Summary
Gautham Gudur is a Ph.D. student and graduate research assistant at UT Austin with a decade of experience building resource-efficient, data-centric machine learning systems across health sensing, multimodal sensing, and telecom domains. He combines industry R&D experience at Ericsson and Nokia Bell Labs with hands-on work on on-device and time-series models for health from roles at SmartCardia and prior research projects. His research focuses on data- and parameter-efficient methods—continual, active, federated and Bayesian learning—applied to inertial, audio, and clinical sensing as well as foundation models and LLMs. He also teaches deep learning and human signals courses, mentoring students in practical project development and paper reviews. Notably, Gautham bridges applied telecommunication AI and medical wearable analytics, bringing a rare mix of production-facing ML engineering and academic research.
9 years of coding experience
8 years of employment as a software developer
Deep Learning and Healthcare, Deep Learning and Healthcare at Oxford Machine Learning Summer School (OxML)
Higher Secondary School Examination (HSC), Higher Secondary School Examination (HSC) at DAV Higher Secondary School
Computer Vision and Machine Learning, Computer Vision and Machine Learning at Summer School on Artificial Intelligence
Doctor of Philosophy - PhD, Electrical and Computer Engineering, Doctor of Philosophy - PhD, Electrical and Computer Engineering at The University of Texas at Austin
Deep Learning and Reinforcement Learning, Deep Learning and Reinforcement Learning at Eastern European Machine Learning Summer School (EEML)
Bachelor of Technology - BTech, Information Technology, Bachelor of Technology - BTech, Information Technology at SSN College of Engineering
English, Tamil, Hindi