Lingpeng Kong

Lingpeng Kong is a prominent researcher in the field of artificial intelligence, particularly known for his contributions to natural language processing (NLP) and machine learning. He currently serves as an Assistant Professor in the Department of Computer Science at the University of Hong Kong (HKU), where he also co-directs the HKU NLP Lab.

Educational Background

• Ph.D. in Computer Science from Carnegie Mellon University (CMU), completed in 2017, where he was co-advised by Noah Smith and Chris Dyer.
• M.S. in Computer Science from CMU in 2015.
• B.E. in Computer Science from Beijing Language and Culture University in 2011.

Professional Experience

Before his tenure at HKU, Dr. Kong was a Research Scientist at Google DeepMind from 2017 to 2020. His work at DeepMind focused on developing algorithms that leverage deep learning for various applications, including syntactic parsing and machine translation.

Research Interests

Dr. Kong's research primarily revolves around:

• Natural Language Processing (NLP): Developing representation learning algorithms that utilize linguistic structures.
• Machine Learning (ML): Exploring deep learning techniques and structured prediction.
• Applications include syntactic parsing, speech recognition, social media analysis, and machine translation.

Selected Publications

Dr. Kong has authored several influential papers, including:

• "Syntactic Structure Distillation Pretraining For Bidirectional Encoders" (TACL 2020).
• "A Mutual Information Maximization Perspective of Language Representation Learning" (ICLR 2020).
• "Episodic Memory in Lifelong Language Learning" (NeurIPS 2019).

Recognition

He has received accolades for his work, including the Outstanding Paper Award at the EACL 2017 conference.

In summary, Lingpeng Kong is a leading figure in NLP and ML research, with a strong academic background and significant contributions to the field through both his teaching and his work at DeepMind.