Eric Chen
PhD Student, Carnegie Mellon University
ericc3 [AT] andrew.cmu.edu
Bio
I am a first-year PhD student at Carnegie Mellon University. I build principled frameworks that enables reliable inference and decision-making from complex data. My interests include:
AI for Science
How can we integrate modern AI into existing research pipelines to enable valid, explainable inference from complex, high-dimensional data and ensure trustworthy scientific conclusions?
Causal Inference
How can we leverage machine learning tools to estimate causal effects while preserving validity and develop robust methods under modern data challenges like confounding and selection bias?
Data-Driven Decision-Making
What are the fundamental limits of learning in interactive environments, and how can we design provably efficient algorithms with theoretical guarantees that scale to real-world systems?
Previously, I received my bachelor's degrees in Computer Science and Statistics from Columbia University, where I had the great fortune of being advised by Arian Maleki.
Publications
Deep Memory Unrolled Networks for Solving Imaging Linear Inverse Problems PDF
Yuxi Chen, Xi Chen, Shirin Jalali, Arian Maleki
Sampling Theory and Applications (SampTA), 2025 (Oral)
Comprehensive Examination of Unrolled Networks for Solving Linear Inverse Problems PDF
Yuxi Chen, Xi Chen, Arian Maleki, Shirin Jalali
Entropy (Special Issue on Advances in Computational Imaging), 2025
Joint Optimization of Multiple Resources for Distributed Service Deployment in Satellite Edge Computing Networks PDF
Jiachen Sun, Xu Chen, Zhen Li, Jiawei Wang, Yuxi Chen
IEEE Internet of Things Journal, 2024
Vita
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Carnegie Mellon University 2025 - PresentPh.D
Statistics and Data Science -
Columbia University 2021 - 2025Undergraduate
Computer Science and Statistics
Advised by Arian Maleki