Liang Ma is a Staff AI Applied Scientist at Red Violet, focusing on AI model and agent development for identity verification and fraud detection. Dr. Ma received his Ph.D. degree from the Department of Electrical and Electronic Engineering at Imperial College London in July, 2014. He received both his M.Sc. and B.Sc. degrees with distinction from the Beijing University of Posts and Telecommunications (BUPT), China.

Before joining Red Violet (2026-present), he once worked at NTT DoCoMo Beijing Labs (2007), Ericsson (China) Communications (2008), and Microsoft Research Asia (MSRA) (2009), where he participated in projects involving WLAN Medium Access Control, High-Speed Switching Systems, and Software Radio-Based Gigabit Multi-antenna Communications, respectively. After his Ph.D. graduation, he worked as a Research Staff Member at IBM T.J. Watson Research Center (2014-2020), where he led two projects with team members from Yale, UCSB, Northwestern, Penn State, Imperial College London, and UMASS-Amherst. The project objectives were to develop efficient resource management strategies via reinforcement learning, low-dimensional node sequence embedding, and efficient question answering in dynamic and multi-genre networks. In 2020, he joined Dataminr (2020-2025) as a Senior Research Scientist, focusing on NLP, LLMs, reinforcement learning (RL), and product-level AI model development. In 2025, he joined Thomson Reuters Labs (2025-2026) as a Senior AI Applied Scientist II, working on CoCounsel legal AI Agent development and evaluations. 

Dr. Ma has served as a peer reviewer for a range of conferences and journals, including NeurIPS, ACL, ICLR, ACM TKDD, IEEE/ACM TON, INFOCOM, SECON, etc. He was the recipient of the IEEE International Conference on Communications (ICC 2019) Best Paper Award for reinforcement learning approaches to resource management, the IEEE International Conference on Distributed Computing Systems (ICDCS 2013) Best Paper Award, the IBM Outstanding Technical Achievement Award, the Chatschik Bisdikian Memorial Best Student Paper Award, the ACM SIGCOMM Internet Measurement Conference (IMC 2013) Best Paper Award Finalist, and the winner of Outstanding Graduate Student in 2008 and Excellent Student Awards four times during 2003-2006.