Anis HOAYEK
- École des Mines de Saint-Étienne (Mines Saint-Étienne MSE)
- Institut Henri Fayol (FAYOL-ENSMSE)
- Département Génie mathématique et industriel (FAYOL-ENSMSE)
- Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes (LIMOS)
Présentation
My research interests focus on stochastic behavior analysis for rare, unreliable, and extreme data models, particularly in the context of record series. I aim to develop decision-support tools and optimal action detection based on information theory. Additionally, I explore the application of artificial intelligence, statistical learning, and time series analysis to develop methods for dimensionality reduction, variable selection, and analyzing large-scale, complex data sources. My work also includes creating goodness-of-fit tests to discriminate between statistical models, developing anomaly detection algorithms for diverse data types, and applying record theory to improve the robustness of existing anomaly detection methods through dimensionality reduction. I am particularly interested in parametric inference methods for stochastic processes that extend beyond classical statistical assumptions, as well as applying these techniques to study the stability of economic markets, the power of information structures, epidemiological risk, telecommunications quality, production chain reliability and failure analysis.
Domaines de recherche
Publications
Publications
Anomaly Detection in a Production Line: Statistical Learning Approach and Industrial Application58th Conference on Manufacturing Systems - CMS 2025, Apr 2025, Enschede, Netherlands
Communication dans un congrès
emse-05049494
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Statistical Inference and Model Selection for Models Adapted to Record Series14th Conference on Extreme Value Analysis, Probabilistic and Statistical Models and their Applications (EVA 2025), Jun 2025, Chapel Hill, United States
Communication dans un congrès
hal-05305930
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Aggregated model for anomaly detection: a statistical learning approach56eme journees de Statistique de la SFdS, Jun 2025, Marseille, France
Communication dans un congrès
hal-05117306
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Coupling Variable Selection and Anomaly Detection: Record-Based Approach2025 5th IEEE Middle East and North Africa Communications Conference (MENACOMM), Feb 2025, Byblos, Lebanon. pp.1-6, ⟨10.1109/MENACOMM62946.2025.10911010⟩
Communication dans un congrès
hal-04345833
v2
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Exploring Climate Change Through the Lens of Records Theory56eme journees de Statistique de la SFdS, Jun 2025, Marseille, France
Communication dans un congrès
hal-05035638
v1
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New Algorithm for Detecting Weak Changes in the Mean in a Class of CHARN Models with Application to Welding Electrical Signals10th International Conference on Time Series and Forecasting, Jul 2024, Grande Canarie, Spain. pp.42, ⟨10.3390/engproc2024068042⟩
Communication dans un congrès
emse-04699930
v1
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Anomaly Detection in a Production Line: Statistical Learning Approach and Industrial Application43th IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2024, Chemnitz, Germany. pp.341-354, ⟨10.1007/978-3-031-71637-9_23⟩
Communication dans un congrès
emse-04709567
v1
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Anomaly Detection Based on System Log DataICLDQAD 2023 : International Conference on Linked Data Quality and Anomaly Detection, Apr 2023, Athenes, Greece
Communication dans un congrès
emse-04059771
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Anomaly Detection based on Alarms Data2022 AIMLNET International Conference, Oct 2022, Vienna, Austria. ⟨10.5121/csit.2022.121810⟩
Communication dans un congrès
emse-03945296
v1
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Unsupervised Variable Selection Using a Genetic Algorithm: An Application to Textual DataInternational Conference on Smart Systems and Power Management (IC2SPM), 2022, Beyrouth, Lebanon. pp.11-19, ⟨10.1109/IC2SPM56638.2022.9989008⟩
Communication dans un congrès
emse-03923877
v1
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β -Variational AutoEncoder and Gaussian Mixture Model for Fault Analysis Decision Flow in Semiconductor Industry 4.0ENBIS 2021 Spring Meeting, May 2021, Online, France
Communication dans un congrès
emse-03524369
v1
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Intelligent Fault Analysis Decision Flow in Semiconductor Industry 4.0 Using Natural Language Processing with Deep ClusteringIEEE 17th International Conference on Automation Science and Engineering (CASE), Aug 2021, Lyon, France. p 429-436
Communication dans un congrès
emse-03325358
v1
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New Algorithm for Weak Changes Detection with Application to Financial DataSustainable Progress Through Innovation in Data Science, Health, Environment, and Social Systems, Jul 2025, On Line, France
Poster de conférence
hal-05263325
v1
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On detecting changes in the mean with application to financial data2025
Pré-publication, Document de travail
hal-05135979
v1
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New algorithm for weak changes detection with application to real data.2024
Pré-publication, Document de travail
hal-04424352
v2
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Anomaly Detection in a Production Line: an Online/Offline Statistical Learning Approach2023
Pré-publication, Document de travail
hal-04328405
v1
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GCVAE: Generalized-Controllable Variational AutoEncoder2022
Pré-publication, Document de travail
emse-03712594
v1
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Leveraging Pre-trained Models for Failure Analysis Triplets Generation2022
Pré-publication, Document de travail
(preprint/prepublication)
hal-03837798
v1
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Exploration et Convergence : une approche combinant la théorie de records et la détection des anomaliesSciences de l'ingénieur [physics]. Mines Saint-Etienne, 2024
HDR
tel-04879867
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Estimation des paramètres pour des modèles adaptés aux séries de recordsMathématiques générales [math.GM]. Université Montpellier, 2016. Français. ⟨NNT : 2016MONTT336⟩
Thèse
tel-01816935
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