Chuyang Ke

Engineering · Purdue University West Lafayette

Mid career · publishing since 2016

Sparse and Compressive Sensing Techniques Markov Chains and Monte Carlo Methods Machine Learning and Algorithms Complex Network Analysis Techniques Computational Drug Discovery Methods

Publications

Citations

Est. group size

—

Recurring co-author estimate

Active years

Publishing since 2016

Research summary

AI-generated

Chuyang Ke works on theoretical questions in statistics and machine learning, particularly the mathematical limits and algorithms for recovering hidden structure from noisy or incomplete data. This includes topics like structured prediction (inferring complex outputs such as labels or graphs with dependencies), community detection in networks (finding hidden groups in relational data), and sparse/tensor-based methods for high-order data models. Much of the work is mathematically oriented, establishing theoretical guarantees for when exact recovery or inference is possible.

Structured prediction and exact inferenceCommunity detection in networks and hypergraphsSparse and tensor-based recovery methodsInformation-theoretic limits of statistical estimationConvex and combinatorial optimization for machine learning

Publication output has been irregular over the past decade, peaking around 2021 with five papers but slowing to zero or one per year in 2024 and 2025.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence

Publications per year over the last 10 years — averaging 1.2/year recently

Recent publications

Partial Inference in Structured Prediction
2025
Exact Inference in High-order Structured Prediction
arXiv (Cornell University) · 2023
Partial Inference in Structured Prediction
arXiv (Cornell University) · 2023
Exact Partitioning of High-Order Planted Models with A Tensor Nuclear Norm Constraint
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) · 2022
Provable Guarantees for Sparsity Recovery with Deterministic Missing Data Patterns
arXiv (Cornell University) · 2022
Dual Convexified Convolutional Neural Networks
arXiv (Cornell University) · 2022
Information Theoretic Limits of Exact Recovery in Sub-hypergraph Models for Community Detection
2021
Federated Myopic Community Detection with One-shot Communication
arXiv (Cornell University) · 2021
Information Theoretic Limits of Exact Recovery in Sub-hypergraph Models for Community Detection
arXiv (Cornell University) · 2021
A Thorough View of Exact Inference in Graphs from the Degree-4 Sum-of-Squares Hierarchy
arXiv (Cornell University) · 2021
A Thorough View of Exact Inference in Graphs from the Degree-4\n Sum-of-Squares Hierarchy
arXiv (Cornell University) · 2021
Exact Partitioning of High-order Planted Models with a Tensor Nuclear Norm Constraint
arXiv (Cornell University) · 2020
Exact Recovery in the Latent Space Model.
arXiv (Cornell University) · 2019
Exact Partitioning of High-order Models with a Novel Convex Tensor Cone Relaxation
arXiv (Cornell University) · 2019
Exact Inference with Latent Variables in an Arbitrary Domain
arXiv (Cornell University) · 2019

Publishes in

arXiv (Cornell University)×15
Journal of Biomedical Informatics×1
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)×1
International Conference on Machine Learning×1

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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 20, 2026.

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