I'm working on a project and I created doc2vec representation of different academics which include their patents and publications etc. For each publication and patent I have information such as title and abstract. Now, I want to do a search on all of the professors and find which professor is the most similar to a query string, such as "deep learning" or "computer networking". I have tried to use the infer_vector() to create a doc2vec representation of the query string using the already generated model and calculate the cosine similarity between the vectors. But I got terrible results. For example, when I search for "computer networking", it will give me the result of professor from History. Is there any recommendation of how to find most similar document to a query string?