I am an applied scientist at Amazon on the Alexa Shopping science team. I was formerly a research scientist at GroupLens, the social computing group at the University of Minnesota, where I worked on the MovieLens project.
As a researcher, I build and study personalization technology in online systems. I think it is important and interesting to study humans, algorithms, and interfaces together. I specialize in quantitative, empirical methods, but I like employing multiple methods, and I enjoy branching out.
See Google Scholar for an exhaustive list of publications. If you'd like to get a sense for my research, start with these:
Yuan Yao and F. Maxwell Harper. 2018. Judging Similarity: A User-centric Study of Related Item Recommendations. In Proceedings of the 12th ACM Conference on Recommender Systems (RecSys ’18), 288–296. https://doi.org/10.1145/3240323.3240351
F. Maxwell Harper, Funing Xu, Harmanpreet Kaur, Kyle Condiff, Shuo Chang, and Loren Terveen. 2015. Putting Users in Control of Their Recommendations. In Proceedings of the 9th ACM Conference on Recommender Systems (RecSys ’15), 3–10. https://doi.org/10.1145/2792838.2800179
F. Maxwell Harper, Daniel Moy, and Joseph A. Konstan. 2009. Facts or Friends? Distinguishing Informational and Conversational Questions in Social Q&A Sites. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’09), 759–768. https://doi.org/10.1145/1518701.1518819