The MIC Team

Fourth-year undergraduate in Computer Science with a minor in Statistics. Aiden co-founded MIC and has driven its growth from a reading group of eight into a recognized university research club. His research interests lie in variational quantum algorithms and their generalization properties.

Third-year undergraduate in Computer Science and Mathematics. Mei-Ling coordinates the club's research agenda, manages project mentorship pairings, and leads the weekly QML reading group. She is particularly interested in quantum kernel methods and their theoretical underpinnings.

Third-year undergraduate in Statistics and Cognitive Science. James oversees club logistics, membership, and event coordination. He is interested in hybrid quantum-classical optimization and its applications to large-scale statistical inference problems.

Third-year undergraduate in Computer Science. Yuki manages MIC's external communications, website, and social media presence. She is also an active researcher with interests in quantum neural network architectures and barren plateau mitigation techniques.

Second-year undergraduate in Engineering Science (Machine Intelligence option). Raj plans and organizes MIC's workshops, guest lectures, and reading group sessions. His research interests include quantum-enhanced support vector machines and near-term quantum advantage benchmarking.

Master's student in Computer Science, supervised by Prof. Vasquez. Priya leads the Quantum Machine Learning research stream, mentoring undergraduate projects on variational circuits, generalization theory, and barren plateau mitigation. Her thesis investigates the statistical mechanics of parameterized quantum circuits.

Master's student in Electrical and Computer Engineering with a focus on machine learning theory. Tobias leads the ML Theory reading group, guiding discussions on PAC learning, Rademacher complexity, and connections to quantum information theory. He is interested in the optimization landscape of parameterized quantum models.

PhD candidate in Physics, working at the intersection of quantum information and machine learning. Sofia leads the Hybrid Classical-Quantum Systems stream, with a focus on scientific ML applications including molecular property prediction and fluid dynamics surrogate modeling using quantum subroutines.

Third-year undergraduate in Computer Science. Daniel contributes to the QML benchmarking project and is exploring quantum circuit expressivity in the context of function approximation.

Second-year undergraduate in Mathematics and Physics. Amara is exploring quantum error correction protocols and their relevance to fault-tolerant quantum machine learning.

Fourth-year undergraduate in Computer Science and Economics. Leon is interested in quantum-classical optimization for financial modelling and contributes to the club's hybrid systems reading group.

First-year Master's student in Applied Mathematics. Nadia joined MIC to explore connections between optimal transport theory and quantum optimal control, with applications to training parameterized quantum circuits.