Meet the June Member of the Month, Dr. Xia (Ben) Hu, Director of the Data to Knowledge Lab (D2K) and Associate Professor of Computer Science. Dr. Hu's research areas include; data science, interpretable machine learning, automated machine learning, and network analytics.
Dr. Hu received BA and MS degrees from Beihang University and his PhD from Arizona State University. Dr. Hu has published over 100 papers in several major academic venues, including NeurIPS, ICLR, KDD, WWW, IJCAI, AAAI, etc. An open-source package developed by his group, namely AutoKeras, has become the most used automated deep learning system on Github (with over 8,000 stars and 1,000 forks). Also, his work on deep collaborative filtering, anomaly detection and knowledge graphs have been included in the TensorFlow package, Apple production system and Bing production system, respectively. His papers have received severaL Best Paper (Candidate) awards from venues such as WWW, WSDM and ICDM. He is the recipient of NSF CAREER Award. His work has been cited more than 10,000 times with an h-index of 41. He was the conference General Co-Chair for WSDM 2020.
How do you explain your research in one sentence?
We develop automated and interpretable data mining and machine learning algorithms with theoretical properties to better discover actionable patterns from large-scale, networked, dynamic and sparse data.
What is your favorite aspect of your research?
Our research not only has theoretical impact, but also has a real-world impact that helps researchers and practitioners in their machine learning algorithms and systems.