Intelligent Mobility · Human-Aware Intelligent Vehicles · Multimodal Perception · Trustworthy & Deployable AI

Human-Centered AI for Intelligent Transportation Systems

I am an Electronics Engineer and AI researcher working on Human-Centered AI for Intelligent Transportation Systems, with a focus on Intelligent Mobility. My interests include intelligent vehicles, computer vision, multimodal learning, trustworthy AI, and deployable intelligent systems.

My research explores AI systems that integrate human, environmental, and operational context to support safer and more adaptive mobility, with particular interest in multimodal perception, human-aware decision support, explainable AI, and real-world deployment.

I also have experience in university teaching and engineering laboratories, and I am interested in an academic trajectory combining research, teaching, advanced training, and international collaboration.

Human-Centered AI Intelligent Transportation Systems Intelligent Mobility Human-Aware Intelligent Vehicles Multimodal Perception Human-Aware Decision Systems Trustworthy & Explainable AI Human-AI Interaction Embedded / Edge AI

research lines

Four complementary directions within a broader research agenda in Human-Centered AI for Intelligent Transportation Systems, with a focus on Intelligent Mobility.

Multimodal Human & Scene Understanding

Integrating visual, behavioral, contextual, and temporal information to model both human state and the surrounding environment.

Human-Aware Assistance & Automation

Adaptive assistance, shared control, and decision support that account for human state, uncertainty, and driving context.

Trustworthy & Explainable AI

Robust, interpretable, and uncertainty-aware AI for safety-critical perception and decision-making.

Deployable & Edge AI

Efficient multimodal systems designed for real-time deployment under practical sensing, computational, and operational constraints.

news

Sep 2026 Paper Confidence-Controlled XAI Auditing for Pedestrian Detection under Domain Shift accepted as a Regular Paper at IEEE ICVES 2026.

Aug 2026 Extending the driver-monitoring benchmarking work toward deployment-aware, non-compensatory evaluation across robustness, efficiency, explainability, and generalization.

Jul 2026 Completed master's thesis research on driver-grouped conformal risk control and graded longitudinal fallback for Level 2 automated driving; journal manuscript submitted.

Jun 2026 Released the preprint Beyond aggregate scores: Deployment-aware and non-compensatory benchmarking of vision-based eye-state recognition models for driver monitoring on arXiv. → preprint · code

Oct 2024 Published a real-time embedded driver-drowsiness system on NVIDIA Jetson Nano in Sensors 24(19). → paper