Nesma is professor at Télécom SudParis (EPH department - Samovar ARMEDIA team).

Specialized in neurosciences, she studies attention measurements by analyzing brain activity and looks for ways to innovate in tele-vigilance. Nesma also works in biometrics on signature recognition.

Nesma Houmani's skills cover a large spectrum of AI domain, ranging from electronics to data science, along with signal and image processing, machine learning, pattern recognition and computer science. Engineer in electronics, Nesma obtained her PhD in 2011 from Telecom SudParis (TSP), with the habilitation of the University of Evry Val d'Essonne. Her thesis work, applied to the field of biometrics, concerns the development of statistical quality measures for the characterization of online handwritten signals. During her PhD and post-doctoral research position in biometrics at TSP, she participated in the conception and organization of two international evaluation campaigns on online handwritten signatures (BSEC'2009 and ESRA'2011). She also worked on the development of super resolution techniques for 2D iris images to enhance authentication systems, when being confronted to degraded sequences. In 2012, Nesma joined the “Brain Computer Interface” team of Brain Plasticity Lab (UMR 8249) at ESPCI (Paris, France). She started her research on the analysis of electrophysiological signals, in particular on the analysis of EEG signals to study brain activity. She developed a new statistical EEG biomarker for the diagnosis of Alzheimer's disease at the early stage. Since 2015, Nesma is senior lecturer, member of ARMEDIA team, SAMOVAR Lab at TSP. One of her current researches focuses on e-health, especially on cognitive and behavioral neuroscience, and deals with EEG signal processing and analysis. This axis has two objectives: first, the detection and prediction of neurodegenerative diseases; second, the monitoring of sustained and selective visual attention by combining brain response with eye movements. She is also working on the detection of cognitive and behavioral disorders in children and the elderly, through the analysis of fine motor gestures coupled with other sequential signals from other sensors, such as the eye tracker, via serious games adapted to the person. Besides, Nesma is pursuing her researches in Biometrics, in particular on offline and online handwritten signatures, with an extension to Forensics Science and e-Health. Her research work is focusing on the profiling of persons based on their signature behaviors that reflect unconscious ballistic gesture.