Research title: The hippocampus as an indexing machine.
What makes us who we are? There are as many answers to this question as there have been scholars asking it. One intriguing approach is the one of memory. What we perceive around us reaches us filtered through the lens of our past experiences. Likewise, how we interact with our environment is shaped by our memories. During my PhD I leverage human intracranial recordings to probe the very building blocks – individual neurons – that make up our memories. We call these Episode Specific Neurons (ESNs) because they show a specific firing rate reinstatement when correctly remembering a unique past episode. Although already proposed by Teyler and Discenna in 1986, their existence has never been empirically shown in humans before.
I am very interested in learning and implementing new methods, linear algebra and currently work on a classification project using macro iEEG electrodes.
Society for Neuroscience Trainee Professional Development Award (December 2020)
CoLES PGR Travel Prize a merit based grant supporting the attendance at a conference or workshop (May 2019)
Deutschlandstipendium (“Germany Scholarship”) awarded to students with excellent academic grades and social commitment (October 2016 – July 2018)
SfN Global Connectome - Poster, 2021
Workshop on Intracranial Recordings in humans: Epilepsy, DBS (WIRED) - Poster, 2019
OxBirm Oscillations Workshop, Poster 2019
School Research Conference, Poster 2019
Outside of academia I have experience teaching Karate to children and young adolecents.
In the past I have participated in outreach programs presenting to prospective undergraduate students
Analyzing Neural Time Series Data (August 2019)
Fourier transform, convolution, time-frequency analysis, synchronization, nonparametric statistics, simulating time series data
Statistical Parametric Mapping for MEG/EEG (May 2019)
Data pre-processing, general linear model and classical inference, multiple comparisons, Bayesian interference, advanced applications of the general linear model, M/EEG source analysis, dynamic causal modeling
Spiking Neural Networks (September 2019)
Hardware implementations of spiking neural networks, neuromorphic systems, tempotrons, neurophysiological spiking networks
NVIDIA Deep Learning (November 2019)
Fundamentals of deep neural networks, image classification and object detection