Hao-Fei Cheng

About Hao-Fei Cheng

Hao-Fei Cheng, With an exceptional h-index of 9 and a recent h-index of 9 (since 2020), a distinguished researcher at University of Minnesota-Twin Cities, specializes in the field of Human-Computer Interaction, Social Computing.

His recent articles reflect a diverse array of research interests and contributions to the field:

Why do customers return products? Using customer reviews to predict product return behaviors

Searching for products in virtual reality: Understanding the impact of context and result presentation on user experience

Edgexar: A 6-dof camera multi-target interaction framework for mar with user-friendly latency compensation

“Why Do I Care What’s Similar?” Probing Challenges in AI-Assisted Child Welfare Decision-Making through Worker-AI Interface Design Concepts

Extended Analysis of" How Child Welfare Workers Reduce Racial Disparities in Algorithmic Decisions"

How child welfare workers reduce racial disparities in algorithmic decisions

Improving human-AI partnerships in child welfare: understanding worker practices, challenges, and desires for algorithmic decision support

A sandbox tool to bias (stress)-test fairness algorithms

Hao-Fei Cheng Information

University

Position

___

Citations(all)

769

Citations(since 2020)

729

Cited By

201

hIndex(all)

9

hIndex(since 2020)

9

i10Index(all)

9

i10Index(since 2020)

9

Email

University Profile Page

Google Scholar

Hao-Fei Cheng Skills & Research Interests

Human-Computer Interaction

Social Computing

Top articles of Hao-Fei Cheng

Why do customers return products? Using customer reviews to predict product return behaviors

2024

Hao-Fei Cheng
Hao-Fei Cheng

H-Index: 5

Searching for products in virtual reality: Understanding the impact of context and result presentation on user experience

2023/7/19

Edgexar: A 6-dof camera multi-target interaction framework for mar with user-friendly latency compensation

Proceedings of the ACM on Human-Computer Interaction

2022/6/17

“Why Do I Care What’s Similar?” Probing Challenges in AI-Assisted Child Welfare Decision-Making through Worker-AI Interface Design Concepts

2022/6/13

Extended Analysis of" How Child Welfare Workers Reduce Racial Disparities in Algorithmic Decisions"

arXiv preprint arXiv:2204.13872

2022/4/29

How child welfare workers reduce racial disparities in algorithmic decisions

2022/4/27

Improving human-AI partnerships in child welfare: understanding worker practices, challenges, and desires for algorithmic decision support

2022/4/27

A sandbox tool to bias (stress)-test fairness algorithms

arXiv preprint arXiv:2204.10233

2022/4/21

Advancing Explainability and Fairness in AI with Human-Algorithm Collaborations

2022

Hao-Fei Cheng
Hao-Fei Cheng

H-Index: 5

Soliciting stakeholders’ fairness notions in child maltreatment predictive systems

2021/5/6

Understanding community-level conflicts through Reddit r/place

2020/10/17

See List of Professors in Hao-Fei Cheng University(University of Minnesota-Twin Cities)

Co-Authors

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