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Muhammad Usman
Senior Lecturer in Quantum and Photonics Technologies at University of Melbourne and STEM Educator with CSIRO
M. Usman is a Senior Lecturer at the University of Melbourne and a STEM Educator with CSIRO, specializing in nano-science and technology.
With a strong background in quantum materials, M. Usman aims to advance next-generation technologies through research in quantum processor design, quantum simulations, photovoltaics, and photonic devices.
His notable achievements include pioneering work in solid-state spin qubits in silicon for scalable quantum computing architecture and contributions to groundbreaking investigations such as spatial metrology of P donor atoms in silicon and machine learning scalable architectures.
Prior to his current roles, M. Usman conducted research on optoelectronic properties of III-V materials and heterostructures, focusing on quantum wells, quantum dots, and nanowires.
A dedicated STEM advocate, he is involved in promoting science education among students through various programs and serves on the Education Committee at the Melbourne School of Engineering.
M. Usman is affiliated with prestigious societies like APS, AAIP, and IEEE and has received fellowships from DAAD and the USA State Department.
He holds degrees from various institutions including a Ph.D. from Purdue University and has practical experience in Compound Semiconductor Fabrication.
Throughout his career, M. Usman has showcased a commitment to research, education, and innovation in the field of nano-science and quantum technologies.
Highlights
Looking forward to attending Australian Army 2024 Land Forces event in Melbourne this year: https://lnkd.in/gCR2h4K7
CSIRO's Data61 Quantum Systems Team will be showcasing our Quantum Machine Intelligence Technology which has the potential to provide asymmetric advantage to the Australian Defence Forces by leveraging state of the art quantum capabilities.
Simonette Cox
#defence #ADF #landforces #cas2024 #quantumcomputing #quantumtechnology
Freshly posted on arXiv today: https://lnkd.in/gZ3Pesb5 A great piece of work by my PhD students @Max West and Chris Nakhl with Prof Kavan Modi group (@Neil Dowling, Angus Southwell) and Prof Martin Sevior.
There have been a few recent studies which have empirically shown that quantum machine learning models indeed exhibit superior robustness against adversarial attacks, yet there is no clear fundamental understanding of this phenomena. We have now developed a detailed theoretical formalism for the adversarial robustness of quantum machine learning which ties it to the quantum dynamical complexity and quantum entanglement – the fundamental properties of quantum systems. Our work therefore concretely establishes a unique quantum advantage in machine learning models.
#quantumadvantage #quantummachinelearning #quantumcomputing
