Francisca Vasconcelos
CS PhD @ UC Berkeley Theory Group and BAIR Lab.
francisca @ berkeley.edu
I am a thirdyear 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 coadvised 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) nonprofit. Since 2019, we have taught 20,000+ diverse K12 students, undergraduates, and members of the workforce worldwide about the fundamentals of quantum computing and QISE.
selected publications

 A Quadratic Speedup in Finding Nash Equilibria of Quantum ZeroSum Games2023⭐ Long talk at QTML 2023 (CERN).
 UncertaINR: Uncertainty Quantification of EndtoEnd 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:
MedNeurIPS (Oral  6.66% Acceptance Rate) & Bayesian Deep Learning (Poster)