Natalia Ares
Associate Professor Natalia Ares works on experiments to advance the development of quantum technologies, with a focus on artificial intelligence for quantum device control and quantum thermodynamics. She joined the Materials Department at the University of Oxford in 2013. She was awarded a series of fellowships, including a Marie Skłodowska-Curie and a Royal Society University Research Fellowship, and was awarded a European Research Council Starting Grant in 2020. During her PhD she focused on silicon-based devices for quantum computing at CEA Grenoble, France. She completed her undergraduate studies in Physics and a Masters equivalent in the theory of quantum chaos at the University of Buenos Aires, Argentina, where she was born and raised. In October 2021 she was appointed as Associate Professor in the Department of Engineering Science and Tutorial Fellow at New College.
P: +44 (0)1865 283187
Postdocs
Federico Fedele
My main research area is on quantum technologies and nanoscale quantum devices that allows fine control over individual charges and spins which are used to encode and manipulate quantum information. In addition, I am interested in hybrid devices, in which individual quantum systems are coupled to nanomechanical resonators such that their thermodynamic quantities can be measured and harnessed to further optimise these quantum systems.
Federico Cerisola
I share my time between Natalia Ares' group at University of Oxford and Janet Anders' group at University of Exeter. My main research interests are in aspects of non-equilibrium thermodynamics of quantum systems, the link between thermodynamics and information theory, and the effects of strong coupling with the environment. Recently I have also developed interest in the theory of quantum devices.
Vincent Michal
Vincent is a theoretical quantum physicist, his research interests include the physical implementation of quantum information processing in semiconducting and hybrid (semi/superconducting) systems, out of equilibrium quantum dynamics, and quantum simulation. He is involved in a project that aims at controlling quantum devices with machine learning techniques.
DPhil Students
David Craig
Combining machine learning methods with physical models to understand transport in electrostatic quantum dot devices.
Joseph Hickie
Designing algorithms to improve quantum dot device readout and working on pulse optimisation for semiconductor qubits.
Brandon Severin
AI for qubit readout. Focused on taking Silicon devices from cool down to qubits with a flick of a switch.
Barnaby van Straaten
Machine learning techniques for high bandwidth measurements to ease the burden of transport measurements, for more scalable quantum computing architectures.
Kushagra Aggarwal
Exploring thermodynamics in the nanoscale regime using carbon nanotube-based electromechanical resonators.
Jonas Schuff
Combining the necessary parts (and proposing methods where there are gaps) to achieve fully automated tuning of semiconducting qubits. This will lead to an understanding of how highly complex algorithms can work together to contribute to the final goal of scalable quantum computers.
Pranav Vaidhyanathan
Theory of open quantum systems, specifically interested in investigating continuous measurements and feedback control in non markovian systems.
Part II/Master Students
Alumni
Dr Dominic Lennon
William Wombell
Oluwafemi Fakokunde
Daniel Antoine-Donatein
Dr Florian Vigneau
Nicholas Sim
Dr Hyungil Moon
Dr Vu Nguyen
Dr Anna Pearson
Josh King
Nina van Esbroeck
