I obtained my PhD from the University of Tokyo in early 2021. During my doctoral studies, I developed a multi-compartmental dendritic neuron model for self-supervised detection of salient patterns in a continuous stream of information. Currently I am still working with patterns, but my focus has shifted to extraction and analysis of spike patterns from experimental data using flexible detection rules. I am also interested in the simulation and characterization of different spiking neuronal networks and brain criticality.
In my free time, I enjoy going to live music concerts and reading.
Simulators are computer programs that can imitate the neuronal mechanisms of healthy and diseased brains. I build simulators of biological neuronal networks and study how to keep them healthy despite simulated insults that resemble those seen in brain disorders. Because simulators model neuronal mechanisms, they can be used to discover patient-specific causes of multicausal brain disorders.
Although scientists have found various possible causes of brain disorders, the exact cause in a specific patient is hard to determine. For example, loss of specific cell types or overexpression of proteins are not measurable in the brains of living patients. However, such immeasurable features can be inferred in a simulator from readily measurable features such as electroencephalogram. Therefore, simulation-based inference with patient data estimates otherwise immeasurable features, but it is currently unclear how accurate these estimates are. I develop and benchmark simulators and inference algorithms on mouse and human data to make them reliable in diagnostic practice. Diagnosing not just the brain disorder but the patient-specific causes with personalized simulators will support precision treatments.
I have been postdoc at the NCBC unit since July 2023. I am interested in exploring the limits of the brain in storing memories, and how the brain generates new knowledge from existing memories. I joined the unit shortly after defending my PhD, which I obtained jointly from the Charles University in Prague and Sorbonne University in Paris. During my PhD, I used computational approaches to study the limits of information transmission by single neurons and neural networks, and also sensory signal processing by insect olfactory neurons. My previous background is in physics and mathematical and computational modeling therein.
In my free time I like to go snorkeling, bouldering, cook, bake... or just explore this beautiful island. I’m also dabbling in growing vegetables on my balcony and I’m excited to see if it turns into anything.
Both the beauty and frustration of neuroscience is that there is no solid ground of theory derived from first principles. Therefore, we are all in the parable of “blind men and an elephant”, i.e., neuroscientist and brain. I am “blindly” interested in the circuit dynamics of the brain. I want to understand what network structures, e.g., heterogeneous neuron types and connectivity, gives rise to the computational power of the brain in response to structured stimuli. Hopefully, to also learn the limitation of it. I obtained my PhD at KTH in 2025 and joined the NCBC unit shortly after the defense. In turn, my research shifted from within-trial correlation and across-trial variability to sequence learning in the brain. I investigate both network and neuronal mechanisms that could support sequential memory.
During spare time, I’m a slave of my cat, Shannon, who remotely controls my mind. Other than that, I enjoy playing indie games, watching movies and learning about ancient buildings.
I joined NCBC in Sep 2020 as a PhD student. My main interest is the interaction between hippocampus and several brain region that contributes to memory systems in human brain. To try this challenge, I learned information technology in bachelor at Chiba Univ and Computational neuroscience in master at Univ of Tokyo.
My current research is the modeling of the brain circuit for the memory function which reproduces the results of rodents experiment, with using neuroscience knowledge and machine learning technics.
My studies (Undegraduate and Master's) involved exclusively biology and neuroscience, with no computational aspects whatsoever. I developed an interest in computational neuroscience after some internships, and got fascinated with the possibilities offered by computational approaches (the absence of long and tedious experimental procedures and preparations is also a big plus). I am now a fully certified Computational Neuroscientist™. My research interests are now in the hippocampus, more specifically how place cells are involved in replay sequences, but I also am very curious about completely different branches of science and epistemology.
I completed my BSc in Mathematics and Physics at the University of Chicago in 2019 before coming to Japan and OIST, where I switched to Computational Neuroscience and have since joined the NCBC unit as a PhD student.
My current research involves investigating the role of inhibition in reservoir computing and working with the successor representation to describe the hippocampus. Other current research interests include analytic explorations of the information bottleneck and chunking in the brain.
