Huyunting Huang
Computer Science · Purdue University West Lafayette
Publications
18
Citations
50
Est. group size
~2
Recurring co-author estimate
Active years
8
Publishing since 2019
This researcher works on methods for analyzing large, complex datasets, including techniques for data compression and pattern-finding (tensor decomposition), grouping similar data points (clustering), and statistical prediction methods (regression) for high-dimensional data such as images and videos. Recent work also applies deep learning models, including vision transformers, to medical signal data (EEG) for predicting delirium, a condition affecting mental clarity in patients. The work spans methodological development in statistics and machine learning as well as applied healthcare data analysis.
Publication output has been modest but fairly steady over the last decade, with small yearly counts (0-4 papers) and no clear long-term growth or decline.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Unsupervised Variable Selection for Ultrahigh-Dimensional Clustering Analysis
arXiv (Cornell University) · 2024
- Supervised deep learning with vision transformer predicts delirium using limited lead EEG
Scientific Reports · 2023
- Improved Clustering Using Nice Initialization
2023
- Supervised Deep Learning with Vision Transformer Predicts Delirium Using Limited Lead EEG
Scholar Commons (University of South Carolina) · 2023
- Tensor Decomposition for High-Resolution Images and Videos
Research Square · 2022
- Vision Transformer Prediction of Delirium
Research Square · 2022
- Managing Controlled Unclassified Information in Research Institutions
arXiv (Cornell University) · 2022
- HOOD: High-Order Orthogonal Decomposition for Tensors
Lecture notes in computer science · 2021
- Regression PCA for Moving Objects Separation
2020
- Low-Rank Sparse Tensor Approximations for Large High-Resolution Videos
2020
- Multiple Learning for Regression in Big Data
2019
- Sparse Block Regression (SBR) for Big Data with Categorical Variables
2019
- Multiple Learning for Regression in big data
arXiv (Cornell University) · 2019
- Regression Principal Analysis
INDIGO (University of Illinois at Chicago) · 2019
- arXiv (Cornell University)×4
- Research Square×2
- Scientific Reports×1
- Lecture notes in computer science×1
- INDIGO (University of Illinois at Chicago)×1
- Thái Hoàng Lê
Computer Science · Indiana University
- Aleix M. Martı́nez
Computer Science · The Ohio State University
- Parichit Sharma
Computer Science · Indiana University
- Qiang Qiu
Computer Science · Purdue University West Lafayette
- Haoyu Chen
Computer Science · Purdue University West Lafayette
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.
Claim or correct this profile