Brief Bio

Mourad Khayati is a Senior Researcher and a Lecturer with the eXascale Infolab group and the Advanced Software Engineering group, respectively, 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 temporal data cleaning/repair with a special focus on recovery of missing values. He is the recipient of the VLDB 2020 Best Experiments and Analysis Paper award.

Open Source Software

• TSM-Bench : Benchmark of Time Series Database Systems (TSDBs) [PDF (pvldb’23) | code ]
• ORBITS : Online Recovery of Missing Values in Time Series Streams [PDF (pvldb’21) | code | repro | GUI]
• ImputeBench : Benchmark of Time Series Imputation [PDF (pvldb’20) | code | repro]
• VADETIS : Explainable Evaluator for Anomaly Detection [PDF (icde’21) | GUI]
• CDRec : Recovery of Missing Blocks in Time Series [PDF (kais’20) | code | repro | GUI]
• RecovDB : Time Series Repair inside MonetDB [PDF (icde’19) | code | GUI ]

Teaching & Projects

• Teaching:
  • Fall 2023:
    • Data Science Seminar (MSc)
    • Advanced Software Engineering (MSc)
  • Spring 2023:
    • Social Media Analytics (MSc)
    • Software Engineering (BSc)
• Projects:
  • ProvDS (D-A-CH project): Main lead, 1.06.2018-31.05.2022
  • FashionBrain (H2020 European project), Technical lead, 1.1.2017-31.12.2019

Selected Publications (DBLP)

1. Abdelouahab Khelifati, Mourad Khayati, Anton Dignös, Djellel Difallah, and Philippe Cudré-Mauroux. “TSM-Bench: Benchmarking Time Series Database Systems for Monitoring Applications.” In Proceedings of the VLDB Endowment, 16:3363–76, 2023. Bibtex PDF

   TSM-Bench: Benchmarking Time Series Database Systems for Monitoring Applications

   Abdelouahab Khelifati, Mourad Khayati, Anton Dignös, Djellel Difallah, and Philippe Cudré-Mauroux. “TSM-Bench: Benchmarking Time Series Database Systems for Monitoring Applications.” In Proceedings of the VLDB Endowment, 16:3363–76, 2023.

   @inproceedings{khelifati2023vldb,
     author = {Khelifati, Abdelouahab and Khayati, Mourad and Dignös, Anton and Difallah, Djellel and Cudré-Mauroux, Philippe},
     title = {TSM-Bench: Benchmarking Time Series Database Systems for Monitoring Applications},
     booktitle = {Proceedings of the VLDB Endowment},
     volume = {16},
     number = {11},
     pages = {3363--3376},
     year = {2023},
     doi = {10.14778/3611479.3611532},
     url = {https://www.vldb.org/pvldb/vol16/p3363-khelifati.pdf}
   }
   

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2. 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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3. 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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4. 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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5. 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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6. 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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7. 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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8. 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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9. 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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10. 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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11. 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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12. 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: Zakhar Tymchenko , Abdelouahab Khelifati , Ines Arous (finished), and Artem Lutov (finished).

MSc/BSc

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

• Available proposals:
  • Time Series Repair on Heterogeneous Data Sources (MSc/BSc, available).
• Ongoing theses:
  • Automatic Parametrization of Time Series Imputation Techniques (Lucien Gremaud, BSc).
  • Prediction of Environmental Hazards using Data Fusion (Dana Gousson, MSc).
  • Lightweight Framework to Evaluate Symbolic Data Fusion (Martin Poplawski, MSc)
• Completed theses:
  • 2023
    • Mirko Bristle (MSc): A Lightweight Meta-Learning Framework to Asses the Validity of Model Selection in Time Series Forecasting.
    • Brian Schweigler (MSc): ImputeVIS: Visualizing Time Series Recovery using ImputeBench.
    • Flavien Buron (BSc): Evaluation of Neural Networks Imputation using ImputeBench.
  • 2022
    • Manuel Mondal (MSc): Evaluating Link Prediction for Emerging Nodes in Dynamic Networks.
    • Zakhar Tymchenko (MSc): Evaluating the Impact of Imputation on Time Series Tasks.
    • Luca Althaus (MSc): Repairing Anomalies in Time Series Data.
    • Jana Stojanovic (BSc): Evaluating the Impact of Time Series Features on Downstream Tasks.
    • Jonathan Bernhard (BSc): An Empirical Comparison of Time Series Forecasting Techniques.
  • 2021
    • Guillaume Chacun (MSc): A Configuration-Free Repair of Time Series.
    • Louis Müller (MSc): Multiclass Classification of Open-ended Answers.
    • Gabriela-Carmen Voroneanu (MSc): Benchmark of Time Series Management Systems using Analytical Queries.
    • Jonas Fontana (BSc): Comparison of Synthetic Time Series Data Generation Techniques.
  • 2020
    • Adrian Hänni (MSc): Correlation-based Anomaly Detection in Time Series.
  • 2019
    • Mili Biswas (MSc): Incremental Enrichment of Taxonomies using Transfer Learning.
  • 2018
    • Ahana Malik (MSc): Trend Prediction on Fashion Data.
    • Manuel Mondal (BSc): Reducing Polarization in Social Media by Balancing Content Exposure.
  • 2017
    • Oliver Stapleton (MSc): Real-Time Centroid Decomposition of Streams of Time Series.
    • Leutrim Kaleci (MSc): Modeling the Evolution of Fashion Trends using Matrix Factorization Techniques.
    • Zakhar Tymchenko (BSc): Empirical Comparison of Incremental Matrix Decomposition Techniques.
  • 2016
    • Laura Rettig (MSc): Online Anomaly Detection over Big Data Streams, Best Thesis Award.
    • Qian Liu (MSc): Implementation of Centroid Decomposition Algorithm on Big Data Platforms - a Comparison Between Spark and Flink.
  • Prior to 2015 (University of Zurich)
    • Eszter Börzsönyi (MSc): Evaluating the Optimality of Centroid Decomposition.
    • Jonathan Nagel (MSc): Decomposition of Time Series Subsequences.
    • Michał Kołtonik (MSc) : LDBE Project.