Hi! I am a Machine Learning Engineer at Apple AI/ML working on question answering. I graduated from the research-oriented master program MLT of Language Technology Institute in School of Computer Science at Carnegie Mellon University. I was fortunate to be co-advised by Prof. Claire Le Goues and Prof. Bogdan Vasilescu, and collaborate with Prof. Graham Neubig. Prior to that, I received Bachelor’s degree in Computer Science at Tsinghua University. My undergraduate thesis, advised by Prof. Jie Tang, was honored outstanding thesis.

My research interests generally include representation learning, natural language processing, and their applications to software engineering. My current and past works span contrastive learning, graph representation learning, knowledge graphs, text generation, and question answering. I am also interested in learning parallel computing and distributed systems.

New: I joined 🍎 Apple AI/ML as a Machine Learning Engineer in June 2022!


VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning
Qibin Chen, Jeremy Lacomis, Edward J. Schwartz, Graham Neubig, Bogdan Vasilescu, Claire Le Goues
ICSE 2022 / arXiv / GitHub

Augmenting Decompiler Output with Learned Variable Names and Types
Qibin Chen, Jeremy Lacomis, Edward J. Schwartz, Claire Le Goues, Graham Neubig, Bogdan Vasilescu
USENIX Security 2022 (Distinguished Paper Award) / arXiv / GitHub

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training
Jiezhong Qiu, Qibin Chen, Yuxiao Dong, Jing Zhang, Hongxia Yang, Ming Ding, Kuansan Wang, Jie Tang
KDD 2020 (Most cited in KDD’20) / arXiv / GitHub

CogDL: An Extensive Toolkit for Deep Learning on Graphs
Yukuo Cen, Zhenyu Hou, Yan Wang, Qibin Chen, Yizhen Luo, Xingcheng Yao, Aohan Zeng, Shiguang Guo, Peng Zhang, Guohao Dai, Yu Wang, Chang Zhou, Hongxia Yang, Jie Tang
Preprint 2021 / arXiv / GitHub / Website

Towards Knowledge-Based Recommender Dialog System
Qibin Chen, Junyang Lin, Yichang Zhang, Ming Ding, Yukuo Cen, Hongxia Yang, Jie Tang
EMNLP 2019 / arXiv / GitHub

Cognitive Graph for Multi-Hop Reading Comprehension at Scale
Ming Ding, Chang Zhou, Qibin Chen, Hongxia Yang, Jie Tang
ACL 2019 (Oral) / arXiv / GitHub

Towards Knowledge-Based Personalized Product Description Generation in E-commerce
Qibin Chen*, Junyang Lin*, Yichang Zhang, Hongxia Yang, Jingren Zhou, Jie Tang
KDD 2019 (Applied Data Science Track) / arXiv / GitHub


Distinguished Paper Award, USENIX Security, 2022
Research Fellowship, Carnegie Mellon University, 2021/2020
Outstanding Undergraduate Thesis, Tsinghua University, 2019
Outstanding Graduate, Tsinghua University, 2019
Qualcomm Scholarship, 2018
Research/Academic Excellence Award, 2018/2017/2016


PC Member: KDD’23, ICMR’23, IJCAI’23, PAKDD’23, ICLR’22 DL4C Workshop
Review Assistant: EACL’23, EMNLP’21, KDD’19