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Machine Learning
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Interpretable and Fair Learning
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Deep Learning
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overview
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Dr. Liu completed doctoral training in pattern recognition and artificial intelligence, with strong expertise on natural language processing, machine learning (deep learning), and biomedical informatics. His research focuses on exploiting advanced computational models to analyze heterogeneous and complex healthcare data for knowledge extraction, predictive modeling and preventative data analytics, in the areas of suicide prevention, HIV prevention, cancer informatics and stroke management. Over more than 10 years in this field, Dr. Liu has published more than 60 peer reviewed manuscripts (29 first-author) on premium journals and top computer science conferences. He have served co-investigator (lead data scientist) on 5 NIH-funded R01 projects, and participated NSF study sections in the area of machine learning and natural language processing. Through developing advanced machine learning methods, Dr. Liu has won the first place in two international challenge tasks: Medical Visual Question Answering (2018) and Gene Mutation/Disease Relation Extraction (2019). Recently Dr. Liu's research focuses on applying AI techniques to advance health equity, assessing and mitigating potential biases related to data processing and algorithmic training. In 2022, he has been selected by the National Institute of Health and AIM-AHEAD Principal Investigators for the AIM-AHEAD Fellowship Program in Leadership Award.
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