Ping is currently a Staff Machine Learning Engineer at LinkedIn, where he works on large-scale job search and job matching. His recent work covers LLM-based query understanding in production search, graph neural networks for job matching (LinkSAGE), and the signal integration systems that make both practical at scale.
He earned his Ph.D. in Computer Science in 2022 from Illinois Institute of Technology under the guidance of Dr. Mustafa Bilgic. His doctoral research spanned natural language processing in social networks, news recommender systems, machine learning for microscopy and cell biology, and the analysis of model sensitivity to input perturbations. His Ph.D. thesis explored filter bubbles in news recommender systems, in collaboration with Drs. Mustafa Bilgic, Aron Culotta, and Matthew A. Shapiro.
Prior to his full-time role, Ping gained industry experience working at Conversant as a Data Scientist Intern (Summer 2018) and spent two subsequent summers at LinkedIn as a Machine Learning Engineer Intern.
Education
-
Ph.D. in Computer Science, 2022
Illinois Institute of Technology -
M.S. in Computer Science, 2016
Illinois Institute of Technology -
B.S. in Computer Science, 2008
Nankai University