Short Biography
Haiqin Yang is a principal researcher at International Digital Economy Academy (IDEA) to head the DataStory AI lab. He is also an adjunct professor at the South China University of Technology.
Before that, he was a senior researcher at Ping An Life, where he established the Statistical Artificial Intelligence and Learning (SAIL) lab to provide natural language processing/generation services. He has previously worked as an adjunct associate professor in the Department of Decision Sciences and Managerial Economics at The Chinese University of Hong Kong (CUHK), and an assistant professor in Department of Computing, and the deputy director of Deep Learning Research and Application Centre, at Hang Seng Management College. He received the Ph.D. from Dept. of Computer Science and Engineering at CUHK, under the supervision of Prof. Irwin King and Prof. Michael R. Lyu.
His current work focuses on providing niche services based on natural language processing and multimodal data analysis, where his team has developed open-domain commercial event evolutionary graphs] to provide services for various commercial domains. He realizes various research problems in this project, which needs deeply investigate on deep learning, natural language processing, multimodal processing, and reinforcement learning. If you are interested in our work, please drop him an email.
He received the 2018 Asia Pacific Neural Network Society (APNNS) Young Researcher Award and is recognized as the Most Influential Scholar Award Honorable Mention for outstanding and vibrant contributions to the field of AAAI/IJCAI between 2009 and 2019. His publications are in Google Scholar or DBLP.
Recent News
(June, 2024) Paper Natural Language Interfaces for Tabular Data Querying and Visualization: A Survey was accepted by IEEE TKDE. Papers was accepted by ACL, ICASSP, UAI. Congratulations to the collaborators!
(June, 2024) A fair comparison for Event Coreference Resolution, EasyECR: A Library for Easy Implementation and Evaluation of Event Coreference Resolution Models (Code), was provided.
(May, 2024) Being a programm committee chair at WI-IAT 2024.
(May, 2023) Two papers were accepted by ACL and 2 were accepted by ICML. Congratulations to the team and collaborators!
(April, 2022) Paper Vision-and-Language Pretrained Models: A Survey was accepted by IJCAI’22 Survey Track (AR: 18%). Congratulations to Siqu and Feiqi, two excellent interns from the University of Sidney.
(July, 2021) Join IDEA and recruit self-motivated team members (both interns and full-time members) to work on research at NLP, knowledge graph, machine learning, etc.; see details here.
(July, 2021) Paper Progressive Open-Domain Response Generation with Multiple Controllable Attributes was accepted by IJCAI’21.
(July, 2021) Two papers, RefBERT: Compressing BERT by Referencing to Pre-computed Representations and Emotion Dynamics Modeling via BERT, were accepted by IJCNN’21.
(July, 2021) Three papers, PALI at SemEval-2021 Task 2: Fine-Tune XLM-RoBERTa for Word in Context Disambiguation, MagicPai at SemEval-2021 Task 7: Method for Detecting and Rating Humor Based on Multi-Task Adversarial Training, Sattiy at SemEval-2021 Task 9: An Ensemble Solution for Statement Verification and Evidence Finding with Tables, disclosed our solution for the corresponding tasks at SemEval’21.
(March, 2021) Paper Automatic Intent-Slot Induction for Dialogue Systems paper was accepted by WWW’21; Paper KGSynNet: A Novel Entity Synonyms Discovery Framework with Knowledge Graph was accepted by DASFAA’21.
(June, 2020) Call for papers, “ICONIP 2020”.
(October, 2019) A technical report, “BERT Meets Chinese Word Segmentation”, was posted on Arxiv.
(October, 2019) Paper “Effective Data-Aware Covariance Estimator From Compressed Data” was accepted by IEEE Trans. Neural Network and Learning Systtem. 2019 (IF: 11.683).
(October, 2019) Paper “Making Online Sketching Hashing Even Faster” was accepted by IEEE Trans. Knowledge and Data Engineering. 2019 (IF: 3.857).
(April, 2019) Paper “HiGRU: Hierarchical Gated Recurrent Units for Utterance-level Emotion Recognition” was accepted by NAACL-HLT 2019.
(December, 2018) Received the 2018 Asia Pacific Neural Network Society (APNNS) Young Researcher Award, see certificate.
Solution “EmotionX-DLC: Self-AttentiveBiLSTM for Detecting Sequential Emotions in Dialogues” achieves the second place of SocialNLP@ACL 2018.
Paper “TreeNet: Learning Sentence Representations with Unconstrained Tree Structure” was published in IJCAI’18.
Quote
— The fear of the LORD is the beginning of wisdom, and knowledge of the Holy One is understanding. (Proverbs 9:10)
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