Presenter

Dr. Muhammad Kashif is a Research Team Lead at eBRAIN Lab, Division of Engineering, and a Postdoctoral Research Associate at the Center for Quantum and Topological Systems (CQTS) at NYU Abu Dhabi. Dr. Kashif's specializes in hardware-aware quantum machine learning, focusing on bridging the gap between theoretical quantum models and their practical deployment on NISQ devices. His work spans variational quantum algorithms, hybrid quantum–classical architectures, and system-level optimization, with an emphasis on expressibility–trainability trade-offs, noise resilience, and resource-efficient design. He focuses on developing methodologies for co-designing quantum algorithms and hardware-aware implementations, including quantum resource modeling and quantum neural architecture search.