I am a dynamic, results-oriented team leader and a passionate scientist, developing novel deep learning/machine learning models and transforming these techniques into the business products for solving real-world challenging problems. I earned his Ph.D. degree in computer science from the College of William and Mary in 2016. Currently, I am an Engineering Manager in the Content and Knowledge Graph Group at Pinterest, where we are building the next generation Knowledge Graph to empower Pinterest recommendation/research systems across all major surfaces including Homefeed, Search, Ads, and etc. Previously, I was a Principal Scientist at JD.COM Silicon Valley Research Center, leading a team of 30+ machine learning / natural language processing / recommendation system scientists, software engineers and product managers to build next generation intelligent ecommerce systems for personalized and interactive online shopping experience in JD.COM. Before that, I was a research staff member at IBM Research and led a research team (10+ RSMs) for developing novel Graph Neural Networks for various AI tasks, which leads to the #1 AI Challenge Project in IBM Research and multiple IBM Awards including Outstanding Technical Achievement Award.

My research interests lie at the intersection of Machine Learning(Deep Learning), Representation Learning, and Natural Language Processing, with a particular emphasis on the fast-growing subjects of Graph Neural Networks and its extensions on new application domains. I have published one book (in GNNs) and more than 100 top-ranked AI/ML/NLP conference and journal papers, including but not limited to NIPS, ICML, ICLR, KDD, ACL, EMNLP, NAACL, IJCAI, and AAAI. I am also a co-inventor of more than 40 filed US patents. Because of the commercial value of my patents, I received several invention achievement awards and was appointed as IBM Master Inventors, class of 2020. I was the recipients of the Best Paper Award and Best Student Paper Award of several conferences such as IEEE ICC’19, AAAI workshop on DLGMA’20 and KDD workshop on DLG'19. My research has been featured in numerous media outlets, including NatureNews, YahooNews, AP News, PR Newswire, The Time Weekly, Venturebeat, TechTalks, SyncedReview, Leiphone, QbitAI, MIT News, IBM Research News, and SIAM News.

I have served as Associate Editor for IEEE Transactions on Neural Networks and Learning Systems and ACM Transactions on Knowledge Discovery from Data. I have also served as Industry and Government Program Co-Chairs of IEEE BigData'22, Sponsorship Co-Chairs of KDD'22, Virtual Conference Chairs of KDD'21, Associate Conference Chairs of AAAI'21, Poster co-chairs of IEEE BigData'19, Tutorial co-chairs of IEEE BigData'18, and is the founding co-chairs for multiple Workshops, including Deep Learning on Graphs (with KDD'19-22 and AAAI'20-23). Furthermore, I have regularly served as an AC/SPC of the following major AI/ML/DL/DM/NLP conferences including KDD, WSDM, IJCAI, AAAI and EMNLP.