The biological brain is the only example of general intelligence that we know of. What are the core design principles that give rise to this remarkable ability? Since the brain came about through a complicated evolutionary process, identifying these principles a priori is challenging. The approach I take to understand these constraints is by simulating the evolutionary process via in silico neural network models that toggle four main components of “architecture class”, “objective function”, “data stream”, and “learning rule”. By comparing the artificial networks that arise from these components to quantitative metrics on high-throughput neural recordings and behavioral data, the long-term aim is to produce better normative accounts for how the brain produces intelligent behavior and build better artificial intelligence algorithms along the way.
If you are interested in my research, feel free to reach out!
PhD in Neuroscience, 2016 - 2022
MS in Computer Science, 2015 - 2017
BS in Mathematics, 2011-2015