Francisca Vasconcelos
CS PhD @ UC Berkeley Theory Group and BAIR Lab.
francisca @ berkeley.edu
I am a third-year PhD student in the UC Berkeley Department of Electrical Engineering and Computer Science. My research is supported by the NSF Graduate Research Fellowship and Paul & Daisy Soros Fellowship for New Americans. I am co-advised by Profs Michael Jordan and Umesh Vazirani. My research interests lie at the intersection of quantum computation and machine learning theory.
In 2020, I received a BS in EECS and Physics from MIT, where I was fortunate to do substantial undergraduate research advised by Prof William Oliver in the MIT Engineering Quantum Systems group. As an undergraduate, I also interned under Dr. Marcus da Silva at Rigetti Computing and Microsoft Research Quantum. Supported by a Rhodes Scholarship, I received two masters from the University of Oxford: an MSc in Statistical Sciences and MSt in Philosophy of Physics. Following from the MSc, I performed statistical ML research in the OxCSML group, advised by Prof Yee Whye Teh.
I am also the Founding Academic Director of the Qubit x Qubit (QxQ) initiative of The Coding School (TCS) non-profit. Since 2019, we have taught 20,000+ diverse K-12 students, undergraduates, and members of the workforce worldwide about the fundamentals of quantum computing and QISE.
selected publications
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- A Quadratic Speedup in Finding Nash Equilibria of Quantum Zero-Sum Games2023⭐ Long talk at QTML 2023 (CERN).
- UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed TomographyTransactions on Machine Learning Research (TMLR), 2023🎓 Oxford MSc in Statistical Sciences Thesis
Early version of work (Abstract) also presented at NeurIPS 2021 workshops:
Med-NeurIPS (Oral - 6.66% Acceptance Rate) & Bayesian Deep Learning (Poster)