Alliot Nagle
Graduate Research Assistant
United States
Summary
👤
Senior🎓
Top SchoolAlliot Nagle is a PhD student and graduate research assistant at UT Austin specializing in the intersection of information theory and machine learning, with research focused on large language models, representation learning, and methods for accelerated training and inference. With eight years of experience spanning academic research, EEG/fMRI modeling, and industry internships in data science and hardware design, he blends rigorous theoretical grounding with practical systems and high-throughput computing. His work has applied statistical models like MVARX with group LASSO and leveraged meta-schedulers (DAGman) for large-scale cross-validation pipelines, showing a knack for scalable experimental design. An award-winning teaching assistant, he also brings strong communication and pedagogy to mentor-driven research settings. Outside core research, he has driven impactful applied projects—such as high-savings predictive maintenance algorithms—and maintains a public profile at acnagle.com.
8 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Electrical and Electronics Engineering, Doctor of Philosophy - PhD, Electrical and Electronics Engineering at The University of Texas at AustinMaster of Science - MS, Electrical Engineering, Master of Science - MS, Electrical Engineering at University of Wisconsin-Madison
Github Skills (8)
compression7
inference5
pytorch4
llm4
deepspeed3
iphone1
ipad1
cider1
Programming languages (3)
Github contributions (5)
acnagle/acnagle.github.io
Dec 2018 - Jun 2026
Contributions:101 pushes, 1 branch in 7 years 7 months
acnagle/CLA-Project
Dec 2018 - Jan 2020
Contributions:90 pushes in 1 year 1 month
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