Ruidan HE
Hi! I am a data scientist at Grab, working on recommendation and ranking algorithms for Grab food and Grab Mart. Previously I worked as an NLP scientist for two years at Alibaba DAMO Academy. I received my PhD in computer science from National University of Singapore, advised by Prof. Lee Wee Sun and Prof. Ng Hwee Tou. My research focus is primarily on deep learning, semi-supervised learning, transfer learning, and their applications in natural language processing.
[Email] [CV] [GitHub] [Google Scholar]
Publications
(*: equal contribution)
Knowledge Based Multilingual Language Model [pdf]
Linlin Liu, Xin Li, Ruidan He, Lidong Bing, Shafiq Joty, and Luo Si
Preprint
Document-level Relation Extraction with Adaptive Focal Loss and Knowledge Distillation [pdf]
Qingyu Tan, Ruidan He, Lidong Bing, and Hwee Tou Ng
ACL-22 Findings
MELM: Data Augmentation with Masked Entity Language Modeling for Low-Resource NER [pdf]
Ran Zhou, Xin Li, Ruidan He, Lidong Bing, Erik Cambria, Luo Si, and Chunyan Miao
ACL-22
IAM: A Comprehensive and Large-Scale Dataset for Integrated Argument Mining Tasks [pdf]
Liying Cheng, Lidong Bing, Ruidan He, Qian Yu, Yan Zhang, and Luo Si
ACL-22
Cross-lingual Aspect-based Sentiment Analysis with Aspect Term Code-Switching [pdf]
Wenxuan Zhang, Ruidan He, Haiyun Peng, Lidong Bing and Wai Lam
EMNLP-21
On the Effectiveness of Adapter-based Tuning for Pretrained Language Model Adaptation [pdf]
Ruidan He*, Linlin Liu*, Hai Ye*, Qingyu Tan, Bosheng Ding, Liying Cheng, Jia-Wei Low, Lidong Bing, and Luo Si
ACL-21
Bootstrapped Unsupervised Sentence Representation Learning
Yan Zhang*, Ruidan He*, Zuozhu Liu, Lidong Bing, and Haizhou Li
ACL-21
An Unsupervised Sentence Embedding Method by Mutual Information Maximization [pdf]
Yan Zhang*, Ruidan He*, Zuozhu Liu, Kwan Hui Lim, Lidong Bing
EMNLP-20. November 16-20, 2020
Feature Adaptation of Pre-Trained Language Models across Languages and Domains for Text Classification [pdf]
Hai Ye, Qingyu Tan, Ruidan He, Juntao Li, Hwee Tou Ng, Lidong Bing
EMNLP-20. November 16-20, 2020
Juntao Li, Ruidan He, Hai Ye, Hwee Tou Ng, Lidong Bing, Rui Yan
IJCAI-20.
Adaptive Semi-supervised Learning for Cross-domain Sentiment Classification [pdf][poster][data & code]
Ruidan He, Wee Sun Lee, Hwee Tou Ng, and Daniel Dahlmeier.
EMNLP-18. Brussels, Belgium, October 31-November 4, 2018
Exploiting Document Knowledge for Aspect-level Sentiment Classification [pdf][poster][data & code]
Ruidan He, Wee Sun Lee, Hwee Tou Ng, and Daniel Dahlmeier.
ACL-18. Melbourne, Australia, July 15-20, 2018
An Unsupervised Neural Attention Model for Aspect Extraction [pdf][slides][data & code]
Ruidan He, Wee Sun Lee, Hwee Tou Ng, and Daniel Dahlmeier.
ACL-17. Vancouver, Canada, July 30-August 4, 2017
Education
2015-2019: Ph.D. from National University of Singapore
2012-2015: B.E. from Singapore University of Technology and Design (SUTD), First Class Honour
Honours and awards
Dean's Graduate Research Excellence Award from NUS School of Computing, 2019
Research Achievement Award from NUS School of Computing, 2017, 2018
Research Scholarship, SAP Innovation Center Network, 2015-2019
GLC-SM2 PRC Student Scholarship by Ministry of Education Singapore, 2012-2015