Xuan has been working with data in multiple modalities, including  physicians' clinical diagnostic narratives,  their eye movements over medical images, and general users' electroencephalographic data, etc. He was involved with all stages, such as experimental design, data collection, processing, data mining, and modeling.

His theoretical contributions are a variational algorithm of representation learning, a data fusion algorithm for heterogeneous data, and an interactive machine learning paradigm to allow human collaborations with machines in the learning loop. He has also applied these algorithms to developing systems, such as a multimodal information retrieval system, and an expert-in-the-loop medical image grouping system.

Beside working on the above topics, Xuan also participated in many other projects. For example, he interned at Amazon.com LLC with a team to develop web services for some business logics. During the internship, he migrated a database, developed APIs accessing the new database. Dates back to his undergraduate, Xuan developed a 3D game for psychological study of fire escape from indoor virtual environment, and that project was awarded the 2nd place under National Undergraduate Project Award in China.

Additionally, Xuan has other roles to service the academic/technical community. He accepted to review papers from multiple conferences and journal venues in the field. He served as guest speakers in a variaty of courses, including natural language processing, usability testing, and many yearly workshops and symposiums at RIT. He also volunteered at the Lollypop Farm as a data analyst, hosted a few on-campus EEG device demonstrations, and implemented their research group website.

A Summary of Research Topics & Projects

Xuan ("Sean") Guo is a 5th-year PhD candidate in the Human Computer Interaction/Machine Learning areas at RIT's Golisano College of Computing and Information Sciences. He is a member of the interdisciplinary H-C Multi-Modal Modeling Lab and the Multidisciplinary Vision Research Laboratory. He is also a student member in the ACM and IEEE communities.

Xuan passed his research potential assessment in 2012 and defended his dissertation proposal in 2015. Now he is working towards his doctoral degree in Computing and Information Sciences from Rochester Institute of Technology (with a focus on Human Computer Interactions and Machine Learning), in addition to a bachelor's degree in Software Engineering at Nankai University. During bachelor's, he studied Human Computer Interactions in the aspect of online security and user trust.

Xuan's research focuses on interactive machine learning, visual (image) analytics, and knowledge discovery, particularly in clinical domains. He has special interests in areas including mining multimodal data for shared semantics, recognizing patterns related to hierarchical knowledge structures, and formalizing user interactions as constraints to optimize user-machine collaborations. Xuan works with professors and researchers in various disciplinaries.