Personal information
Master Tutor
Gender:Male
Education Level:博士研究生毕业
Alma Mater:University of the West of England
Degree:博士学位
Status:Job
School/Department:重庆交通大学
Discipline:计算机科学与技术
Contact Information:zhangtianchi@cqjtu.edu.cn
E-Mail:46519d424d7590e5dcc4815d43328f3d05469587709ba8318e51fee240e4a98efca39e8eab3c648c2800d20535b44fcbec41001b4c56c335116a5701c39429d23094035b54eaa648adc7371511d6b4a8d7297b5fed68bfcf237ddfbefea29f107a09b9a3a2bfeb925dfc20b0d7e2bc7bce8f93232f1679abfa27d1f63f3e1904
Personal Profile
Doctoral Supervisor Profile
Chongqing Jiaotong University
Master's Supervisor in Computer Science and Technology, College of Information Science and Engineering
Positions:
- Associate Director, Artificial Intelligence Research Institute, College of Information Science and Engineering
- Editorial Reviewer for Academic Journals
- Member of the Professional Committee on Intelligent Control and Intelligent Management, Chinese Association for Artificial Intelligence (CAAI)
Research Projects:
- Principal Investigator of 1 National Natural Science Foundation Project (Youth Program): *Research on Visual Image Restoration Methods for AUV Autonomous Operations (52001039)*
- Lead Investigator of 1 National Key Laboratory Project
- Participant in 5 National Natural Science Foundation Projects, including:
- *Medical Media Data Mining Technology Based on Multimodal Correlation Graphs (61672181)*
- *Research on Ship Drift Model Technology with Multi-Factor Information Imbalance Based on Perturbation Wave Spectrum Modeling (51679058)*
Patents:
- 8 authorized national invention patents, including:
- 6 filed as first inventor
- 2 authorized as second inventor
Publications:
- 25 published papers, including 13 first-authored SCI-indexed papers
Awards:
- Provincial/Ministerial Level Science and Technology Award (Second Class)
Professional Services:
- AC Member of CCF YOCSEF Chongqing
- Reviewer for international journals such as *IEEE Transactions on Medical Imaging* and *IEEE Transactions on Biomedical Engineering*
Research Interests:
- AUV underwater image restoration
- Underwater image recognition
- Underwater image enhancement
- Machine learning
- Deep neural networks
Graduate Supervision:
Supervised 8 postgraduate students since 2020, with 3 already graduated.
Admission Requirements:
1. Background in Computer Science and Technology or Electronic Information Engineering.
2. Prospective students are advised to contact via email in advance, attaching a resume (including postgraduate entrance examination scores).
3. The supervisor is committed to providing support within their capacity during the study period.
Welcome students interested in underwater image restoration and machine learning to apply and collaborate on related research!
zhangtianchi@cqjtu.edu.cn
Other Contact information
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Education Experience
-
重点大学 | 计算机科学与技术(计算机软件开发) | 博士研究生毕业 | 博士学位
本硕博连读
Work Experience
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信息学院 | 人工智能研究所 | 信息学院 | 副所长
Social Affiliations:
Research Focus
研究方向聚焦于解决水下复杂环境带来的视觉挑战,核心涵盖水下图像复原、识别与增强。研究旨在通过先进的机器学习与深度神经网络技术,开发创新算法,以有效克服水下图像存在的颜色失真、低对比度与雾化模糊等问题。具体研究包括基于物理模型的水下图像复原、面向AUV自主作业的实时视觉处理、以及基于深度学习的水下目标智能识别。本方向致力于将理论创新与工程应用紧密结合,研究成果可广泛应用于海洋勘探、水下机器人作业、生态监测及国防安全等领域,旨在提升智能系统对水下环境的感知与认知能力,为认识海洋、经略海洋提供关键的视觉技术支撑
水下目标识别与理解
聚焦于复杂水下场景中的目标检测、识别与分割问题。
研究轻量化、高效率的深度神经网络模型,以满足自主水下航行器(AUV)等平台对实时视觉感知的迫切需求。前沿技术探索与应用
深度融合机器学习、计算机视觉与海洋工程知识。
推动研究成果在海洋资源勘探、水下机器人自主作业、生态环境监测及国防安全等领域的实际应用。
本研究方向旨在通过理论创新与技术突破,全面提升智能装备对水下环境的感知能力,为认识与开发海洋提供关键的视觉技术支撑。


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