Introduction to quantum machine learning by Kareem H. El-Safty
20:00 (Tunis Time), Thursday, August 12, 2021
Moderators and organizers: Mohamed Yassine Ferjani and Sahar Ben Rached (QTunisia)
“Quantum machine learning is the integration of quantum algorithms within machine learning programs, and it is one of the promising fields of Quantum Computing applications. Potential advantages include improving runtime, capacity and learning.”
Kareem H. El-Safty is a Research Assistant at Wigner Research centre for Physics. He is an AI Team Leader at DevisionX focusing on AutoML solutions for machine vision industries. He’s doing his master’s degree in computer engineering especially in Quantum Machine Learning (QML). He’s interested in the Continuous Variable model of quantum computing to be used in QML. He’s a PC member in the Quantum Computing Thematic Track in conjunction with the International Conference on Computational Science and in Python for ML and AI Global Summit 21. Besides his work, he is an active member in Alexandria Quantum Computing Group, where he led several workshops in Qiskit as he is a Qiskit Advocate and coordinated a quantum winter school for Egyptian researchers.