Zaid Harchaoui
About Zaid Harchaoui
Zaid Harchaoui is a researcher with extensive experience in data science and machine learning, currently serving as Visiting Faculty at New York University and a researcher at Inria. His research focuses on developing computationally-efficient machine learning algorithms, particularly in computer vision and audio signal processing.
Current Work at Inria
Zaid Harchaoui has been working as a researcher at Inria since 2012. His role involves engaging in advanced research projects in the Grenoble Area, France. Inria is known for its focus on computer science and applied mathematics, making it a fitting environment for Harchaoui's expertise in machine learning and data science.
Current Position at New York University
Since 2014, Zaid Harchaoui has served as visiting faculty at New York University, specifically within the Moore-Sloan Data Science Initiative. This initiative aims to enhance data science methodologies and applications. Harchaoui is actively involved in the Center for Data Science and the Courant Institute for Mathematical Sciences, contributing to interdisciplinary research efforts.
Education and Expertise
Zaid Harchaoui obtained his Doctor of Philosophy (PhD) in Statistical Machine Learning from Telecom ParisTech, where he studied from 2005 to 2008. He also holds a Master's degree in Applied Mathematics and Computer Science from Ecole nationale supérieure des Mines de Saint-Etienne, completed between 2001 and 2004. His academic background supports his research interests in computationally-efficient machine learning algorithms.
Previous Research Experience
Harchaoui has a diverse research background, having worked in various esteemed institutions. He was a postdoctoral research fellow at Carnegie Mellon University and Télécom ParisTech in 2009. He also served as a PhD student at CNRS from 2005 to 2008 and held internships at several institutions, including École normale supérieure and Max Planck Institute, gaining valuable experience in the field.
Research Interests
Zaid Harchaoui's research interests focus on developing computationally-efficient machine learning algorithms that come with theoretical guarantees. His work is applied to various domains, including computer vision and audio signal processing. This focus reflects his commitment to advancing the field of data science through innovative methodologies.