My name is Fan Du. I am a 5th year computer science Ph.D. candidate at the University of Maryland, College Park. My advisors are Prof. Ben Shneiderman and Dr. Catherine Plaisant. Prior to joining UMD, I received my master's degree from University of Maryland and bachelor's degree from Zhejiang University, both in computer science.

My research interest lies at the intersection of information visualization, recommender systems, and machine learning. My dissertation is about temporal event sequence recommendation, with applications in student advising, prescriptive marketing, and precision medicine. My dissertation research received Adobe marketing research award ($50,000) and honorable mention award at ACM CHI conference. I have built or contributed to four state-of-the-art event sequence analysis software (EventFlow, EventAction, PeerFinder, and CoCo) that are widely used by corporations (Oracle, Adobe), hospitals (MedStar, Children’s National), and institutes (NIH, CDC).

Recently, I interned at Adobe Research, working on improving the transparency and interactivity of black-box recommendation algorithms. In the last two summers, I interned at IBM Research, where I developed a visual analysis system for large-scale linked data that was funded by DARPA. In the past, I have also worked for Alibaba and Tencent and I founded WaiMai Online, a startup that provided online-to-offline solutions for more than 40 restaurants.

I am graduating in Spring 2018 and looking for full-time opportunities.

Email: [email protected]
Resume: frankdu.org/Fan_Du.pdf
Homepage: frankdu.org
LinkedIn: linkedin.com/in/fandu