I am associate professor attached to École Nationale Supérieure de Physique, Électronique et Matériaux (Phelma), GrenobleINP-UGA and a researcher at GIPSA-lab (Grenoble Images Parole Signal Automatique), attached to ACTIV team research unit.

• Computer Vision (Anomaly detection, Semantic segmentation, Localization, Classification).

• Deep Learning (Semi Supervised Learning, Explainability, Uncertainty Quantification).

• Active Learning ( Smart data selection, Exploration and Exploitation).

• Medical Imaging ( Segmentation, Volume Quantification, Fatigue Index, EMG analysis).

• Optimal Transport ( Domain Shift).

• Hybrid AI:  blending physical models and big data.

Dawood Al Chanti recieved the B.E degree in Biomedical Engineering. He has a M.S. degree in Machine Learning and Data Mining from the University of Jean Monnet in Saint-Étienne and the University of Alicante in Spain in 2016. He then received a Doctor of Philosophy PhD degree in Image and Signal Processing from the University of Grenoble Alpes in 2019. After that, he worked at lS2N laboratory, École Centrale de Nantes as a Postdoctoral Researcher in the field of Medical Image Analysis using Deep Learning based Method for almost of two years. He joined Grenoble-INP in 2021 where he is now an Associate Professor in the National School of Physics, Electronics and Materials (Phelma) and a permenant research member of the ACTIV team, pôle PSD at Gipsa-Lab. His current research interests include semantic segmentation, anomaly detection, learning with fewer data, smart data selection, representation learning, uncertainty measure. He is an IEEE Fellow and often serves as program committee member for many Journals (IEEE Trans. on Neural Networks and Learning Systems, IEEE Trans. on Medical Imaging, IEEE Trans. on Affective Computing, IEEE Trans. on  Image Processing, Pattern Recognition Elsevier, Medical Image Analysis Elsevier, ...) and Conferences (IEEE WCCI, IPCAI, MICCAI, CVPR).  He also serve as a reviewer for the French National Research Agency (ANR) project finance.

• Image, vidéo et vision par ordinateur (3A SICOM, S9, 5PMSIVV3)

• Projet d'apprentissage profond - Accélération Matérielle (3A SICOM, S9, 5PMSPAM1) 

• Traitement de l'image  (M1 Daleth, S8, VPMDIPR1)

• Dynamic System Analysis (M1 Daleth, S8, VPMDDSA2)

• Traitement d'images et applications médicales (2A Biomed, S8, 4PMBIPM9)

• Traitement d'image avancé (2A SICOM, S8, 4PMSTIA5)

• Projet de programmation (1A PI, S6, 3PMIPPR2)

• Traitement d'images médicales (3A SICOM, S9, 5PMSTIM1, course changed to 5PMSIVV3 )

• Introduction à l'intelligence artificielle (2A SICOM, S7, 4PMSIIA4)

• Projet Génie Logiciel  (2A SEOC, S8, 4MMPGL)

• Projet Informatique - (2A SEOC, S7, 4PMEMST9)

• Tronc commun Programmation - (1A, S5, 3PMKPRO6 )