Hello!

I am Alexandra, a PhD student working on quantum computing, currently doing an internship at UT Austin supervised by Scott Aaronson.  I am especially interested in quantum-enhanced numerical integration and quantum characterization. You can find my complete CV at the bottom of this page. 

For a quick overview of my favorite work so far, check out this short video where I explain it using silly metaphors. 

My PhD project involves developing noise-resilient algorithms for quantum amplitude estimation (QAE), under the supervision of professors Luís Paulo Santos and Ernesto Galvão. 

I recently finished an internship at the National Institute of Informatics, in Tokyo, working on models for open quantum systems with professor Akihito Soeda, and another at the Institute of Corpuscular Physics in Valencia with professor Germán Rodrigo, working on practical applications of QAE in physics and finance.

I am a member of the Quantum and Linear-Optical Computation (QLOC) research group at the International Iberian Nanotechnology Laboratory (INL), in Portugal.

I am also affiliated with  the High-Assurance Software (HASlab) center of the Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), and a student (and teacher) at University of Minho.

Background

I have a BSc and MSc in Engineering Physics, having graduated in late 2021. This course focused on physics, mathematics, computer science, and electronics, with a specialization on quantum information.

The focus of my Master's project was quantum characterization; you can find my MSc thesis here. I implemented efficient algorithms for this purpose, and tested them experimentally by characterizing noise channels in IBM's quantum computers. I used Qiskit Pulse, Bayesian inference, and advanced methods for numerical integration, with particular focus on Monte Carlo integration. This project was supervised by Raffaele Santagati, Ernesto Galvão and Luís Soares Barbosa.

Research interests

These are the main topics of my past and present research:

• Quantum amplitude estimation (QAE), namely hybrid and "NISQ-friendly" algorithms. I am especially interested in the potential speed-up in Monte Carlo integration associated with QAE.

• Quantum metrology; in particular, the use of adaptive measurements as a resource to perform Heisenberg-limited estimation.

• Bayesian inference, particularly as a tool for quantum science. Notable applications are Hamiltonian learning, characterization of open system dynamics, tomography, magnetic field sensing, and (iterative) phase estimation.

• Monte Carlo integration: Markov Chain Monte Carlo (namely Metropolis and Hamiltonian Monte Carlo), Sequential Monte Carlo (all variants), and associated techniques (e.g. variance reduction). I am interested in these algorithms as a backbone to Bayesian inference, but also in their application to more general problems. I am also interested in their quantum counterparts.

• Quantum algorithms in general, both fault-tolerant and near-term.

Publications

A. Ramôa, L. P. Santos. (2025). Bayesian Quantum Amplitude Estimation. Quantum, 9, 1856.

A. Ramôa, L. P. Santos, A. Soeda (2025). Low Cost Bayesian Experimental Design for Quantum Frequency Estimation with Decoherence (under review).

G. Cunha, A. Ramôa, A. Sequeira, M. de Oliveira, L. Barbosa. (2025). Hybrid quantum-classical algorithm for near-optimal planning in POMDPs (under review).

A. Ramôa, R. Santagati, N. Wiebe. (2025). Calibration of Quantum Devices via Robust Statistical Methods (under review).

Other

Here's a flashtalk where I explain my PhD project in under 3 minutes.

This video introduces quantum amplitude estimation and discusses the noise resilience of several quantum amplitude estimation algorithms. 

I have presented a video-poster the Machine Learning for Quantum (MLQ) 2021 conference, titled "Experimental Hamiltonian Learning".

Contact

You can e-mail me at: alexandraramoaalves [at] gmail [dot] com. You can also find me on GitHub and Linkedin. 

CV