IEEE International Conference on Data Mining (ICDM) — 2026
November 12-15, 2026
Northeastern University (NEU)Shenyang, China
Data Mining Machine Learning
Important Dates
| Submission deadline | June 6, 2026 (closed) |
| Notification of acceptance | August 16, 2026 (passed) |
ICDM is the world’s premier research conference in data mining, covering algorithms, systems, and applications across machine learning, deep learning, graph mining, time series analysis, and recommender systems. It has shaped the field for over two decades with a rigorous, selective review process and a program spanning both academic research and industry applications. Data scientists, researchers, and engineers attend to present novel methods and connect with the global data mining community.
Venue
Northeastern University (NEU)
No. 3-11 Wenhua Road, Heping District, Shenyang, Liaoning 110819, China
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AI-ready Data for Science
Focuses on preparing data for AI-driven scientific discovery, which is usually the limiting factor rather than the model. Topics include...
AI-for-Science Benchmarking
Covers benchmarking AI methods for scientific applications, on the premise that claims in AI for science are currently outrunning the...
Adaptable Reliable Responsible Learning
Focuses on adaptability, reliability and responsibility in machine learning, treating the three as a single problem rather than separate research...
Foundation Models for Biology
Explores foundation models for biology and bioinnovation, an area that has moved quickly since large pretrained models began working on...
Data and Database Systems for AI
Covers data and database systems that underpin modern AI, the infrastructure layer that rarely gets its own venue. Topics include...
Deep Learning and Clustering
Focuses on deep-learning approaches to clustering and representation learning, where the two problems are increasingly the same problem. Topics include...
Data Mining for Ambient Intelligence
Applies data mining to ambient intelligence and secure communications: environments densely instrumented with sensors that are expected to respond to...
Data Mining in Biomedical Informatics
Applies data mining to biomedical informatics and healthcare data, including electronic health records, clinical notes, registries and monitoring streams. Topics...
Data Mining for Service
Applies data mining to service systems and service science, covering the operational side of businesses that deliver services rather than...
Evolutionary Data Mining
Covers evolutionary computation approaches to data mining and machine learning: genetic algorithms, genetic programming, swarm methods and related population-based search....
Evolving Graph Data Mining
Focuses on mining evolving graphs and continual relational learning, where the structure itself changes over time rather than staying fixed....
GNN-LLM Synergy
Combines graph neural networks with large language models for reasoning over structure, bringing together two communities that solve complementary halves...
Human Dynamics and Mobility Analytics
Focuses on mining human dynamics and mobility in the age of AI agents, covering how people move through cities and...
High Dimensional Data Mining
Focuses on mining and learning from high-dimensional data, where distance measures lose meaning and most classical intuitions stop holding. Topics...
Incremental and Continual Learning
Covers incremental, continual and lifelong learning: models that keep learning after deployment instead of being retrained from scratch. The central...
Knowledge Discovery in ISAC
Applies knowledge discovery to integrated sensing and communication systems, in which the same radio hardware both transmits data and senses...
LLMs for Multimodal Data Fusion
Applies large language models to fusing multimodal data, using language as the connective layer between modalities that are otherwise hard...
LLMs and Tensor Analysis
Explores the interplay of large language models and tensor analysis, in both directions. Topics include tensor decomposition for compressing and...
Large Models for Time Series
Covers large and foundation models applied to time series data mining, an area that arrived late compared with text and...
Medical Time Series Foundation Models
Covers foundation models for medical time series analytics, including ECG, EEG, vital signs and continuous monitoring data from intensive care...
Mental Health on Social Media
Covers detecting mental-health signals in social media data, a research area with unusually heavy ethical weight. Topics include modelling linguistic...
Multimodal Mining for Agriculture
Applies multimodal data mining to sustainable agriculture, combining satellite and drone imagery, in-field sensors, weather records and farm management data....
Machine Learning for Cybersecurity
Applies machine learning to cybersecurity problems, where the data is adversarial by construction rather than merely noisy. Topics include intrusion...
Optimization for Data Mining
Applies optimization techniques to emerging data mining problems, focusing on the mathematical machinery underneath rather than on applications. Topics include...
Open World Anomaly Detection
Covers anomaly detection in open, dynamic and evolving settings, where the closed-world assumption behind most benchmarks does not hold. Topics...
Pattern Mining for Bioinformatics
Applies pattern mining and machine learning to bioinformatics, covering sequence, structure and omics data. Topics include motif and frequent pattern...
Clustering with Pretrained Models
Explores clustering using pretrained and foundation models, which has quietly changed how the task is approached. Rather than learning a...
Sentiment Analysis
Covers sentiment analysis and opinion mining from text, a long-running area substantially reshaped by large language models. Topics include aspect-based...
Spatial and Spatiotemporal Data Mining
Covers data mining over spatial and spatiotemporal data, where observations are correlated across both space and time and standard independence...
Secure Federated Generative AI
Covers security and trust in federated generative AI, combining two areas whose risks compound. Federated training keeps data local, but...
Trustworthy ML for Decision-Making
Covers fairness, privacy, robustness and explainability in decision-making machine learning, in settings where a model's output changes someone's circumstances. Topics...
Trustworthy Federated Learning for Industry
Focuses on trustworthy federated learning for smart industrial systems, where data is distributed across factories and firms that have commercial...
Trustworthy Recommender Systems
Focuses on trust, privacy and unlearning in recommender systems, covering the obligations that arrive once recommenders are regulated rather than...
Urban Intelligence and Mobility
Covers urban intelligence and multimodal mobility data mining, treating the city as a sensed system. Topics include integrating transit, ride-hailing,...
AI for Personalization
Covers AI and data mining methods for personalization and recommendation, spanning both the modelling and the consequences. Topics include user...
World Models and Autonomous Intelligence
Explores world models and autonomous intelligence for data mining: learned internal models of an environment that an agent can use...
Our picks for IEEE International Conference on Data Mining (ICDM) attendees
A curated selection of hotels chosen for location, value, and fit for conference travellers.
DoubleTree by Hilton Shenyang
89 Fengyutan Street, Shenhe District, Shenyang 110013, China
Reliable Hilton property in Shenhe District convenient for the Northeastern University area.
Hilton Shenyang
374 Qingnian Street, Heping District, Shenyang 110004, China
Full-service Hilton in central Shenyang with indoor pool and spa, a short drive from the university campus.
Jinjiang Inn Shenyang Northeastern University
Wenhua Road, Shenhe District, Shenyang, China
Budget-friendly option closest to the Northeastern University campus.
NEU International Hotel Shenyang
80 West Wenti Road, Heping District, Shenyang 110004, China
On-campus hotel at Northeastern University - the most convenient option for ICDM conference attendees.
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