# Cho‐Jui Hsieh

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/cho-jui-hsieh/

## Facts

| Field | Value |
| --- | --- |
| Citations | 26,886 |
| Field | Adversarial Robustness in Machine Learning |
| h-index | 68 |
| i10-index | 199 |
| Last Known Institution | University of California, Los Angeles |
| OpenAlex ID | https://openalex.org/A5010841999 |
| ORCID iD | https://orcid.org/0000-0002-3520-9627 |
| Works | 461 |

## Researcher topics

- [Adversarial Robustness in Machine Learning](https://scholariq.org/topics/adversarial-robustness-in-machine-learning/)
- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [Domain Adaptation and Few-Shot Learning](https://scholariq.org/topics/domain-adaptation-and-few-shot-learning/)
- [Topic Modeling](https://scholariq.org/topics/topic-modeling-2/)
- [Anomaly Detection Techniques and Applications](https://scholariq.org/topics/anomaly-detection-techniques-and-applications/)

## Researcher university

- [University of California, Los Angeles](https://scholariq.org/institutions/university-of-california-los-angeles/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.