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
Venue details to be announced by KDD 2026
When
Workshop day to be announced by KDD 2026
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.
Awards
- Best Paper Award
- Best Demo Paper Award
Important Dates
All times are listed in GMT+8.
10 Apr 2026
Submission opens on OpenReview
16 May 2026
Paper submission deadline
4 June 2026
Workshop paper notification
Organizing Committee
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 speaker session.
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
Venue Details To Be Announced
This workshop is part of the KDD 2026 Workshop Program. Detailed information on the workshop date, room assignment, and venue logistics will be posted once confirmed by the KDD 2026 organizers.
Current Venue Status
- Workshop day: to be announced by KDD 2026
- Workshop room: to be announced by KDD 2026
- On-site logistics: will be posted after final assignment
Once the official workshop date and room are released, this section can be updated with the final venue details, transportation tips, and nearby hotel information if needed.
Contact
Main Contact
Hao Liu
The Hong Kong University of Science and Technology (Guangzhou)
Email Us
For inquiries about submissions, speakers, collaboration, or workshop organization.