Research interests

I am interested in understanding how neurons compute: how they encode, store, and process information. My background in engineering physics colors my approach to this question, but I work best in interdisciplinary settings integrating many different perspectives on neuroscientific problems.

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Bio-inspired and material computation

My PhD research is part of the SOCRATES project and is also strategically aligned with the goals of NordSTAR, where I coordinate a satellite group on Material Computing. Along with my colleagues at the Living Technology Lab, led by Dr. Stefano Nichele, I am working toward translating the findings from my research to novel computational models and hardwares that are energy efficient, capable of learning, and robust against component failure. My work on studying the dynamics and flow of information in neural systems will inform the development of models emulating the behavior we observe in biological systems. Together with one of my master students, Jørgen Jensen Farner, I am also studying learning in spiking neuron models inspired by findings on axonal computation.

Signatures of criticality in neural systems

My current research has been focused on studying the question of neural computation through the lens of criticality. The critical state, poised between order and disorder, shows many features associated with good computational performance, such as maximal dynamic range and long-range spatiotemporal correlations. I have been working to evaluate the closeness to criticality of networks of neurons in vitro and understanding if this closeness can be correlated with other aspects of network behavior, such as patterns of functional connectivity.

Signal analysis in microelectrode arrays with microfluidics

I first became interested in neuroscience during my master thesis work with the Neuroengineering and Computational Neuroscience group (NCN), led by Dr. Paulo Aguiar, at the Institute for Research and Innovation in Health (i3S) in Porto, Portugal. Working with this group gave me a wonderful introduction to neuroscience, starting with understanding the Hodgkin–Huxley model and the electrical basis of neural activity and expanding into experimental work with neural cell culture and microelectrode array (MEA) electrophysiology. For my thesis work, I developed a computational tool for the analysis of electrophysiological signals traveling along axons confined to microfluidic tunnels. This tool provides an intuitive audiovisual interface with the data and performs propagation velocity calculation and simple graphical spike sorting, and it has since been used for a number of publications by NCN.

Other interests

I also find the following areas of research interesting, though I have not worked directly with them as yet: brain–machine interfaces and neural prosthetics, information theory, control theory, representational drift, and neural coding.