How to approach clustering of time-series with a single variable
Welcome to the community Blitva!

There are things to clear at the beginning:


You may cluster authors based on their time-series but it does not necessarily answer the question you asked. How prolific they were in a certain time-period might need another approach to the problem. In other words, you may cluster the authors but you don't necessarily know what was the reason behind that unless you explicitly define Similarity based on which clusters are formed.
Feature Extraction is sometimes needed when you want a specific question to be answered. See my example bellow to understand it more.
What does being prolific in a certain time period mean? Imagine a person who published 1 2 1 papers in 3 consecutive years and another one who published 10 20 10 papers in those days. Are they similar? If being prolific is calculated between them they are certainly not similar. But if it is calculated according to each person, then they have completely similar patterns of being prolific! Which one are you looking for?


Now back to the question. My answer is as follows:

If you are looking for similar patterns i.e. rise and fall in the number of publications, go for DTW for calculating the similarities. I am sure there are R implementations of DTW but I am a Python guy ;) After calculating pairwise DTW similarities, you may apply your Hierarchical Clustering to it (or maybe some other algorithms like Spectral Clustering).

Good Luck!