Under the new situation, student management work in colleges and universities must keep pace with the development of information technology, take the initiative to comply with the laws of the new era, innovate work concepts, revolutionize work methods, and make full use of the new era technology to improve the level of management services. After integrating and optimizing the management mechanism of student work in colleges and universities, the study establishes a deep neural network-based student management work effect assessment model in colleges and universities using cluster analysis and convolutional neural network and takes 20 colleges and universities in city A as examples to conduct empirical analysis. The results show that the fit of the CNN neural network model is relatively good, and the total R value is 0.99634, R2 = 0.98324, R2 is greater than 0.75. The student work management mechanism has been optimized and integrated by 13 colleges and universities, and their scores are all above 80 points. Among them, there are 5 colleges and universities whose evaluation results exceed 90 points. The construction of their student management cadres, the construction of student self-government capacity, the construction of school spirit and academic style, the work of campus security and stability, and the campus cultural activities have achieved better optimization results.