semi-Agentic co-clustering via large language models.
About
He earned his BSc in Statistics and Applications at IKIU (2009–2014), where he first became drawn to the idea that data can tell real stories. He then moved to the University of Tehran for his MSc in Mathematical Statistics (2014–2016), going deep into Bayesian inference and ranked set sampling. His PhD in Data Science at Amirkabir University of Technology (2016–2023) was where it all came together — he worked on latent block models and non-negative matrix tri-factorization for text co-clustering, guided by three accomplished supervisors.
Research Interests
Natural Language Processing, Machine Learning, Co-clustering, Text Mining, EM Algorithms, Latent Block Models, Matrix Factorization, Optimization Problems, Transformer Models, Large Language Models, Agentic AI
Articles
Publications
A Sparse Exponential Family Latent Block Model for Co-clustering
Advances in Data Analysis and Classification, 2024
This paper introduces a sparse exponential family latent block model for co-clustering and structured data analysis.
Orthogonal Parametric Non-negative Matrix Tri-Factorization with α-Divergence for Co-clustering
Expert Systems with Applications, 2023
This paper presents an orthogonal parametric non-negative matrix tri-factorization method with α-divergence for co-clustering.
Software
ELBMcoclust
Software package and reproducible code for sparse exponential family latent block model co-clustering.
NMTFcoclust
Software package and reproducible code for orthogonal parametric non-negative matrix tri-factorization with α-divergence.
