Charlie Fieseler, Ph.D.

University of Vienna

Charlie Fieseler started their academic journey interested in physics and, like many of their peers, was impressed by compact theories like general relativity. They continued to work in condensed matter theory, but realized that such strongly interacting systems are extremely complex and messy. Then, after graduating from university in the U.S., they taught high school in Japan. Experiencing a less academic and human-oriented side of the world continued their trajectory into their current and more interdisciplinary field: computational neuroscience. In addition, they feel that this experience of full time teaching has been invaluable to all subsequent teaching duties.

In their current position as a postdoctoral researcher, Fieseler fully managed a cohort of five undergraduate students on a computational project and supervised a partial masters thesis. They fundamentally believe that science is a social endeavor, and that its continued success requires support at all levels: educational, intellectual and social. They have put this into action by listening to the interests and plans of the students mentioned above, and supporting them in getting an additional position in our lab or elsewhere. Fieseler hopes to both use the skills they already have and continue to grow as a mentor through the SURFiN program.

Principal Investigator: Manuel Zimmer

Fellow: Hannah Brenner

Undergraduate Fellow Project: What is the neuronal representation of brain states?
The Zimmer Lab at the University of Vienna, Austria, utilizes the microscopic roundworm C. elegans as a model organism to explore fundamental questions in neuroscience. With only 302 neurons in its nervous system, we can identify each neuron and leverage a synaptic resolution connectome to understand the network’s architecture. Our lab has developed novel technologies to record the activity of all neurons in the worm’s brain while it freely crawls under a microscope. Additionally, we employ advanced AI techniques, such as convolutional neuronal networks, to extract meaningful information from these experiments.
This SURFiN project aims to investigate how longer-lasting behavioral states, including sleep, arousal, hunger and satiety, are encoded in the brain. The project will entail conducting behavioral and neuronal imaging experiments on animals that switch between these states. The fellow will work with two mentors, with each experimental and computational background, to develop a pipeline that can quantitatively describe such brain states in complex datasets.
We therefore are seeking students interested in combining experimental and computational work. This unique opportunity will provide an excellent learning experience in both fields while working on a project at the forefront of neuroscience research.

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