Maxwell T. West

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About

Maxwell T. West is a leading researcher at the intersection of quantum computing and machine learning, with a primary focus on adversarial robustness. His work addresses a critical vulnerability in modern AI: the susceptibility of neural networks to carefully crafted malicious inputs. West’s major contribution lies in systematically benchmarking how quantum machine learning (QML) models perform under adversarial attacks at scale. His landmark 2023 paper, “Benchmarking Adversarially Robust Quantum Machine Learning at Scale,” has garnered 59 citations, establishing a foundational framework for evaluating whether quantum architectures can offer inherent security advantages over classical models. By comparing the robustness of quantum classifiers against classical counterparts, West has provided crucial insights into the practical viability of QML in security-sensitive applications. His research not only advances theoretical understanding but also guides the development of more resilient AI systems. With his work continuing to influence both the quantum computing and cybersecurity communities, West is shaping the future of trustworthy machine learning in an era where adversarial threats are increasingly sophisticated.