Feng Zhou

Assistant professor

University of Michigan

United States

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Feng Zhou is an Assistant Professor at the University of Michigan, USA. His research areas encompass automated driving, including risk perception, driver experience, and trust in autonomous vehicles. He also contributes to advancements in brain disorder diagnosis and engineering system design through innovative modeling and algorithm development.

Articles (17)

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2025

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2022

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2022

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2022

Collaborators (2)

Alejandro Frangi

Prof

The University of Manchester

UNITED KINGDOM

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X. Jessie Yang

University of Michigan

UNITED STATES

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Feng Zhou

Research Interests

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About

Articles (17)

The mediating effects of emotions on trust through risk perception and system performance in automated driving

A Systematic Review of Metrics Measuring Takeover Performance in Conditionally Automated Driving

How LLM-Awareness and Explanation Format Shape Driver Experience During AV Anomalies

Towards Context-Aware Modeling of Situation Awareness in Conditionally Automated Driving

Knowledge-Aware Multisite Adaptive Graph Transformer for Brain Disorder Diagnosis

Investigating HMIs to Foster Communications Between Conventional Vehicles and Autonomous Vehicles at Intersections

Building Contextualized Trust Profiles in Conditionally Automated Driving

Real-Time Trust Prediction in Conditionally Automated Driving Using Physiological Measures

Multicenter and Multichannel Pooling GCN for Early AD Diagnosis Based on Dual-Modality Fused Brain Network

A twofold update quantum-inspired genetic algorithm for efficient combinatorial optimal decisions in engineering system design and operations

MHW-GAN: Multidiscriminator Hierarchical Wavelet Generative Adversarial Network for Multimodal Image Fusion

Disengagement Cause-and-Effect Relationships Extraction Using an NLP Pipeline

Predicting Driver Takeover Time in Conditionally Automated Driving

Using Eye-Tracking Data to Predict Situation Awareness in Real Time During Takeover Transitions in Conditionally Automated Driving

Design a sustainable micro-mobility future: trends and challenges in the US and EU

An Investigation of Drivers’ Dynamic Situational Trust in Conditionally Automated Driving

Predicting Driver Fatigue in Monotonous Automated Driving with Explanation using GPBoost and SHAP

Collaborators (2)

Alejandro Frangi

X. Jessie Yang

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