Expert finding is an important part of entity retrieval. Classical expert finding models rest upon the conditional independence assumption between the candidate and term-given document. However, this assumption is usually invalid in real world applications, which makes the performances of classical expert finding models not ideal. In this research, an expert finding method is proposed based on the topic model (EFTM). This method discards the conditional independence assumption in classical models and is more maneuverable. In addition, a ranking truncation approach which largely decreases the computational complexity of the model was used. Finally, the performances of the new model were evaluated using the CSIRO Enterprise Research Collection. The results shows that the EFTM model outperformed the classical model significantly on all the metrics and can effectively improve the performances of the expert finding system. 