Chao Gao

Immunology Computational Biology

• Graph neural networks for spatially resolved multimodal data • Deep generative model for single-cell multimodal epigenomics data • Scalable online learning algorithm for integrative negative matrix factorization (iNMF). Online iNMF enables efficient integration of large scale single-cell multi-omics data.

• BIOINF593/EECS598 Machine Learning in Computational Biology

Molecular Profiling and Data Science • Analyzed multi-donor scRNA-seq data to study age-related macular degeneration

• Constructed diagnostic model using machine learning methods (e.g. random forests, xgboost) with 80% accuracy for predicting faller/non-faller patients with Parkinson’s Disease • Collaborated with physicians and applied both supervised and unsupervised learning methods on clinical data for a variety of projects • Organized group meetings and led the team through challenging multi-disciplinary projects

• Performed in vitro study to investigate the cause of abuse liability of Suboxone (abuse-deterrent) and found better dose ratio of drug ingredients that could optimize treatment effect • Facilitated the discovery of novel pain therapeutic of improved analgesic effect and reduced tolerance/dependence by conducting radioligand binding assay