People at the Quantum Device Lab, Department of Engineering Science, University of Oxford

Maria Fuentes Perez

I am the project manager for Natalia Ares's team. With a background in physics, I completed my PhD at the CNB (Spain), focusing on the interface of physics and biology. Afterward, I joined Imperial College London (UK) as a postdoc before moving into the private biotech sector, where I worked as both an operations and project manager. Currently, I manage the portfolio of projects for Natalia and her team.

Jacinta May

Research Associate and Laboratory Manager

Jacinta, a Research Associate and Laboratory Manager at the University of Oxford. My background is in experimental quantum computing and nanoscale device fabrication, and I hold a Bachelor's degree in Physics and Chemistry from the University of Sydney. During my undergraduate and early research career, I worked across several quantum platforms, including superconducting qubits, thin-film NbTiN superconductors, quantum point contacts, ballistic transport systems, rare-earth ion qubits, and hybrid trapped-ion devices. My work has spanned device nanofabrication, process development, and the experimental characterization of quantum systems. At Oxford, I focus on carbon-nanotube quantum devices and a research program investigating dynamic disorder in nanoscale systems, combining cleanroom process development, machine learning, and physics-based modeling to understand and mitigate time-dependent disorder in quantum technologies.

Prasanta Kumbhakar

Postdoctoral Researcher

I completed my PhD at IISER-Thiruvananthapuram, India, with a project on a hybrid mesoscopic electrical amplifier based on a semiconducting quantum point contact in a GaAs/AlGaAs heterostructure coupled to a superconducting microwave cavity. During my first postdoctoral position at the University of Basel (Department of Physics, Nanoelectronics Group), I studies of parity-protected superconductor–semiconductor qubits and Josephson parametric amplifiers in proximity-induced InAs quantum wells. At the University of Oxford, my research focuses on thermodynamic processes in nanoscale systems. I am currently fabricating and measuring carbon nanotube devices, investigating semiconducting quantum dots in CNTs to study mechanical coupling effects and aspects of quantum thermodynamics.

Frederico Martins

Postdoctoral Researcher

I am a solid-state physicist specialising in spin based quantum computing. In parallel with my activities in Natalia Ares’ team, I lead the Spin Qubit team at QuantrolOx, a University of Oxford spinout developing machine-learning-based software for the automated tuning and control of quantum processors. My research focuses on the development, control, and scaling of spin qubits in semiconductor nanostructures to enable robust and scalable quantum computing platforms.

Martyna Sienkiewicz

Postdoctoral Researcher

I completed an MSci in Physics, an MRes in Quantum Technologies, and a PhD in Quantum Engineering at University College London. During my PhD, I focused on the design, fabrication, and characterisation of low-dimensional and quantum dot devices for spin qubit applications. I am now in Dr Natalia Ares’ group, researching noise mechanisms relevant to quantum-dot spin qubits and developing noise mitigation strategies using machine learning approaches.

Mikhail Vaganov

Postdoctoral Researcher

I used to work with magnetic elastomers; that is, materials made of polymeric matrix filled with magnetic particles. Magnetic elastomers readily react to the application of a magnetic field and can be used in the development of field-controlled devices. My DPhil was mostly devoted to using electron and nuclear magnetic resonances for developing new methods for quantum information processing. Currently, I am part of a project in which we study thermodynamics of carbon nanotubes. My broader research interests lie in three major branches of quantum computation: the assembly of microwave apparatuses for quantum measurements, the development of quantum error correction protocols, and the addressability and control of qubits using an external electric field. I also teach physics at New College.

Pranav Vaidhyanathan

Postdoctoral Researcher

Theory of open quantum systems, specifically interested in investigating continuous measurements and feedback control in non-Markovian systems.

Yikai Yang

Postdoctoral Researcher

I conduct experimental research in quantum thermodynamics using quantum devices such as suspended carbon nanotubes and semiconductor quantum dots. My previous work spans spintronics, unconventional superconductivity, and quantum criticality, and my PhD research focused on exploiting cavity–magnon–polariton interactions to probe hybridized spin states in a model Ising compound.

Cornelius Carlsson

DPhil Student

I completed an integrated MEng in Materials Science at Imperial College London, followed by an MSc in Applied Physics at the Technical University of Delft. During my MSc thesis, I focused on probing charge noise using quantum device crossbars. After an internship at IBM, where I worked on designing reflectometry circuits, I am now at Oxford researching autonomous tuning methods for scalable spin-qubit architectures.

Sonali Goel

DPhil Student

I completed my MEng in Engineering Science at the University of Oxford in 2024 and am currently pursuing a PhD applying machine learning to quantum technologies. My work explores how modern AI methods—from large language models and reinforcement learning to scientific machine learning and computer vision—can be leveraged to understand, characterize, and optimize complex quantum systems. More broadly, I am interested in the use of machine learning as a tool for scientific discovery and in physical learning systems that harness the dynamics of matter itself to perform computation.

Anuprita Kulkarni

DPhil Student

I graduated with a BS-MS dual-degree from the Indian Institute of Science Education and Research (IISER Bhopal), where I majored in physics, with a minor in electrical engineering and computer science. For my master's thesis, I explored the application of boson sampling towards analog quantum simulation. As a DPhil student, my research currently focuses on autonomous tuning and optimal control of spin-qubits in semiconductor quantum devices.

Jose Nicolas Alvez

DPhil Student

I graduated in physics from the University of Buenos Aires, where I completed a thesis on shortcuts to adiabaticity. My primary research interests lie in thermodynamics at the nano- and quantum scales, particularly at the interplay between information and energy and the fundamental aspects of quantum physics.

Marek Rychetský

DPhil Student

Marek is a DPhil student in the group, working on machine learning for tuning quantum dots.

Lucas Schorling

DPhil Student

Lucas graduated with a BSc in Engineering Science from the Technical University of Munich and an MSc in Applied Mathematics from the University of Oxford. Current research focuses on developing machine learning algorithms to tune and control quantum devices, ranging from meta-learning to Bayesian optimization.

Freya Shah

DPhil Student

My research focuses on quantum-enhanced machine learning for quantum applications, particularly in quantum chemistry and materials science. More broadly, I am interested in developing ML frameworks to optimize and control quantum devices and to advance quantum simulation methods.

Vivek Wadhia

DPhil Student

My research focuses on noise characterisation and mitigation in superconducting and semiconducting qubits. I am particularly interested in the interplay between noise/errors, thermal effects and qubit benchmarking.

George Whittle

DPhil Student

I have a background in Information Engineering and Machine Learning, and am carrying out research in novel algorithms bridging the gap between the fields of Amortized Bayesian Inference and Bayesian Filtering, with the ultimate goal of applying these to tracking unobservable dynamic phenomena in quantum devices. I also research Fundamental Neural Network Theory, where I apply Bayesian perspectives to understanding extrapolation and implicit priors in deep learning models.