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CALL FOR PAPERS - MAIN TRACK
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PAKDD 2026 will be held exclusively in person. All accepted presentations must be delivered on-site.

The 30th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) will take place in Hong Kong SAR, China, on June 9-12, 2026. PAKDD 2026 is soliciting contributed technical papers for presentation at the Conference and publication in the Conference Proceedings by Springer. We solicit novel, high-quality, and original research papers that provide innovative insights into all facets of knowledge discovery and data science, including but not limited to theoretical foundations of mining, inference, and learning, big data technologies, as well as security, privacy, and integrity. We also encourage visionary papers on emerging topics and application-based papers offering innovative technical advancements to interdisciplinary research and applications of data science.

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IMPORTANT DATES

Submission Deadline: November 15, 2025
Paper Acceptance Notification: February 8, 2026
Camera Ready Papers Due: March 1, 2026
*All deadlines are 23:59 Pacific Standard Time (PST)

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CONFERENCE TOPICS

Topics of relevance for the conference include, but are not limited to, the following:
Note: Papers related to the large language models (LLMs) could be submitted to "Special Track on LLMs for Data Science"

Theoretical Foundations
- Generative AI, quantum ML, neuro-symbolic methods and reasoning, causal reasoning, non-IID learning, OOD generalization, representation learning, mathematical and statistical foundations, information theoretic approaches, optimization method
- Theoretical foundations for fairness, trustworthy AI, safety, model explainability, and XAI

Learning Methods and Algorithms
- Clustering, classification, pattern mining and association rules discovery
- Supervised learning, semi-supervised learning, few-shot and zero-shot learning, active learning
- Reinforcement learning and bandits
- Transfer learning, federated learning
- Anomaly detection, outlier detection
- Learning in recommendation engines
- Learning in streams and in time series
- Learning on structured data, images, texts and multi-modal data
- Online learning, model adaption
- Graph mining and Graph NNs
- Trustworthy Machine Learning
- Fairness
- Data Proces

Data Processing for Learning
- Dimensionality reduction, feature extraction, subspace construction
- Data cleaning and preparation, data integration and summarization
- Learning in real-time
- Big data technologies
- Information retrieval
- Data/entity/event/relationship extraction
- User interfaces and visual analytics

Security, Privacy, Ethics, Information Integrity and Social Issues
- Modeling credibility, trustworthiness, and reliability
- Privacy-preserving data mining and privacy models
- Model transparency, interpretability, and fairness
- Misinformation detection, monitoring, and prevention
- Social issues, such as health inequities, social development, and poverty

Interdisciplinary Research on Data Science Applications
- Social network/media analysis and dynamics, reputation, influence, trust, opinion mining, sentiment analysis, link prediction, and community detection
- Symbiotic human-AI interaction, human-agent collaboration, socially interactive robots, and affective computing
- Internet of Things, logistics management, network traffic and log analysis, and supply chain management
- Business and financial data, computational advertising, customer relationship management, intrusion and fraud detection, and intelligent assistants
- Urban computing, spatial data science and pervasive computing
- Medical and public health applications, drug discovery, healthcare management, and epidemic monitoring and prevention
- Methods for detecting and combating spamming, trolling, aggression, toxic online behaviors, bullying, hate speech, and low-quality and offensive content
- Climate, ecological, and environmental science, and resilience and sustainability
- Astronomy and astrophysics, genomics and bioinformatics, high energy physics, robotics, AI-assisted programming, and scientific data

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SUBMISSION DETAILS

Please refer to Author's Kit (https://www.pakdd2026.org/authors-kit) for submission details. If you have any questions, please feel free to contact us at pakdd2026.pc@gmail.com

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PAKDD PROGRAM COMMITTEE CHAIRS

Raymond Wong Hong Kong University of Science and Technology
Hanghang Tong University of Illinois Urbana-Champaign
Hua Lu Aalborg University

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CALL FOR PAPERS - SURVEY TRACK
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PAKDD 2026 will be held exclusively in person. All accepted presentations must be delivered on-site.

The 30th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) will take place in Hong Kong, China, on June 9-12, 2026. The PAKDD 2026 Survey Track solicits high-quality survey papers that present a structured synthesis of a particular topic in the area of knowledge discovery, data mining and machine learning, including but not limited to theoretical foundations of mining, inference, and learning, big data technologies, as well as security, privacy, explainability, and integrity. Papers accepted to the Survey Track will be published in the PAKDD proceedings by Springer. At least one author of each accepted survey paper must register for the conference and present the work.

For up-to-date information on PAKDD 2026, please visit its homepage: https://www.pakdd2026.org.

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IMPORTANT DATES

Paper Submission Deadline: November 15, 2025
Paper Acceptance Notification: February 8, 2026
Camera Ready Papers Due: March 1, 2026
*All deadlines are 23:59 Pacific Standard Time (PST)

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SUBMISSION

Submitted papers should be anonymous and are not allowed to include the author names and affiliations. Submitted survey papers must be formatted according to PAKDD guidelines and submitted electronically through the PAKDD 2026 special track paper submission site. Submissions must be self-contained; the PAKDD survey track will not accept or review any supplementary material. Submitted survey papers must be no longer than 18 pages in total: 15 pages for the main text of the paper and up to 3 additional pages for references. Final camera-ready versions will be formatted according to the publisher's instructions. Submissions not in compliance with these length and formatting requirements will not be considered for review.

Submission Details: https://www.pakdd2026.org/authors-kit

If you have any questions, please feel free to contact us at pakdd2026.survey@gmail.com.

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PAKDD 2026 SURVEY TRACK CHAIRS

Elena Baralis Politecnico di Torino, Italy
Guandong Xu The Education University of Hong Kong, China

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CALL FOR PAPERS - SPECIAL TRACK ON LLMS FOR DATA SCIENCE
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PAKDD 2026 will be held exclusively in person. All accepted presentations must be delivered on-site.

The rapid advancements in Large Language Models (LLMs) have opened new avenues for innovation and research across various domains, particularly in the field of Data Science. As LLMs continue to evolve, their applications in data analysis, machine learning, natural language processing, and decision-making processes are becoming increasingly profound. The PAKDD 2025 Special Track on Large Language Models for Data Science aims to explore the transformative potential of LLMs for Data Science, bringing together researchers, practitioners, and industry experts to discuss the latest developments, challenges, and opportunities in this rapidly growing area. Novel, high-quality, and original research papers that provide innovative insights into all facets of large language models and their applications in data science, including but not limited to science and algorithms of LLMs, enlarged language models, retrieval-augmented text generation, vision-language pretraining, vision transformers, trustworthiness and societal implications of LLMs, and LLMs on diverse applications are solicited. Papers accepted to the LLM Special Track will be published in the PAKDD proceedings by Springer. At least one author of each accepted paper must register for the conference and present the work.

For up-to-date information on PAKDD 2026, please visit its homepage: https://www.pakdd2026.org.

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IMPORTANT DATES

Paper Submission Deadline: November 15, 2025
Paper Acceptance Notification: February 8, 2026
Camera Ready Papers Due: March 1, 2026
*All deadlines are 23:59 Pacific Standard Time (PST)

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TOPICS

- LLM-enhanced Data Analytics: Methods for leveraging LLMs to automate or augment data analysis workflows.
- LLM-based Data Preprocessing and Cleaning: Using LLMs for data wrangling, missing value imputation, or schema alignment.
- LLMs for Data Integration and Knowledge Graph Construction: Techniques for using LLMs to merge heterogeneous data sources or build structured knowledge graphs.
- LLMs for Data Labeling and Annotation: Semi-automatic or interactive labeling pipelines powered by LLMs.
- Prompt Engineering for Data Science Tasks: Systematic methods for prompt design to solve data mining tasks.
- LLMs for Feature Engineering and Selection: Automating feature extraction, selection, or transformation using LLMs.
- LLM-powered Conversational Interfaces for Data Analysis: Chatbots or agents that assist with exploratory data analysis via natural language.
- LLMs for Explainable Data Science: Using LLMs to generate natural language explanations of models or complex datasets.
- Combining LLMs with Classical Machine Learning Models: Hybrid frameworks where LLMs support or supervise classical models.
- Evaluation and Benchmarking of LLMs for Data Science: Novel benchmarks or empirical studies on how well LLMs perform real-world data science tasks.
- Domain-specific LLMs for Data-intensive Applications: Fine-tuning or adapting LLMs for domains like finance, healthcare, or scientific research.
- Human-in-the-loop Systems with LLMs for Data Science: Designing interactive systems where LLMs assist analysts or domain experts.
- Trust, Reliability, and Bias Mitigation in LLM-assisted Data Science: Addressing risks and ethical concerns when using LLMs in data-driven workflows.
- Applications and Case Studies: Practical reports showing how LLMs are deployed to solve data science problems in industry or research.

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SUBMISSION

Submission Details: https://www.pakdd2026.org/authors-kit
If you have any questions, please feel free to contact us at pakdd2026.llm@gmail.com.

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PAKDD 2026 LLM TRACK CHAIRS

Carl Yang Emory University, USA
Xiang Li East China Normal University, China

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CALL FOR APPLICATIONS - DOCTORAL CONSORTIUM
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https://www.pakdd2026.org/call-for-doctoral-consortium

PAKDD will take place in Hong Kong SAR, China, on June 9-12, 2026. The PAKDD2026 organizing committee invites students to apply for the doctoral consortium. The Doctoral Consortium (DC) provides an opportunity for doctoral students to discuss and explore their research interests and career objectives with a panel of established researchers in knowledge discovery and data mining. Doctoral students expect to interact with other researchers through participation in conference events and receive feedback on their current research and guidance on future research directions.

All PhD students are welcome to apply!
(PAKDD 2026: the 30th Pacific-Asia Conference on Knowledge Discovery and Data Mining)

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IMPORTANT DATES

Submission Deadline: February 10, 2026
Acceptance Notification: March 6, 2026
Submission of Camera Version: March 25, 2026
*All deadlines are 23:59 Pacific Standard Time (PST)

All doctoral consortium applications should be submitted to https://cmt3.research.microsoft.com/PAKDDDC2026
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APPLICATION INSTRUCTIONS

1. Cover Sheet
A one-page information sheet that includes the following:

Your full name
Email address
Affiliation: department, university, country
Personal home page (URL)
(Optional) Your gender
Country of Citizenship
Are you a member of an underrepresented minority ethnic group? If so, please specify.
Expected graduation date
Your thesis advisor's full name
Your thesis advisor's contact details (title, department, affiliation, and email address)
List of up to 5 keywords to help us select reviewers for your application

2. Thesis Summary
The summary (maximum three pages) should include the thesis title, the research questions being investigated, significance of this problem, key challenges, and important related work. Describe the proposed research plan and anticipated thesis contribution. Include a brief timeline and the planned work in your dissertation study.

Remember that the audience for your thesis summary includes people who are knowledgeable about data science, but are not necessarily experts in the specific topic of your thesis. Introduce the content at a high level so that the general data science researchers can understand, but also include sufficient low-level details so that the experts will appreciate your unique contribution.

The thesis summary is limited to three pages, in Springer format, including references.

Springer LNCS/LNAI manuscript submission guidelines and formatting template (https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines)

All the manuscripts must be prepared and submitted in accordance with the above format. The use of generative AI models (e.g., large language models (LLMs)) must be explicitly disclosed and explained in the submission form. LLMs may only be employed for grammatical error correction. If generative AI is used at any stage of the paper-writing process, the authors should assume full responsibility for all content, including checking for plagiarism and correctness of the entire submission. Misuse of LLMs may lead to disqualification of application for the DC.

3. Curriculum Vita
Include a CV (at most one page) that describes your background, relevant experience (e.g., research, education, employment), and a list of your publications (including those under review and planned to be submitted) if you have any.

4. Advisor's Support Letter
The letter should describe the status of your thesis research and progress through your graduate program.

5. (Optional) Questions
A short (at most one-page) statement of what you expect to gain from presenting and participating in the DC and what specific questions you may have.

Please combine the documents into one PDF document with at most seven pages in total (1-page cover sheet, 3-page thesis summary, at most 1-page CV, 1-page support letter from advisor, and 1-page questions).

Note that DC thesis summaries will not be included in the conference proceedings but are available on the PAKDD2026 webpage. All participants selected to present their work at the Doctoral Consortium are expected to be present throughout the consortium.

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DOCTORAL CONSORTIUM CO-CHAIRS OF PAKDD2026

Xiao Huang Hong Kong Polytechnic University
Byron Choi Hong Kong Baptist University

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CALL FOR WORKSHOP PROPOSALS
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PAKDD 2026 will be held exclusively in person. All accepted presentations must be delivered on-site.

The 30th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) will take place in Hong Kong, China, on June 9-12, 2026. The PAKDD 2026 organizing committee invites workshop proposals covering foundational and emerging topics in all KDD-related areas, including data science, data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems, and emerging applications. The PAKDD workshops provide an informal and vibrant opportunity for researchers and industry practitioners to exchange their research perspectives, original research results, and practical development experiences on specific challenges and emerging issues. Each workshop should be focused on a cohesive theme so that participants can benefit from meaningful interactions with each other. Please note that PAKDD 2026 will be held entirely in-person, so we won't be able to accommodate workshops with virtual or hybrid elements.

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IMPORTANT DATES

- Workshop Proposal Submission Deadline: November 15, 2025
- Workshop Proposal Acceptance Notification: December 6, 2025

Additionally, we urge workshop organizers to adhere to the following author-related deadlines:
- Workshop CFP Announcement: December 13, 2025
- Workshop Paper Deadline: February 22, 2026
- Workshop Paper Acceptance Notification: March 15, 2026
- Workshop Paper Camera-ready: March 29, 2026
*All deadlines are 23:59 Pacific Standard Time (PST)

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TOPICS OF INTEREST

While workshop topics typically align with those identified in the PAKDD 2026 call for papers, we also welcome proposals focusing on other facets of data science, data mining and knowledge discovery. Interdisciplinary workshops that explore the convergence of data science, data mining and knowledge discovery with various disciplines are also encouraged.

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FORMAT

Workshops are scheduled to be held at the beginning of the conference, June 9, 2026. The workshop papers will not be included in the conference proceedings but are available on the PAKDD2026 webpage. Springer Nature will collaborate to connect the workshops with journals or book series for the publication of workshop papers.

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DUTIES

The organizers of accepted workshops are responsible for:

- Disseminating the call for papers
- Collecting and managing submissions
- Forming program committees
- Conducting the reviewing process
- Curating the final workshop program

The organizers and chairs of the workshop shall have full control over the call for papers, formation of program committees, reviewing and selection of papers as well as planning the workshop program. However, the workshop chairs are not allowed to submit papers to the workshops to ensure a fair review process. The conference program chairs may check the final decisions of workshop papers.

The registration fees for workshops will be determined by the conference (not the workshop itself). The fees will be paid to the conference, and the conference will provide workshop facilities including working notes printing, meeting rooms, coffee breaks, and proceedings, etc.

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SUBMISSION

Template: https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines

All the manuscripts must be prepared and submitted in accordance with the above format. Usage of other formats may lead to disqualification of paper for the conference.

The workshop proposal should contain the following information:

- Title of the workshop
- Objectives, scope, and contribution to the main conference
- Names, affiliations and contacts of the organizers
- Tentative list of the program committee members
- Length of the workshop (full day or half day)
- Expected number of submissions and attendees

Workshop proposals should be submitted by November 15, 2025 at 11:59PM (PST). Please prepare a PDF (maximum three pages) that contains the aforementioned contents and send it to PAKDD2026.workshop@gmail.com.

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WORKSHOP CO-CHAIRS OF PAKDD2026

Cheng Long Nanyang Technological University, Singapore
Jieming Shi The Hong Kong Polytechnic University, Hong Kong
Yuxuan Liang The Hong Kong University of Science and Technology (Guangzhou), China

PAKDD2026.workshop@gmail.com

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CALL FOR TUTORIALS
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The 30th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) will take place in Hong Kong, China, on June 9-12, 2026. We invite proposals for half-day (3 hours) tutorials from active researchers in both academia and industry who are experienced and engaging presenters. Ideally, a tutorial will cover the state-of-the-art research, development, and applications in a specific data mining domain, to stimulate and facilitate future work. Tutorials on interdisciplinary areas, novel and fast-growing directions, and significant applications are highly encouraged.

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IMPORTANT DATES

- Proposal due: February 10, 2026
- Tutorial notification: February 28, 2026
- Submission of tutorial notes: April 25, 2026
*All deadlines are 23:59 Pacific Standard Time (PST)

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PROPOSAL

Formatting Template: https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines

All the Manuscripts must be prepared and submitted in accordance with the above format. Usage of other formats may lead to disqualification of paper for the conference.

A tutorial proposal should include the following and should not exceed 5 pages excluding references:

- Title
- Abstract
- Tutorial outline, including background, goals and objectives
- Presenters' name, affiliation, address, email, phone
- A biographical sketch of the presenter(s)
- References
A list of up to 20 most important references that will be covered in the tutorial.

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SUBMISSION

Please prepare a PDF (maximum five pages) that contains the aforementioned contents and send it to pakdd2026.tutorial@gmail.com.

Proposals will be evaluated by the tutorial co-chairs based on merit and relevance. The tutorial presenters will be required to provide comprehensive tutorial notes prior to the event, which will be published on the PAKDD website. Tutorials are expected to be scheduled on the day before the main PAKDD conference, June 9, 2026. All presenters named in the proposal are expected to attend physically to present the tutorial. For each accepted tutorial proposal, the PAKDD organizing committee may provide support for the tutorial lecturer attendance in the form of ONE Workshop, Tutorial, or Consortium Only (i.e. 9 June only) registration to the conference. Tutorial lecturers should contact the local team at pakdd2026.reg@gmail.com for obtaining the complimentary registration with specific tutorial and lecturer information.

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TUTORIAL CO-CHAIRS OF PAKDD2026

Jianliang Xu Hong Kong Baptist University
Gao Cong Nanyang Technological University
Sinno Jialin Pan Chinese University of Hong Kong

pakdd2026.tutorial@gmail.com