Qihong Xue

Doctoral Candidate

Primary research focus is on autonomous driving decision-making and control, currently specializing in large model-empowered single-vehicle intelligence/multi-vehicle collaborative control. During my laboratory tenure, I have participated in multiple projects and gained substantial hands-on experience. Future plans involve exploring various directions in AI4Vehicle.

Research Interest:

• Intelligent Driving Decision-Making
• Large Language Models
• Artificial Intelligence

Bo Li

Master's Candidate

My primary research area is cybersecurity in vehicular networks, with current specialization in identity authentication mechanisms. The objective is to establish a secure and robust vehicular network ecosystem. I welcome collaborations with fellow researchers who share interests in this field for mutual academic advancement.

Research Interest:

• Vehicular Network Security

Jinyuan Shao

Master's Candidate

My primary research interests lie in video object segmentation and acceleration of visual-language large model inference. During my laboratory tenure, I participated in the end-to-end development of industrial software (based on the Qt application framework), implementing parallel execution and interactive optimization for multi-task systems.

Research Interest:

• Video Object Segmentation
• Vision-Language Models

Tianci Huo

Master's Candidate

The primary research focus is on autonomous driving perception, with a current emphasis on compression techniques for VLMs. During the lab tenure, the work involved image processing, VLM perception, and model compression technologies, leading to the development of a multi-network architecture-based strong consistency specular highlight removal algorithm and an N:M sparse structure-based VLM pruning technique. Future plans include exploring the application and deployment of VLMs in vehicle systems.

Research Interest:

• Deep Learning
• Vision-Language Models (VLMs)
• Model Compression

Hai Yu

Master's Candidate

My main research focus is autonomous driving planning, with current work centered on interactive prediction-planning optimization. Future research will explore quantization and deployment of large-scale models.

Research Interest:

• Decision-Making and Planning for Autonomous Driving

Zhigui Chen

Master's Candidate

The main research direction is autonomous driving perception, currently focusing on 3D object detection algorithms that fuse 4D millimeter-wave radar with images.

Research Interest:

• Multi-sensor fusion

Qian Hu

Master's Candidate

My main research focuses on constructing real-world test cases for autonomous vehicles, and I have participated in projects involving test route generation.

Research Interest:

• Autonomous Driving Function Testing
• Autonomous Driving Test Scenario Library Construction

Bingxiang Kang

Master's Candidate

My research is centered around 3D reconstruction, particularly high-fidelity vehicle modeling and dynamic scene reconstruction. In the lab, I've worked on developing collision detection and warning algorithms for robots navigating narrow, reflective spaces. I also built a depth estimation-based algorithm and a software module for loading and visualizing point cloud models. Moving forward, I'm eager to explore new challenges and possibilities in the field of 3D reconstruction.

Research Interest:

• 3D Reconstruction
• SLAM

Tao Jiang

Master's Candidate

Main research focus is on reinforcement learning-based decision-making and control for autonomous driving, currently specializing in multi-agent large-scale model decision-making and control. During the lab research period, participated in a 3D Gaussian-based autonomous driving simulator project, responsible for local Gaussian point cloud editing and deployment.

Research Interest:

• Reinforcement Learning-based Vehicle Decision and Control

Junjie Zhang

Master's Candidate

The current research focuses on multi-sensor fusion-based localization and mapping systems (SLAM), multi-sensor simulation, and LiDAR point cloud processing and registration.

Research Interest:

• Multi-sensor Fusion
• Sensor Simulation
• SLAM

Ke Li

Master's Candidate

During the lab research period, I was primarily engaged in dynamic 3D reconstruction and Unreal Engine 5 plugin development for Gaussian point clouds.

Research Interest:

• Dynamic 3D Reconstruction

Chenfei Guo

Master's Candidate

My primary research area is autonomous driving data synthesis algorithms, with an established pipeline for image data synthesis and ongoing development in trajectory data generation.

Research Interest:

• Data Synthesis
• Trajectory Prediction
• Image Harmonization

Jie Zou

Master's Candidate

My primary research area is autonomous driving scene 3D reconstruction, currently specializing in generative model-based and 3D Gaussian Splatting (3DGS)-enhanced reconstruction. During my laboratory tenure, I contributed to vehicle simulation test scenario construction and developed a dynamic object editing module for autonomous driving scenes.

Research Interest:

• Autonomous Driving Scene 3D Reconstruction

Yingchen Wang

Master's Candidate

The main research focus is on autonomous driving decision-making, currently specializing in reinforcement learning-based decision-making in complex environments.

Research Interest:

• Autonomous Driving Decision-Making
• Diffusion Models

Jun Yan

Master's Candidate

My primary research focuses on decision-making and control for autonomous driving. Currently, I am working on the design of lightweight decision-making models. In the future, I will continue exploring end-to-end model lightweighting techniques and their practical implementation in autonomous driving systems.

Research Interest:

• Autonomous Driving Decision & Control

Funing Cai

Master's Candidate

My primary research area is decision-making for autonomous driving. Currently, I am working on safe reinforcement learning (Safe RL) to achieve high-efficiency decision-making while ensuring safety guarantees. This involves developing algorithms that balance optimal driving performance with rigorous safety constraints in dynamic traffic environments.

Research Interest:

• Reinforcement Learning (RL)

Qi Lan

Master's Candidate

His main research focuses on reinforcement learning, with current specialization in diffusion planning. He plans to further explore applying diffusion models to end-to-end autonomous driving systems in the future.

Research Interest:

• Diffusion Models

Yaohui Ji

Master's Candidate

My research focuses on autonomous driving decision-making, particularly RL and Bézier curve-based trajectory prediction. I developed editable static models in the 3DGS-based UniSim project, with plans for algorithm optimization.

Research Interest:

• RL + Bézier Curves
• Decision-Making And Planning

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Ying Fang

Master's Candidate

I'm currently fascinated by visual perception, particularly 3D reconstruction and multimodal learning. With solid Python skills, I'm actively studying classic models (e.g., CNN, Transformer) and research papers. I look forward to deepening my theoretical understanding through systematic training in the research group while gradually exploring my specialized focus.

Research Interest:

• Computer Vision
• Motion Planning

Yicui Shi

Master's Candidate

My current research primarily focuses on 3D simulation scene reconstruction. During my time in the lab, I have been actively involved in development work related to simulated environment reconstruction. I intend to further explore this field in the future.

Research Interest:

• 3DGS 3D Reconstruction
• Multi-Sensor Fusion Perception

Shuang Liang

Master's Candidate

My primary research focus is on reinforcement learning (RL). During my undergraduate studies, I participated in a SLAM (Simultaneous Localization and Mapping) project at the lab, where I was responsible for the localization and mapping module. In the future, I plan to explore the intersection of reinforcement learning and path planning, along with related research directions.

Research Interest:

• Reinforcement Learning
• Path Planning
• Decision-Making and Control

Yucheng Pan

Master's Candidate

As a member of the Dynamic Reconstruction team, I participated in a UE5-based dynamic reconstruction project, where I was primarily responsible for developing the main interface UI, functional UIs for various features, and interactive bubble UIs with click-based interactions.

Research Interest:

• Dynamic Scene Reconstruction
• Point Cloud Processing

Yi Zhou

Master's Candidate

My research primarily focuses on the decision-making module of autonomous driving systems, specifically investigating how robust reinforcement learning can enhance an agent's decision-making capabilities in complex, uncertain environments. I am dedicated to exploring robustness optimization of reinforcement learning algorithms in dynamic and adversarial scenarios.

Research Interest:

• Robust Reinforcement Learning

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Yu Shen

Master's Candidate

My primary research focus lies in world models, where I'm actively exploring their integration with robust reinforcement learning (RRL). I aim to make continuous advancements in these cutting-edge AI domains and contribute meaningful research outcomes.

Research Interest:

• World Models
• Robust RL

Chen Yang

Master's Candidate

My current research focuses on large language models (LLMs) for autonomous driving applications, with particular emphasis on vision-language models (VLMs) for scene understanding. In the future, I plan to explore multimodal large models and lightweighting techniques for large models to enhance their practicality in real-world autonomous systems.

Research Interest:

• End-to-End Foundation Models
• Edge AI
• Reinforcement Learning

Rende Chen

Master's Candidate

My primary research focuses on reinforcement learning (RL) for decision-making. During my laboratory tenure, I contributed to the UniSim project by developing its dynamically editable modules. I plan to further explore RL applications in autonomous driving decision systems, particularly for complex urban scenarios.

Research Interest:

• Reinforcement Learning Decision-Making

Wenxuan Yu

Master's Candidate

The field I'm most interested in is computer vision, and I'm currently at the learning stage of 3D point cloud object detection and segmentation algorithms. I hope to continuously improve myself during future learning and exploration.

Research Interest:

• Computer Vision
• Point Cloud Data Processing

Yuhao Wei

Master's Candidate

My primary research focuses on decision-making and motion planning for autonomous vehicles, with current emphasis on learning-based end-to-end algorithms. In the future, I plan to explore applications of multimodal large models, diffusion models, and Mixture-of-Experts (MoE) architectures in autonomous driving systems.

Research Interest:

• End-to-End Autonomous Driving Systems
• Reinforcement Learning
• VLM/VLA

Zhongquan Wang

Master's Candidate

2021.9-2024.6, Chongqing University of Posts and Telecommunications, Undergraduate, IoT Engineering
2024.9-2025.6, Chongqing University National Excellent Engineer College, Exchange Student, Intelligent Connected Vehicle
2025.9- , Chongqing University , Master's Student, Robotics Engineering

Research Interest:

• Intelligent Connected Vehicles
• Some interesting things

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