主要研究方向包括计算机视觉、人工智能算法等；

人工智能算法研究：深度学习算法、多模态大模型、小样本学习；侧重处理和理解图像、文本、音频、视频等多种模态的信息，实现跨模态的交互与推理，并力图在某些垂直领域设计理想通用的多模态模型。

计算机视觉：语义分割，3D语义分割，小样本图像语义分割，情感识别；研究侧重对自然场景的理解，以便应用于具身智能领域。

无线电信号识别：通信信号的识别分类；侧重将辐射源信号（如雷达或通信设备）进行检测并且实现个体识别和解析。

[1]    Hai Min, Wei Jia, Yang Zhao, Wangmeng Zuo, Haibin Ling, Yuetong Luo: LATE: A Level Set Method Based on Local Approximation of Taylor Expansion for Segmenting Intensity Inhomogeneous Images. IEEE Transaction on Image Processing, 27(10):5016-5031,2018

[2]     Hai Min, Li Xia, Junwei Han, Xiaofeng Wang, Qianqian Pan, Hao Fu, Hongzhi Wang, Stephen T.C. Wang, Hai Li: A multi-scale level set method based on local features for segmentation of images with intensity inhomogeneity, Pattern Recognition, 91:69-85, 2019,

[3]    Hai Min, Jingting Lu, Wei Jia, Yang Zhao, Yuetong Luo: An Effective Local Regional Model Based on Salient Fitting for Image Segmentation. Neurocomputing 311:245-259,2018

[4]    Hai Min, Wei Jia*, Xiao-Feng Wang, Yang Zhao, Jing-Ting Lu, Yue-Tong Luo: A Polynomial Piecewise Constant Approximation Method Based on Dual Constraint Relaxation for Segmenting Images with Intensity Inhomogeneity. Pattern Recognition, 73(1):15-32(2018)

[5]     Hai Min, Xiao-Feng Wang*, De-Shuang Huang, Wei Jia, “A novel dual minimization based level set method for image segmentation” Neurocomputing 2016

[6]    Hai Min, Wei Jia*, Xiao-Feng Wang, Yang Zhao, Rong-Xiang Hu, Yue-Tong Luo, Feng Xue, Jing-Ting Lu: An Intensity-Texture model based level set method for image segmentation. Pattern Recognition 48(4): 1547-1562 (2015)