Welcome! I am currently an associate professor in School of Computer Science and Technology at Dalian University of Technology. Prior to it, I worked as a Postdoctoral Fellow in Zhiyong Lu’s BioNLP Group at National Institutes of Health (NIH). I received my PhD’s degree in the College of Computer Science and Technology at Dalian University of Technology, where I was a member of Information Retrieval lab (DUTIR). I received my master’s degree and bachelor’s degree in the School of Information Science and Engineering at Xiamen University, where I was a member of Natural Language Processing Laboratory of Xiamen University. I like traveling and photography (See my CV for more information).

My Homepage in Chinese

Research Interests

• Natural Language Processing
• Biomedical Text Mining
• Machine Learning

Selected Publications

(* denotes equal contribution, + denotes corresponding author)

• Ling Luo+, Jinzhong Ning, Yingwen Zhao, et al. Taiyi: a bilingual fine-tuned large language model for diverse biomedical tasks. Journal of the American Medical Informatics Association, February 2024, btad310.
• Ling Luo*, Chih-Hsuan Wei*, Po-Ting Lai, Robert Leaman, Qingyu Chen, Zhiyong Lu. AIONER: all-in-one scheme-based biomedical named entity recognition using deep learning. Bioinformatics, Volume 39, Issue 5, May 2023, ocae037.
• Ling Luo*, Po-Ting Lai*, Chih-Hsuan Wei*, Cecilia N Arighi, Zhiyong Lu. BioRED: a rich biomedical relation extraction dataset. Briefings in Bioinformatics, Volume 23, Issue 5, September 2022, bbac282.
• Ling Luo, Shankai Yan, Po-Ting Lai, Daniel Veltri, Andrew Oler, Sandhya Xirasagar, Rajarshi Ghosh, Morgan Similuk, Peter N. Robinson, Zhiyong Lu. PhenoTagger: A Hybrid Method for Phenotype Concept Recognition using Human Phenotype Ontology. Bioinformatics, Volume 37, Issue 13, 1 July 2021, Pages 1884–1890.
• Ling Luo, Zhihao Yang, Pei Yang, Yin Zhang, Lei Wang, Hongfei Lin and Jian Wang. An attention-based BiLSTM-CRF approach to document-level chemical named entity recognition. Bioinformatics, Volume 34, Issue 8, 15 April 2018, Pages 1381–1388.
• Ling Luo, Zhihao Yang, Mingyu Cao, Lei Wang, Yin Zhang and Hongfei Lin. A neural network-based joint learning approach for biomedical entity and relation extraction from biomedical literature. Journal of Biomedical Informatics, 2020, Volume 103: 103384.
• Ling Luo, Zhihao Yang, Lei Wang, Yin Zhang, Hongfei Lin, Jian Wang, Liang Yang, Kan Xu and Yijia Zhang. Protein-Protein Interaction Article Classification: A Knowledge-enriched Self-Attention Convolutional Neural Network Approach. Procceding of 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2018. (Regular Paper)
• Ling Luo, Zhihao Yang, Yawen Song, Nan Li and Hongfei Lin. Chinese Clinical Named Entity Recognition Based on Stroke ELMo and Multi-Task Learning . Chinese Journal of Computers, 2020, 43(10):1943-1957. (In Chinese)

PhD Thesis

• Ling Luo. Research on the Key Techniques of Biomedical Text Mining . Dalian University of Technology, Dalian, China, 2019. (In Chinese)

Challenges

• BioCreative VIII Challenge: Phenotype normalization (genetic conditions in pediatric patients) Track, The Second Place in 5 Teams [paper]
• BioCreative VII Challenge: Text mining drug and chemical-protein interactions (DrugProt) Track, The Second Place in 30 Teams [paper]
• The 2019 China Conference on Knowledge Graph and Semantic Computing (CCKS 2019) Challenge: Chinese Clinical Named Entity Recognition Task, The Third Place in 44 Teams [paper]
• The 2018 China Conference on Knowledge Graph and Semantic Computing (CCKS 2018) Challenge: Chinese Clinical Named Entity Recognition Task, The Third Place in 69 Teams [paper]
• BioCrative VI Precision Medicine Track: Document Triage Task, The Second Place in 10 Teams [paper]
• BioCreative V.5 Challenge: The CEMP (Chemical Entity Mention in Patents) Task, The First Place in 14 Teams [paper]
• BioCreative V.5 Challenge: The GPRO (Gene and Protein Related Object) Task, The First Place in 7 Teams [paper]

Selected Blog Posts

• BioNER-Progress
• Pre-trianing of language models for natural language processing (in Chinese)
• Self-attention mechanisms in natural language processing (in Chinese)
• Joint extraction of entities and relations based on neural networks (in Chinese)
• Neural network structures in named entity recognition (in Chinese)
• Attention mechanisms in natural language processing (in Chinese)