I am a computational neuroscientist and data scientist, working as a postdoctoral researcher at the Fukai Unit at Okinawa Institute of Science and Technology. My current research interests are knowledge generalization and associative memory.
In the Neural Coding and Brain Computing Unit I study the memory storage limits of the brain and formation of new knowledge from existing memories during offline activity.
I worked on my PhD jointly in two labs, which means that each year I spent several months (4-5) in the laboratory of Philippe Lucas in Versailles. In the project with Philippe Lucas I focused on studying how insects use olfactory cues to navigate in complex environments. Particularly, we studied the signal transdution and adaptation mechanisms of the olfactory receptor neurons. To this end I analyzed electrophysiologal recordings from the moth Agrotis ipsilon and used biophysical models to reproduce the activity.
In the second project with Lubomir Kostal (Laboratory of Computational Neuroscience) we focused on the information metabolic efficiency of neurons and neural networks. We employed Shannon's information theory to evaluate the information transmitted by a single neuron or a group of neurons and use biophysical properties of the neurons to estimate the metabolic cost of the activity. We worked mostly with simulated data obtained from Monte Carlo simulations. To perform the simulations we used either custom code in Python and C++ or the Brian2 Python package.
I worked part-time as a data scientist at the end of my BSc and during my MSc studies. Datatree uses transactional data to help banks understand their clients and to automate financial advice. My job was to develop algorithms to classify transaction and evaluate risk factors using both heuristic approaches and machine learning. Subsequently I worked on approaches to evaluate the clients' financial health and to provide suggestions on where money can be saved.
I worked mostly with Python and data analysis and scientific packages - Pandas, NumPy, SciPy. For machine learning I used mostly methods implemented in the SciKitLearn package, XGBoost and Shap for result interpretation. I also used Tableau, D3JS and Plotly for advanced visualizations and SQL for database queries.
As a tutor I helped the participants (PhD students) of the three weeks summer course shape and achieve their project goals.
Member of the teaching team for Code In Place, April - May 2021 and 2023. This online course was offered by Stanford University during the COVID-19 pandemic. The course is a 6-week introduction to Python programming using materials from the first half of Stanford's CS106A course.
As a volunteer section leader, I prepared and taught a weekly discussion section of small group of students to supplement professors' lectures.
Science To Go organizes lectures at various places across the Czech Republic to present various topics from the natural sciences to the general public interested in science.
During my talk at their event I introduced basics of neuroscience and why and how we can use mathematics and physics to investigate information transmission by neurons.
Member of the organizing team of correspondence competition in physics for high school students. I was setting physics problems and grading the solutions. During other events organized by FYKOS I presented various mathematical and physical topics to motivated high school students. I was also the main organizer of Physics Brawl, competition for high school students, taking place once a year, organized by FYKOS.
Programming & scientific computing: Python - NumPy, SciPy, pandas, experience with C++ and building Cython packages; Linux, Git
Machine learning & statistical modeling: scikit-learn, XGBoost, SHAP; regression/classification, dimensionality reduction, clustering, model evaluation; Monte Carlo simulation
Data handling & pipelines: SQL; HDF5/NWB; large-scale electrophysiology data processing; reproducible analysis workflows; HPC/Slurm
Visualization & reporting: LaTex; Matplotlib, Plotly; scientific figure preparation; Tableau
Research/domain expertise: computational neuroscience; biophysical and spiking neural-network modeling; recurrent/attractor networks; information theory; electrophysiology data analysis
I love going into nature to run, hike, cycle. I can't do a year without going backpacking or bikepacking at least once. Now when I live on Okinawa I try to do various marine activities as much as I can, such as diving or going out on SUP (stand up paddle board), or paddling on a haarii boat with the OIST (Okinawan dragon boat). When the weather is bad, I like to play chess, cook, bake, or learn to play violin and sanshin.
