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Muhammad Kashif
Postdoctoral Associate
Affiliation: NYU Abu Dhabi
Education: BS Comsats Institute of Information Technology, Pakistan; MS Istanbul Sehir University Turkey; PhD Hamad Bin Khalifa University Qatar
Research Websites: Center for Quantum and Topological Systems
Research Areas: Quantum machine learning, quantum neural networks, quantum algorithms, quantum error correction
Muhammad Kashif began his academic journey with a Bachelor's in Electrical (Electronics) Engineering from COMSATS Institute of Information Technology, Pakistan, in 2015. He furthered his education with an MSc in Electronics and Computer Engineering from Istanbul Sehir University, Turkey, in 2020. During his time at Hamad Bin Khalifa University in Qatar, he pursued a PhD, focusing on the exploration of potential Quantum advantages in Machine Learning in the Noisy Intermediate-Scale Quantum (NISQ) era, and successfully defended his thesis in May 2023.
At present, Kashif serves as a Postdoctoral Researcher at the Center for Quantum and Topological Systems (CQTS) at NYU Abu Dhabi. His research interests span the realms of Quantum Machine Learning (QML) and classical machine learning. He's keen on understanding how these fields intersect and enhance one another and is particularly interested in Quantum Error Correction techniques in the context of QML algorithms development.
Current Research
Muhammad Kashif's research interests span the realms of Quantum Machine Learning (QML) and classical machine learning. He's keen on understanding how these fields intersect and enhance one another and is particularly interested in Quantum Error Correction techniques in the context of QML algorithms development.