Name: Gao Yang
Discipline: Computer Science and Technology
Title: Associate Professor
Contact number:
E-mail: gyang@bit.edu.cn
Address: Personal Information
2019.7-present, Associate Professor, School of Computer Science, Beijing Institute of Technology
2019.10-2020.8, Visiting Scholar, Natural Language Processing (EdinburghNLP), School of Informatics, University of Edinburgh
2015.11-2019.7, School of Computer Science, Beijing Institute of Technology, Lecturer
2015.2-2015.9, Postdoctoral Fellow, Queensland University of Technology, Australia
2011-2015, PhD in Data Science, Queensland University of Technology, Australia

Gao Yang, Associate Professor; Professor Mirella Lapata, Visiting Scholar, University of Edinburgh (EdinburghNLP). It is mainly engaged in deep semantic understanding and explainable reasoning, large model training, automatic text generation technology, promoting information retrieval, text summarization, intelligent question answering and other system applications. He has published more than 50 high-level papers in international journal conferences, including ACL, AAAI, WWW, IJCAI, EMNLP, TKDE, TNNLS, Information Sciences, COLING, etc. He is the consulting chief editor of Web Intelligence Journal, the editorial board member of Natural Language Processing Journal, and the chairman of CCL2023 Text Generation track. International conference A Program Committee member of AAI, ACL, EMNLP, NAACL, COLING, ICDM, and journal Reviewer of TNNLS, Computing Surveys, as Outstanding Reviewer of ACL 2021. As a participant, he won the first prize of the Chinese Institute of Electronics Science and Technology Progress Award and the second prize of National Defense Science and Technology Progress Award. Deputy Secretary-General of Natural Language Generation and Intelligent Writing Committee of Chinese Information Society, member of CIPS Youth Working Committee, member of SMP Special Committee.

Research Direction
Text generation, interpretable reasoning, large model training

The computational model of semantic representation, extraction and generation based on text (including image, video, large-scale knowledge and other modes) is studied. Research and use of deep learning computing, data-driven text generation technologies to promote text summarization, cross-language application, image/video description generation, style transfer, intelligent question answering and other system applications. The overall goal of the research is to use the ability of machines to rapidly process large-scale data to achieve human-like information extraction, semantic understanding, logical reasoning, and language generation.

Personal Information
2019.7-present, Associate Professor, School of Computer Science, Beijing Institute of Technology
2019.10-2020.8, Visiting Scholar, Natural Language Processing (EdinburghNLP), School of Informatics, University of Edinburgh
2015.11-2019.7, School of Computer Science, Beijing Institute of Technology, Lecturer
2015.2-2015.9, Postdoctoral Fellow, Queensland University of Technology, Australia
2011-2015, PhD in Data Science, Queensland University of Technology, Australia

Gao Yang, Associate Professor; Professor Mirella Lapata, Visiting Scholar, University of Edinburgh (EdinburghNLP). It is mainly engaged in deep semantic understanding and explainable reasoning, large model training, automatic text generation technology, promoting information retrieval, text summarization, intelligent question answering and other system applications. He has published more than 50 high-level papers in international journal conferences, including ACL, AAAI, WWW, IJCAI, EMNLP, TKDE, TNNLS, Information Sciences, COLING, etc. He is the consulting chief editor of Web Intelligence Journal, the editorial board member of Natural Language Processing Journal, and the chairman of CCL2023 Text Generation track. International conference A Program Committee member of AAI, ACL, EMNLP, NAACL, COLING, ICDM, and journal Reviewer of TNNLS, Computing Surveys, as Outstanding Reviewer of ACL 2021. As a participant, he won the first prize of the Chinese Institute of Electronics Science and Technology Progress Award and the second prize of National Defense Science and Technology Progress Award. Deputy Secretary-General of Natural Language Generation and Intelligent Writing Committee of Chinese Information Society, member of CIPS Youth Working Committee, member of SMP Special Committee.

Personal Information
2019.7-present, Associate Professor, School of Computer Science, Beijing Institute of Technology
2019.10-2020.8, Visiting Scholar, Natural Language Processing (EdinburghNLP), School of Informatics, University of Edinburgh
2015.11-2019.7, School of Computer Science, Beijing Institute of Technology, Lecturer
2015.2-2015.9, Postdoctoral Fellow, Queensland University of Technology, Australia
2011-2015, PhD in Data Science, Queensland University of Technology, Australia

Gao Yang, Associate Professor; Professor Mirella Lapata, Visiting Scholar, University of Edinburgh (EdinburghNLP). It is mainly engaged in deep semantic understanding and explainable reasoning, large model training, automatic text generation technology, promoting information retrieval, text summarization, intelligent question answering and other system applications. He has published more than 50 high-level papers in international journal conferences, including ACL, AAAI, WWW, IJCAI, EMNLP, TKDE, TNNLS, Information Sciences, COLING, etc. He is the consulting chief editor of Web Intelligence Journal, the editorial board member of Natural Language Processing Journal, and the chairman of CCL2023 Text Generation track. International conference A Program Committee member of AAI, ACL, EMNLP, NAACL, COLING, ICDM, and journal Reviewer of TNNLS, Computing Surveys, as Outstanding Reviewer of ACL 2021. As a participant, he won the first prize of the Chinese Institute of Electronics Science and Technology Progress Award and the second prize of National Defense Science and Technology Progress Award. Deputy Secretary-General of Natural Language Generation and Intelligent Writing Committee of Chinese Information Society, member of CIPS Youth Working Committee, member of SMP Special Committee.

代表性学术成果
论文列表：https://dblp.org/pid/89/4402-16.html
文本生成：
1. Jiaao Zhan, Yang Gao*, Yu Bai, Qianhui Liu，Stage-wise Stylistic Headline Generation: Style Generation and Summarized Content Insertion. IJCAI 2022: 4489-4495. (CCF A)
2. Yu Bai, Heyan Huang, Kai Fan, Yang Gao, Yiming Zhu, Jiaao Zhan, Zewen Chi, Boxing Chen. Unifying Cross-lingual Summarization and Machine Translation with Compression Rate. SIGIR 2022: 1087-1097 (CCF A)
3. Xiaochen Liu, Yang Gao*, Yu Bai, Jiawei Li, Yinan Hu,Boxing Chen. PSP: Pre-trained Soft Prompts for Few-Shot Abstractive Summarization. COLING2022. (CCF B)
4. Haonan Wang, Yang Gao*, Yu Bai, Mirella Lapata, Heyan Huang, Exploring Explainable Selection to Control Abstractive Summarization, 35 th AAAI Conference on Artificial Intelligence (AAAI’2021), Feb. 2-Feb 9, 2021 (CCF A)
5. Yu Bai, Yang Gao, Heyan Huang, Cross-lingual Abstractive Summarization with Limited Parallel Resources, Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL 2021. (CCF A)
6. Wenbo Wang, Yang Gao*, Heyan Huang, Yuxiang Zhou, Concept Pointer Network for Abstractive Summarization, EMNLP 2019, Hong Kong, China, 2019. (CCF B)
7. Yang Gao, Yang Wang, Luyang Liu, Yidi Guo, Heyan Huang, Neural Abstractive Summarization Fusing by Global Generative Topics, Neural Computing and Applications, 32(9): 5049-5058 (2020). (SCI 二区)
可解释推理
8. Mucheng Ren , Heyan Huang , Yuxiang Zhou , Qianwen Cao , Yuan Bu, and Yang Gao, TCM-SD: A Benchmark for Probing Syndrome Differentiation via Natural Language Processing, In Proceedings of CCL 2022, Best Paper Award.
9. Luyang Liu, Heyan Huang, Yang Gao, Yongfeng Zhang: Improving neural topic modeling via Sinkhorn divergence. Inf. Process. Manag. 59(3): 102864 (2022) (SCI一区)
10. Mucheng Ren, Heyan Huang, Yang Gao: Interpretable modular knowledge reasoning for machine reading comprehension. Neural Computation. Applications 34(12): 9901-9918 (2022)
11. Mucheng Ren, Heyan Huang, Yang Gao，Prediction or Comparison: Toward Interpretable Qualitative Reasoning. ACL/IJCNLP (Findings) 2021: 664-675
12. Mucheng Ren, Heyan Huang, Yang Gao: SKR-QA: Semantic ranking and knowledge revise for multi-choice question answering. Neurocomputing 459: 142-151 (2021)
13. Yuxiang Zhou, Lejian Liao, Yang Gao, Zhanming Jie, Wei Lu: To be Closer: Learning to Link up Aspects with Opinions. EMNLP (1) 2021: 3899-3909
语义理解
14. Yuxiang Zhou, Lejian Liao, Yang Gao*, et al. TopicBERT: A Topic-Enhanced Neural Language Model Fine-Tuned for Sentiment Classification. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023,34(1): 380-393. (SCI 一区)
15. Yang Gao, Yue Xu, Heyan Huang, Qian Liu, Linjing Wei, Luyang Liu, Jointly Learning Topics in Sentence Embedding for Document Summarization, IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol: 32, Issue: 4, 2020: 688 - 699. （CCF A）
16. Luyang Liu, Heyan Huang, Yang Gao, Yongfeng Zhang, Xiaochi Wei, Neural Variational Correlated Topic Modeling, WWW 2019，San Francisco, CA, USA. (CCF A)
17. Yuxiang Zhou, Lejian Liao, Yang Gao*, Heyan Huang, Extracting salient features from convolutional discriminative filters, Information Sciences, volume 558, May 2021: 265-279. (SCI一区)
18. Qian Liu, Heyan Huang, Guangquan Zhang, Yang Gao, Junyu Xuan, Jie Lu. Semantic Structure-based Word Embedding by Incorporating Concept Convergence and Word Divergence, AAAI 2018. (CCF A)
19. Yang Gao, Yuefeng Li, Raymond Y.K., Lau, Yue Xu, Md Abul Bashar, Finding Semantically Valid and Relevant Topics by Association-based Topic Selection Model, ACM Transactions on Intelligent Systems and Technology (TIST), 2017 (SCI)
20. Qian Liu, Heyan Huang, Yang Gao, Xiaochi Wei, Yuxin Tian, Luyang Liu. Task-oriented Word Embedding for Text Classification, COLING 2018. (CCF B)
21. Yang Gao, Yue Xu, Yuefeng Li, Pattern-based topics for document modelling in information filtering, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2015, 24(6): 1629-1642. （CCF A , SCI）
22. Yuxiang Zhou, Lejian Liao, Yang Gao*, Heyan Huang, Xiaochi Wei, A Discriminative Convolutional Neural Network with Context-aware Attention, ACM Transactions on Intelligent Systems and Technology (TIST), 2020, Vol.11,No.5. (SCI)
所获奖励
1. 2018年 “基于海量知识的智能理解与推理关键技术及智能政务应用”获中国电子学会科技进步奖一等奖（11）
2. 2022年“异构大数据智能处理关键技术及应用”获国防科技进步二等奖（7）
3. 2021年， 北京理工大学优秀硕士学位论文(王浩男同学)，指导教师