Golisano College of Computing and
Information Sciences (GCCIS)
Rochester Institute of Technology (RIT)
I am a third year Ph.D. 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 focuses on developing computational methods to provide insights into underlying biological phenomena that are critical to understanding phenotypes in health and diseases. My research interests lie at the intersection of machine learning and network science, with a current emphasis on graph representation learning, graph neural networks and their application to computational biology.
Specifically, I am interested in developing deep learning model based on Graph Neural networks to integrate heterogeneous information such as topological landscape of interaction networks (multiple functional association networks, gene interaction networks, PPI networks), and additional information about genes (expression profiles, transcription factor binding sites, gene sequences, functional annotations from gene ontology, metabolic pathways, etc.) to derive functional insights about genes or proteins.
Graph Representation Learning, Graph Neural Networks, Heterogeneous Data Integration, Computational Biology
|Nov 2018||Attended Biological Data Science and presented poster at Cold Spring Harbor Laboratory (CSHL).|
|Oct 2018||My application for PyTorch Scholarship Challenge from Facebook on Udacity was accepted.|
|Sep 2018||Our paper "GNE: A deep learning framework for gene network inference by aggregating biological information" was accepted at APBC 2019.|
|Sep 2018||Our paper "Sparse Covariance Modeling in High Dimensions with Gaussian Processes" was accepted at NeurIPS 2018.|
|Jul 2018||Poster entitled "Learning topology-preserving embeddings for gene interaction networks" was accepted for presentation at ECCB 2018 Poster Track.|
|Feb 2018||Presented poster "Network-based Learning to Infer Genetic Interaction Networks" in New Deep Learning Techniques Workshop at IPAM, UCLA.|
|Feb 2018||Attended New Deep Learning Techniques Workshop at IPAM, UCLA.|
|May 2017||Defended the PhD Research Potential Assessment.|
|Apr 2017||Presented poster "Reconstruction of Gene Regulatory Networks with Ensemble SVM" at GCCIS Research Showcase, RIT.|
|Aug 2016||Joined Rochester Institute of Technology as PhD Student in Computing and Information Sciences.|