I am a second year PhD student in Computing and Information Science at the Golisano College of Computing and Information Sciences, Rochester Institute of Technology (RIT) . I am a Graduate Research Assistant under the supervision of Prof. Anne Haake and Prof. Rui Li. My research interest is to develop computational methods to provide insights into underlying biological phenomena that are critical to understanding phenotypes in health and diseases. Specifically, I am currently working in learning low-dimensional vector representation for each gene or protein, that canonically represents topological patterns in interaction networks and various information associated with that gene, which can be plugged into off-the-shelf machine learning methods for diverse functional tasks: gene function prediction, gene ontology reconstruction, and genetic interaction prediction.
I am interested in integration of heterogeneous information such as interaction networks, expression profiles, transcription factor binding sites, gene sequences, functional annotations from gene ontology, metabolic pathways, etc. to derive functional insights about genes or proteins.
Research interests: Heterogeneous Data Integration, Network Representation Learning, Deep Learning, Computational Biology
|February 2018||Presented poster "Network-based Learning to Infer Genetic Interaction Networks" in New Deep Learning Techniques Workshop at IPAM, UCLA.|
|February 2018||Attended New Deep Learning Techniques Workshop at IPAM, UCLA.|
|May 2017||Defended the PhD Research Potential Assessment.|
|August 2016||Joined Rochester Institute of Technology as PhD Student in Computing and Information Sciences.|