I am a tenure-track assistant professor at Computer Science of Engineering Department, Michigan State University. Before joining MSU, I was a staff research scientist at Samsung Research where I was leading the architecture design and development of a large-scale recommendation engine, and designing low-power deep learning models for mobile devices.
I have been working on machine learning theories and methodologies, including multi-task learning, feature selection, sparse learning, matrix completion, numerical optimization and their applications on healthcare analytics. Most of my research has been published in top machine learning and data mining venues including NIPS, SIGKDD, ICDM, and SDM. I served as program committee members in premier conferences and reviewers of leading journals. I currently serve as an associate editor of Neurocomputing.
• Extensive experience with big data platforms, including Apache Spark, Spark MLLib, Spark Streaming, Hadoop, Hadoop streaming, YARN, Amazon EC2/EMR.
• Multiple years of hands-on experience on big data analytics, designing and implementing large-scale machine learning systems and industrial level recommendation engines.
• Profound understanding of machine learning, data mining, and recommender systems (regression, classification, clustering analysis, feature selection, numerical optimization)
• Veteran of designing machine learning models and analytical tools to discover insights from big data.
• Proficiency in Java, Scala, Python, Matlab, Git, Maven, SBT, HTML.