Bio

我长期从事计算机科学与生命医学的交叉研究，拥有南佛罗里达大学计算机科学与工程博士学位。研究方向涵盖人工智能、大语言模型、网络安全以及多组学大数据分析。近年来主持和参与了多项重要项目，包括基于大模型的基因组精确分类、对抗攻击算法设计以及非侵入性产前检测的深度学习方法，并在 Cell Reports Medicine 等国际一流期刊发表成果。已申请多项专利，涉及cfDNA早期预测、基因型重构与疾病风险评估。当前主要致力于推动人工智能在医学与复杂系统中的应用与创新。

Education History

  • Ph.D. in Computer Science and Engineering

    University of South Florida

    2020 - 2024

Research Interests

My research lies at the intersection of bioinformaticsartificial intelligenceand computational biology. I am particularly interested in developing intelligent models for genomic and medical data analysisadvancing methods for medical diagnosticsand investigating the robustness of AI systems. By combining data-driven approaches with biological insightmy work aims to improve the precisionreliabilityand scalability of computational tools for health and life sciences.

Published Works

  • Smartphone Location Spoofing Attack in Wireless Networks

    Chengbin Hu, Yao Liu, Lu Zhuo, Shangqing Zhao, Xiao Han, Junjie Xiong
    International Conference on Security and Privacy in Communication Systems
    2021CCF C

  • A machine learning framework for studying domain generation algorithm (DGA)-based malware

    Tommy Chin, Kaiqi Xiong, Chengbin Hu, Yi Li
    International Conference on Security and Privacy in Communication Systems
    2018CCF C

  • EGFR and CYP signaling disruption underlies 6PPD-quinone hepatotoxicity: Insights from a network and machine learning approach

    Zhang Wenjie, Wu Banghua, Chengbin Hu, Rong Weifeng, Huang Yongshun, Hu Shijie, Qin Yiru
    Toxicology
    2025

  • Self-Learning Neural Network as a Prediction Model in Non-Invasive Prenatal Testing to Detect Fetal SNVs

    Yiming Qi, Chengbin Hu, Jiexia Yang, Ya Gao, Aihua Yin
    Journal of Translational Medicine
    2024

  • Longitudinal integrative cell-free DNA analysis in gestational diabetes mellitus

    Zhuangyuan Tang, Shuo Wang, Xi Li, Chengbin Hu, Qiangrong Zhai, Jing Wang, Qingshi Ye et al.
    Cell Reports Medicine
    2024