KDD 2026 Workshop

The 1st International Workshop on
AI Data Scientist

Aug. 10, 2026 (Morning Workshop) · Jeju International Convention Center (ICC), Jeju, Korea

Submit via OpenReview Call for Papers

About the Workshop

This workshop brings together researchers, practitioners, and industry leaders to discuss the opportunities and challenges of AI Data Scientists, including system design, benchmarking, trustworthiness, human-AI collaboration, and real-world deployment.

Where

Jeju International Convention Center (ICC), Jeju, Korea

When

Aug. 10, 2026 (Morning Workshop)

Overview

AI Data Scientist is emerging as a new paradigm for building intelligent systems that can assist with, coordinate, or automate core stages of the end-to-end data science lifecycle.

Background

As data volumes and analytical demands continue to grow, traditional data science workflows increasingly struggle to deliver the efficiency, scalability, and reliability required in both research and industry. At the same time, recent advances in large language models and agentic AI have opened a promising new direction: using intelligent systems as assistants that can augment or even automate end-to-end data science pipelines.

From data exploration and cleaning to feature engineering, modeling, evaluation, interpretation, and deployment, these systems point toward the emergence of a new paradigm: the AI Data Scientist. In recent years, this area has attracted growing attention across machine learning, data mining, natural language processing, automated machine learning, human-computer interaction, and scientific discovery. Important progress has been made, but many discussions remain fragmented across communities and application domains.

KDD is the premier venue for data mining and data science innovation, making it the ideal place to convene researchers and practitioners interested in the future of intelligent data science systems. The workshop is closely aligned with KDD's strengths in applied data science, machine learning systems, intelligent automation, and real-world impact.

Scope and Goal

This workshop focuses on the foundations, systems, benchmarks, applications, and societal implications of AI Data Scientists. We are particularly interested in how intelligent systems can support end-to-end data workflows, integrate foundation models with data-centric capabilities, and collaborate effectively with human experts in realistic settings.

The goal of the workshop is to provide a dedicated forum for cross-disciplinary dialogue on the development of AI Data Scientists, including their architectures, training strategies, evaluation methodologies, deployment settings, safety concerns, and responsible use. The workshop will highlight both research advances and applied systems, while encouraging discussion around the broader future of data science practice in the age of AI.

We welcome researchers and professionals from applied data science, machine learning and AI, natural language processing, automated machine learning, human-computer interaction, information systems, AI for scientific discovery, and industrial data analytics.

Call for Papers

We invite submissions from both academia and industry on the emerging foundations, systems, benchmarks, applications, and societal implications of AI Data Scientists.

Topics of Interest

  • Foundation models for tabular, graph, spatial, and time series data
  • Architectures for AI Data Scientists
  • Prompt engineering for AI Data Scientists
  • Open datasets and benchmarks for AI Data Scientists
  • Mid-training and post-training for AI Data Scientists
  • Evaluation and benchmarking of AI Data Scientists
  • Automated data cleaning, feature engineering, visualization, and other data-centric capabilities
  • Human-AI collaboration in data science workflows
  • Privacy and security issues of AI Data Scientists
  • Ethical and social implications of AI Data Scientists
  • Applications of AI Data Scientists in science, business, and industry

Submission Format

We welcome technical submissions on the foundations, systems, benchmarks, and applications of AI Data Scientists. Both research papers and system or demo papers are invited.

  • Research Paper (up to 8 pages)
  • System or Demo Paper (up to 4 pages)

The page limit excludes references and supplementary materials. Submissions should be prepared in PDF format using the KDD 2026 template.

Submission Protocol: OpenReview
Submission Template: KDD 2026 template
Archival Option: Workshop papers are expected to be non-archival and will not appear in the ACM Digital Library unless otherwise announced.

Submit Paper View Template

Awards

  • Best Paper Award
  • Best Demo Paper Award

Important Dates

All times are listed in GMT+8.

Submission Start Date

10 Apr 2026

Submission opens on OpenReview

Extended Submission Deadline

23 May 2026

Paper submission deadline extended to 23 May 2026

Workshop Paper Notification

4 June 2026

Workshop paper notification

Organizing Committee

Hao LIU
Google Scholar

Hao LIU

The Hong Kong University of Science and Technology (Guangzhou)

Marinka Zitnik
Google Scholar

Marinka Zitnik

Harvard University

Yong Li
Google Scholar

Yong Li

Tsinghua University

Jindong Han
Google Scholar

Jindong Han

Shandong University

Xia Hu
Google Scholar

Xia Hu

Shanghai Artificial Intelligence Laboratory

Xing Xie
Google Scholar

Xing Xie

Microsoft Research Asia

Invited Talks

Confirmed invited speakers include Lei Chen, Le Cong, and Peng Cui. Additional talk details will be announced soon.

Invited Speaker

Lei Chen

The Hong Kong University of Science and Technology (Guangzhou)

Title: TBD
Invited Speaker

Le Cong

Stanford University

Title: TBD
Invited Speaker

Peng Cui

Tsinghua University

Title: Towards Generalist Models for Structured Data
Abstract: In recent years, large language models have made significant progress in understanding and generating unstructured data, such as text and images. However, in the realm of structured data, which is the cornerstone of modern socio-economic operations, we are still facing a lack of general AI capabilities. Current solutions based on specialized models are expensive to develop and exhibit weak generalization, while directly applying large language models to structured data reveals serious limitations in areas such as numerical reasoning, causal discovery, and out-of-distribution generalization. In this talk, the speaker will focus on recent advances in generalist models for structured data and their application prospects in industrial scenarios, thereby offering new technological pathways for intelligent prediction and decision-making in high-value, high-stake fields.

Event Schedule

Tentative half-day program. The final schedule will be announced after the review process.

Opening and Welcome

Workshop opening remarks.

Invited Talks

Invited talks by Lei Chen, Le Cong, and Peng Cui.

Coffee Break and Poster/Demo Session

Networking and demo interaction session.

Paper Presentations

Five paper presentations, each with 12 minutes presentation time and 3 minutes Q&A.

Closing Discussion

Closing discussion session on the future of AI Data Scientists.

Workshop Venue

KDD 2026

Jeju International Convention Center (ICC)

This workshop is part of The 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining, held at Jeju International Convention Center (ICC) in Jeju, Korea, from August 9, 2026 to August 13, 2026.

Current Venue Status

  • Workshop slot: Aug. 10 Morning Workshops
  • Workshop day: Aug. 10, 2026
  • Venue: Jeju International Convention Center (ICC), Jeju, Korea
  • Workshop room: to be announced by KDD 2026

Room assignment and on-site logistics will be updated once released by the KDD 2026 organizers.

Contact

Main Contact

Hao Liu

The Hong Kong University of Science and Technology (Guangzhou)

Email Us

liuh@ust.hk

For inquiries about submissions, speakers, collaboration, or workshop organization.