Lazhar Labiod

Brief Bio

Lazhar Labiod is an  Assistant Professor with  the  IUT de Paris - Rives de Seine and the Borelli Center at Université de Paris Cité . He received his  Ph.D. degree in statistics from Paris 6 University, France.

Lazhar has made contributions to advance data embedding and co-clustering  machine learning methods for solving hard AI problems for real-life applications, including bio-medical data co-clustering,  tensor data and attributed graph co-clustering, recommender systems, and multi-views data mining. His research has been published in top conferences and journals including, TNNLS, TKDE, PR, WSDM, ICDM, CIKM, and SIGIR.

Recent News:

2023:

• Representation Learning and Clustering (RLC’24)  WSDM workshop   will held in conjunction with  The 17th ACM International Conference on Web Search and Data Mining (WSDM'24) – Mérida,  Yucatan, Mexico,  March 4th-8th, 2024

• The Fifth edition of Deep Learing and clustering workshop : will held in conjunction with IEEE International Conference on Data Mining (ICDM’23) – Shanghai,  China,  December 1-4, 2023 

2022:

• The 4th edition of Deep Learing and clustering workshop : will held in conjunction with IEEE International Conference on Data Mining (ICDM’22) – Orlando, FL, USA, November 28 - December 1, 2022

• One paper for Power Atrributed Graph Embedding and Clusteriung was accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS).

• One paper for Efficient Graph Convolution for Joint Node Representation Learning and Clustering.was accepted by WSDM 2022.

• One paper for TensorClus: A python library for tensor (Co)-clustering was accepted by Neurocomputing . 

2021:

• Deep Learing and clustering workshop : In conjunction with IEEE International Conference on Data Mining (ICDM’21) – Aukland, New Zealand, December 7-10, 2021

• One paper for Efficient regularized spectral data embedding was accepted by Adv. Data Anal. Classif.