Miao is currently a final-year PhD candidate in NLP/AI at School of Computing and Information Systems, The University of Melbourne (UoM), jointly advised by Prof. Eduard Hovy (UoM and CMU) and Dr. Jey Han Lau (UoM) within the NLP group. He has been a visiting PhD student working with Prof. Mirella Lapata at Institute for Language, Cognition and Computation (ILCC), The University of Edinburgh since March 2024. His PhD journey in Melbourne started in December 2020. Before that, he earned a B.E. from Northeastern University in 2017 and an M.Sc. (as an exam-exempted postgraduate) from Institute of Software, Chinese Academy of Sciences in July 2020.

Research Interests

Miao's research certers on natural language processing (NLP) and artificial intelligence (AI). During the PhD, he has primarily worked on multi-document summarization, emphasizing information integration and decompositional reasoning with large language models (LLMs) to enhance transparency and grounding in automatic summarisation of multiple documents. His overarching research goal is to advance AI systems to enable integrated synthesis from complex information sources, enhancing deep and scalable human understanding through human-AI collaboration. Specifically, his research interests include: (1) deepening our understanding of how humans cognitively correlate and integrate dispersed information for complex decision-making, e.g., making well-informed treatment decisions in healthcare, (2) developing computational models, with a current emphasis on LLMs, that can reason over voluminous, heterogeneous, and distributed information at superhuman speeds particularly in low-data machine learning settings, e.g., performing in-context question answering across hundreds of scientific articles, and (3) establishing controlled experimentation and high-quality evaluation for both model outputs and their inner workings and behaviours, ensuring these models are not only useful but also verifiable and explainable for real-world utility.

Selected Publications

• Aspect-Aware Decomposition for Opinion Summarization
  Miao Li, Jey Han Lau, Eduard Hovy, and Mirella Lapata.
  Preprint.
  [abstract] [paper]

• A Sentiment Consolidation Framework for Meta-Review Generation
  Miao Li, Jey Han Lau, and Eduard Hovy.
  ACL 2024.
  [abstract] [paper] [code] [dataset] [slides] [poster]

• NewsBench: A Systematic Evaluation Framework for Assessing Editorial Capabilities of Large Language Models in Chinese Journalism
  Miao Li, Ming-Bin Chen, Bo Tang, Shengbin Hou, Pengyu Wang, Haiying Deng, Zhiyu Li, Feiyu Xiong, Keming Mao, Peng Cheng, and Yi Luo.
  ACL 2024.
  [abstract] [paper] [code] [dataset] [slides] [poster]

• Summarizing Multiple Documents with Conversational Structure for Meta-Review Generation
  Miao Li, Eduard Hovy, and Jey Han Lau.
  Findings of EMNLP 2023.
  [abstract] [paper] [code] [dataset] [poster]

• DeltaScore: Fine-grained Story Evaluation with Perturbations
  Zhuohan Xie, Miao Li, Trevor Cohn, and Jey Han Lau.
  Findings of EMNLP 2023.
  [abstract] [paper] [code]

• Compressed Heterogeneous Graph for Abstractive Multi-Document Summarization
  Miao Li, Jianzhong Qi, and Jey Han Lau.
  AAAI 2023. Oral.
  [abstract] [paper] [code] [slides] [poster]

• Personalized Abstractive Opinion Tagging
  Mengxue Zhao, Yang Yang, Miao Li, Jingang Wang, Wei Wu, Pengjie Ren, Maarten de Rijke and Zhaochun Ren.
  SIGIR 2022. Oral.
  [abstract] [paper]

• A Benchmark and Comprehensive Survey on Knowledge Graph Entity Alignment via Representation Learning
  Rui Zhang, Bayu Distiawan Trisedy, Miao Li, Yong Jiang, Jianzhong Qi.
  VLDB Journal 2022.
  [abstract] [paper] [code]

• A Topic Augmented Text Generation Model: Joint Learning of Semantics and Structural Features
  Hongyin Tang, Miao Li, Beihong Jin.
  EMNLP 2019. Oral.
  [abstract] [paper] [appendix]

• A New Effective Neural Variational Model with Mixture-of-Gaussians Prior for Text Clustering.
  Miao Li, Hongyin Tang, Beihong Jin, Chengqing Zong.
  ICTAI 2019. Oral.
  [abstract] [paper]

• Clustering Large-Scale Origin-Destination Pairs: A Case Study for Public Transit in Beijing
  Miao Li, Hongyin Tang, Beihong Jin.
  UIC 2018. Oral.
  [abstract] [paper]

Honors and Awards

• AAAI-23 Student Scholarship, Association for the Advancement of Artificial Intelligence, January 2023

• Google Conference Scholarship, Google Inc., January 2023

• Excellent Student Cadre, University of Chinese Academy of Sciences, June 2019

• National Scholarship for Graduates, Education Ministry of China, November 2018

• The First Prize Scholarship, University of Chinese Academy of Sciences, October 2018

• Excellent Student Cadre, University of Chinese Academy of Sciences, June 2018

• Outstanding Graduate, Northeastern University, June 2017

• Outstanding Graduate Thesis Award, Northeastern University, July 2017

• The First Prize Scholarship, Northeastern University, September 2016

• National Scholarship for Undergraduates, Education Ministry of China, October 2016

• The First Prize Scholarship, Northeastern University, September 2015

• National Scholarship for Undergraduates, Education Ministry of China, October 2015

• Excellent Student Cadre, Northeastern University, October 2015

Professional Services

• Reviewer for ACL Rolling Review (2021 - Present)

• Member of reviewer committees: NLPCC 2022-2023, EACL 2023, ACL 2023-2024, EMNLP 2023-2024, NAACL 2025

• Subreviewer for WSDM 2022, SIGIR 2022, SIGKDD 2022, and CIKM 2022