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.

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

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.

  • An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis [pdf][code]

Ruidan He, Wee Sun Lee, Hwee Tou Ng, and Daniel Dahlmeier.

ACL-19. Florence, Italy, July 28-August 2, 2019

  • 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

  • Effective Attention Modeling for Aspect-level Sentiment Classification [pdf] [slides]

Ruidan He, Wee Sun Lee, Hwee Tou Ng, and Daniel Dahlmeier.

COLING-18. Santa Fe, New Mexico, USA, August 20-26, 2018

Ruidan He, Wee Sun Lee, Hwee Tou Ng, and Daniel Dahlmeier.

ACL-18. Melbourne, Australia, July 15-20, 2018

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