Marlan McInnes-Taylor

M.S. Candidate in CS @ UT Austin

Marlan's Headshot

I am Marlan, and thanks for stopping by! 👋

I’m a graduate student in Computer Science at UT Austin, and member of the Brain-Behavior-Computation Lab, advised by Xue-Xin Wei. My research interests lie broadly at the intersection of AI/ML and Neuroscience. I am particularly interested in improving artificial networks and learning paradigms by taking inspiration from their biological correlates.

My current research is focused on lifelong/continuous learning, with the goal of limiting catastrophic forgetting in artificial networks by using learning techniques inspired by complementary learning system theories of human learners.

Previously, I received a B.S. in Computer Science and a B.S. in Applied Mathematics from Florida State University as well as a B.A. in Philosophy from the University of Florida.

In my free time I enjoy various athletic pursuits (running, HIIT, swimming, functional strength training), home network tinkering, hiking, and spectating single-seat racing, particularly Formula 1, Formula 3, Formula Regional, and Formula 4.

news

Feb 28, 2024 I presented the paper Dissecting neural computations in the human auditory pathway using deep neural networks for speech (2023) by Li, Y., Anumanchipalli, G.K., Mohamed, A. et al. at the UT Center for Theoretical and Computational Neuroscience Journal Club.
Jan 01, 2024 I handed off future development of Programming-Contest-Suite to the Florida State University Association for Computing Machinery Student Chapter, and will begin serving as an open source development mentor.
Feb 19, 2023 I served as a student member of the UTCS M.S. Admissions Committee, reviewing applications to the on-campus MSCS program for the Fall 2023 admissions cycle.
Sep 30, 2022 I concluded my internship with i2x Solutions. My contributions included successfully overhauling and optimizing the object detection training and inference pipelines of a multiplatform golf analytics mobile application, and introducing an updated model architecture which improved inference speed and accuracy across all tested devices.
Aug 18, 2022 I joined the Brain-Behavior-Computation Lab as a graduate researcher, advised by Dr. Xue-Xin Wei.

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