The IEEE ICDM 2026 Women Forum brings together researchers and students to celebrate women's contributions to data science and exchange ideas on research and career development. The programme features invited talks by Claudia Plant, My T. Thai and Wenjie Zhang, followed by short research presentations from the Female Scholar/Student Awards finalists. Researchers of all genders and career stages are welcome to join, share experiences and build connections.
Session host: Li Qian
| Time | Programme | Speakers |
|---|---|---|
| 10:10–10:15 | Welcome and Opening Remarks | Women Forum Co-Chairs |
| 10:15–10:25 | Promoting Diversity in Data Mining and Machine Learning Research (Invited Talk) | Claudia Plant |
| 10:25–10:35 | Do What You Love. Let the Rest Follow (Invited Talk) | My T. Thai |
| 10:35–10:45 | From Research Ideas to Impact: Building a Research Career and Collaborations (Invited Talk) | Wenjie Zhang |
| 10:45–11:25 | Young Female Scholar Award Finalists | |
| 10:45–10:53 | Toward Trustworthy Learning Under Imperfect Data: A Decade in Software Prediction | Liyan Song |
| 10:53–11:01 | Learning Better Structures and Low-Distortion Representations for Graphs | Qingyun Sun |
| 11:01–11:09 | Brain Graph Learning for Neurodegenerative Disease Diagnosis | Shuo Yu |
| 11:09–11:17 | Exploring multi-modal learning in unsupervised conditions | Yalan Qin |
| 11:17–11:25 | Key Technologies for Scientific and Technological Big Data Mining, Retrieval, and Intelligent Decision-Making | Yawen Li |
| 11:25–11:57 | Female Student Award Finalists | |
| 11:25–11:33 | Advancing Data Science for Urban Intelligence | Chenya Huang |
| 11:33–11:41 | What Can We Learn About the Future from Time-Series Data? | SheoYon Jhin |
| 11:41–11:49 | Causal Inference in Networked Data: Estimating Peer Effects under Interference | Xiaojing Du |
| 11:49–11:57 | Learning from Distribution Shift in Time-Series Forecasting. | Xiaoyang Li |
| 11:57–12:10 | Certificate Presentation and Closing Remarks | Women Forum Co-Chairs |
Professor
Northeast University, China
Research interests: Intelligent Data Analysis Technology and Its Applications in Finance and Healthcare
Professor
Queensland University of Technology, Australia
Research interests: Data mining; machine learning; text mining; web intelligence; social network analysis
Dr.
Chinese Academy of Sciences, China
Research interests: Data mining and machine learning, with a focus on adaptive unsupervised learning, as well as graph and temporal data mining
Professor
University of Vienna, Austria
Research interests: Data mining and machine learning, including clustering and representation learning, anomaly detection, information-theoretic methods, deep learning, and mining graphs, time series and heterogeneous data
Research Foundation Professor
University of Florida, USA
Research interests: Trustworthy AI; graph data mining; optimization; security and privacy
Professor
University of New South Wales, Australia
Research interests: Large-scale data management and analytics; graph data processing; complex data processing; data-centric AI
Harbin Institute of Technology, China
Beihang University, China
Dalian University of Technology, China
Shanghai University, China
Beijing University of Posts and Telecommunications, China
University of Technology Sydney, Australia
School of Computing, KAIST, South Korea
Adelaide University, Australia
Adelaide University, Australia