cross-Correlations

   Mourad Khayati, Philippe Cudré-Mauroux, and Michael H. Böhlen. “Scalable Recovery of Missing Blocks in Time Series with High and Low Cross-Correlations.” In International Journal of Knowledge and Information Systems (KAIS), 2020.

   @inproceedings{khayati2020kais,
     author = {Khayati, Mourad and Cudr{\'e}-Mauroux, Philippe and B{\"o}hlen, Michael H.},
     title = {Scalable Recovery of Missing Blocks in Time Series with High and Low cross-Correlations},
     booktitle = {International Journal of Knowledge and Information Systems (KAIS)},
     year = {2020},
     url = {https://rdcu.be/b32bv},
     code = {https://github.com/eXascaleInfolab/2019_kais-bench}
   }
   

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5. Mourad Khayati, Alberto Lerner, Zakhar Tymchenko, and Philippe Cudré-Mauroux. “Mind the Gap: An Experimental Evaluation of Imputation of Missing Values Techniques in Time Series.” In Proceedings of the VLDB Endowment, Vol. 13, 2020. Bibtex PDF Code Award

   Mind the Gap: An Experimental Evaluation of Imputation of Missing Values Techniques in Time Series

   Mourad Khayati, Alberto Lerner, Zakhar Tymchenko, and Philippe Cudré-Mauroux. “Mind the Gap: An Experimental Evaluation of Imputation of Missing Values Techniques in Time Series.” In Proceedings of the VLDB Endowment, Vol. 13, 2020.

   @inproceedings{khayati2020vldb,
     author = {Khayati, Mourad and Lerner, Alberto and Tymchenko, Zakhar and Cudr{\'{e}}{-}Mauroux, Philippe},
     title = {Mind the Gap: An Experimental Evaluation of Imputation of Missing Values Techniques in Time Series},
     booktitle = {Proceedings of the VLDB Endowment},
     volume = {13},
     number = {5},
     year = {2020},
     code = {https://github.com/eXascaleInfolab/bench-vldb20},
     url = {http://www.vldb.org/pvldb/vol13/p768-khayati.pdf},
     award = {https://vldb2020.org/vldb-2020-awards.html#most-reproducible-paper-award}
   }
   

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6. Ines Arous, Jie Yang, Mourad Khayati, and Philippe Cudré-Mauroux. “OpenCrowd: A Human-AI Collaborative Approach for Finding Social Influencers via Open-Ended Answers Aggregation.” In Proceedings of the Web Conference (WWW 2020). Taipei, Taiwan, 2020. Bibtex Slides PDF Code Video

   OpenCrowd: A Human-AI Collaborative Approach for Finding Social Influencers via Open-Ended Answers Aggregation

   Ines Arous, Jie Yang, Mourad Khayati, and Philippe Cudré-Mauroux. “OpenCrowd: A Human-AI Collaborative Approach for Finding Social Influencers via Open-Ended Answers Aggregation.” In Proceedings of the Web Conference (WWW 2020). Taipei, Taiwan, 2020.

   @inproceedings{arous2020www,
     title = {OpenCrowd: A Human-AI Collaborative Approach for Finding Social Influencers via Open-Ended Answers Aggregation},
     author = {Arous, Ines and Yang, Jie and Khayati, Mourad and Cudr{\'e}-Mauroux, Philippe},
     booktitle = {Proceedings of the Web Conference (WWW 2020)},
     year = {2020},
     address = {Taipei, Taiwan},
     url = {https://exascale.info/assets/pdf/arous2020www.pdf},
     note = {https://exascale.info/assets/pdf/arous2020www-slides.pdf},
     video = {https://www.youtube.com/watch?v=LOPgd-8TS-k&list=PLJNwhMK_V7EwEzlo9exv6COBKA3MQ28KW&index=3&ab_channel=TheWebConference2020Web},
     code = {https://github.com/eXascaleInfolab/OpenCrowd}
   }
   

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7. Abdelouahab Khelifati, Mourad Khayati, and Philippe Cudré-Mauroux. “CORAD: Correlation-Aware Compression of Massive Time Series Using Sparse Dictionary Coding.” In BigData, 2019. Bibtex PDF Code

   CORAD: Correlation-Aware Compression of Massive Time Series using Sparse Dictionary Coding

   Abdelouahab Khelifati, Mourad Khayati, and Philippe Cudré-Mauroux. “CORAD: Correlation-Aware Compression of Massive Time Series Using Sparse Dictionary Coding.” In BigData, 2019.

   @inproceedings{khelifati2019bigdata,
     author = {Khelifati, Abdelouahab and Khayati, Mourad and Cudr{\'{e}}{-}Mauroux, Philippe},
     title = {CORAD: Correlation-Aware Compression of Massive Time Series using Sparse Dictionary Coding},
     booktitle = {BigData},
     year = {2019},
     url = {https://exascale.info/assets/pdf/khelifati2019bigdata.pdf},
     code = {https://github.com/eXascaleInfolab/CORAD}
   }
   

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8. 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 Proceedings of the IEEE International Conference on Data Engineering (ICDE 2019). Demo Track. Macau, China, 2019. Bibtex PDF 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 Proceedings of the IEEE International Conference on Data Engineering (ICDE 2019). Demo Track. Macau, China, 2019.

   @inproceedings{arous2019icde,
     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 = {Proceedings of the IEEE International Conference on Data Engineering (ICDE 2019). Demo Track},
     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 = {https://exascale.info/projects/recovdb/}
   }
   

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9. 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 (ICDM), Demo Track, 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 (ICDM), Demo Track, 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 (ICDM), Demo Track, 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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10. 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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11. 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 Code

    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},
      code = {https://github.com/eXascaleInfolab/cdrec}
    }
    

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Student Supervision

PhD

I co-supervise(d) the following PhD students: Artem Lutov (finished), Ines Arous (expected 2022) and Abdelouahab Khelifati (expected 2022).

MSc/BSc

I supervise(d) the following Master and Bachelor students:

• Available proposals:
  • Repairing Anomalies in Time Series using Missing Values Recovery (MSc, taken).
  • Comparison of Prediction Techniques in Energy Time Series (BSc, taken).
• Completed theses:
  • Guillaume Chacun, MSc 2021: A Configuration-Free Repair of Time Series.
  • Jonas Fontana, BSc 2021: Comparison of Synthetic Time Series Data Generation Techniques.
  • Louis Müller, MSc 2021: Multiclass Classification of Open-ended Answers.
  • Gabriela-Carmen Voroneanu, MSc 2021: Benchmark of Time Series Management Systems using Analytical Queries.
  • Adrian Hänni, MSc 2020: Correlation-based Anomaly Detection in Time Series.
  • Mili Biswas, MSc 2019: Incremental Enrichment of Taxonomies using Transfer Learning.
  • Manuel Mondal, BSc 2018: Reducing Polarization in Social Media by Balancing Content Exposure.
  • Ahana Malik, MSc 2018: Trend Prediction on Fashion Data.
  • Leutrim Kaleci, MSc 2017: Modeling the Evolution of Fashion Trends using Matrix Factorization Techniques.
  • Oliver Stapleton, MSc 2017: Real-Time Centroid Decomposition of Streams of Time Series.
  • Zakhar Tymchenko, BSc 2017: Empirical Comparison of Incremental Matrix Decomposition Techniques.
  • Laura Rettig , MSc 2016: Online Anomaly Detection over Big Data Streams, Best Thesis Award.
  • Qian Liu , MSc 2016: Implemetation of Centroid Decomposition Algorithm on Big Data Platforms - a Comparison Between Spark and Flink.
  • Eszter Börzsönyi, MSc 2013: Evaluating the Optimality of Centroid Decomposition [uzh].
  • Jonathan Nagel, MSc 2013: Decomposition of Time Series Subsequences [uzh].
  • Michał Kołtonik, MSc 2010: LDBE Project [uzh].