Issam Falih
My research focuses on machine learning applied to complex data — heterogeneous, multi-view and multimodal. I am particularly interested in domain adaptation, attributed network mining, and the explainability of deep models, with applications in e-health, multimodal emotion analysis and the study of chronic pain.
News
June 2026
Paper accepted at CAp 2026 — Online domain adaptation for data stream anomaly detection, with H. Tcheneghon Motcheyo and E. Mephu Nguifo.
June 2026
Paper accepted at ISMIS 2026 — Accelerating Gradual Pattern Discovery through Dimensionality Reduction, with H. Tcheneghon Motcheyo, L. Tiogning-Djiogue and E. Mephu Nguifo.
Apr. 2026
Thematic school on generative AI co-organized at the University of Yaoundé I (Cameroon), as part of the FDMI-AMG project supported by the CNRS DSCA program.
Dec. 2025
PhD defense of Jingyao Wang — Edge AI for e-health: application to mobility monitoring.
Dec. 2025
Presentation at the NeurIPS 2025 Workshop on Evaluating the Evolving LLM Lifecycle with C. M. Tran on the evaluation of LLM agents.