About

Hi! I am a PhD student in the Neural Computation and Machine Learning Joint Program at Carnegie Mellon University, advised by Prof. Pulkit Grover and Prof. Robert Kass. My research lies at the intersection of machine learning and brain-computer interfaces. Specifically, I work on two directions.

  • Reading the brain through source localization and neural time-series analysis.
  • Intervening with the brain through spatially and temporally optimized electrical stimulation.

Reading or intervening, I design algorithms that are accurate, safe, and reliable enough to actually trust on a brain.

Previously, I received my B.S. in Electrical and Computer Engineering from Carnegie Mellon University.

Recent News

  • [05/26] Our work on uncertainty quantification in deep generative models is accepted to the ICML Foundations of Deep Generative Models workshop. See you in Seoul!
  • [01/26] Our paper on fundamental limits of EEG sensing is accepted to AISTATS!
  • [11/25] Presented our work at the IEEE NER conference!

Selected Publications

2026
  1. In submission Separating Intrinsic Ambiguity from Estimation Uncertainty in Deep Generative Models for Linear Inverse Problems
    Yuxin Guo, Dongrui Deng, Pulkit Grover.
  2. In submission Interpreting Neural Combinatorial Optimization via Evolving Programmatic Bottlenecks
    Haocheng Duan*, Yuxin Guo*, Jieyi Bi, Anqi Xie, Sirui Li, Yining Ma, Cathy Wu. (*equal contribution)
  3. AISTATS 2026 Information-theoretic Error Bounds for Source Localization in Neural Sensing
    Leighton Barnes, Yuxin Guo, Alex Dytso, Pulkit Grover.
2025
  1. IEEE NER 2025 Identifying Neural Biomarkers of Risk-Taking from Intracranial EEG Recordings
    Yuxin Guo, Amanda Merkley, Stephen Jaffee, Alex Whiting, Pulkit Grover.
  2. Journal of Neural Engineering 2025 DeepFocus: A Transnasal Approach for Optimized Deep Brain Stimulation of Reward Circuit Nodes
    Yuxin Guo*, Mats Forssell*, Dorian Kusyk, Vishal Jain, Isaac Swink, Owen Corcoran, Yuhyun Lee, Chaitanya Goswami, Alexander C. Whiting, Boyle C. Cheng, Pulkit Grover. (*equal contribution)
2023
  1. IEEE EMBC 2023 EEG Source Imaging of Infarct Core and Penumbra for Ischemic Stroke Patients
    Yuxin Guo, Kriti Kacker, Alireza Chamanzar, Pulkit Grover.
  2. Brain Informatics 2023 Effects of EEG Electrode Numbers on Deep Learning-Based Source Imaging
    Jesse Rong, Rui Sun, Yuxin Guo, Bin He.

Selected Awards

  • Center of Machine Learning and Health, Translational Fellowship in Digital Health, 2024
  • E.M. Williams Award (in recognition of a graduating senior with superior scholastic achievement), 2022
  • Senior Research Honors, 2021

Teaching

  • Data-Driven AI for Dynamic Systems Control (18-879) — Carnegie Mellon University, Spring 2025
  • Introduction to Machine Learning (10-601) — Carnegie Mellon University, Spring 2022

Blog

Coming soon.