Workshop on Human-In-the-Loop Data Analytics
Co-located with SIGMOD 2026 (Bengaluru, India)


Venue: Sheraton Grand Bengaluru Whitefield Hotel & Convention Center, Bengaluru, India
Date: May 31, 2026

Past workshops: HILDA 2025 | HILDA 2024 |HILDA 2023 | HILDA 2022 | HILDA 2020 | HILDA 2019 | HILDA 2018 | HILDA 2017 | HILDA 2016

The Human-in-the-Loop Data Analytics (HILDA) workshop provides a forum for researchers and practitioners to exchange ideas and results on how data management and analysis can be conducted with a deep awareness of the people who design, build, interpret, and are impacted by these processes. HILDA brings together researchers from the database systems, human–computer interaction, information visualization, data mining, and machine learning communities to explore the distinctive ways in which humans interact with data systems.

This year's theme, Collaborative Human–AI Data Analysis Workflows, emphasizes the growing need to design and understand data systems where humans and artificial intelligence, particularly large language models (LLMs) collaborate as partners. The success of LLMs highlights the critical role of human interaction in achieving meaningful, reliable, and context-aware outcomes. We invite submissions that study or enable such human–AI partnerships in data analysis pipelines, spanning data curation, exploration, visualization, interpretation, and decision-making.

Given that HILDA 2026 will be held in Bengaluru, India, a global hub for data-driven innovation, human-centered technology, and social impact, we particularly welcome work that explores human–AI collaboration in real-world, socially relevant, or resource-constrained settings. Topics such as fairness, inclusion, and cultural context in data systems are especially encouraged.

Program

The schedule is not finalized yet. Please check closer to the event.

HILDA 2026 Keynote Talks

Our exciting program will feature the two invited keynote speakers to talk about the challenges of human-data interaction.

Aditya Parameswaran

Title: TBD

Aditya Parameswaran, Associate Professor, University of California, Berkeley

Speaker Bio: Aditya Parameswaran is an Associate Professor in EECS at the University of California, Berkeley. He co-directs the EPIC Data Lab and the Police Records Access Project, and is a co-founder of Ponder, which was acquired by Snowflake in October 2023. His recent work explores LLM-powered data tooling, including new approaches to data extraction, transformation, and insight discovery that treat large language models as a core systems component. He is particularly excited about designing data systems both with and for LLMs. More broadly, his research focuses on simplifying data science at scale—empowering individuals and teams to more easily, efficiently, and effectively make sense of large datasets—with a special emphasis on underserved application domains with limited data expertise.

Shailesh Kumar

Title: TBD

Shailesh Kumar, Dean, Jio Institute Chief Data Scientist, Center of Excellence in AI/ML, Jio Platforms

Speaker Bio: Dr. Shailesh Kumar is currently the Chief Data Scientist at the Centre of Excellence in AI/ML, Reliance Jio, Dean for the AI/DS program at the Jio Institute of Eminence, and a Visiting faculty of Machine Learning at the Indian School of Business. Prior to this he worked as a Distinguished Scientist at Ola cabs, Chief Scientist and Co-founder of Third Leap, an EdTech startup, Researcher in the Google Brain team, Sr. Scientist at Yahoo! Labs and Principal Scientist at Fair Isaac Research. Dr. Kumar has 20 years of experience in building AI solutions in a variety of domains including Telecom, Retail, Finance, Fleet Management, Healthcare, Agriculture, Education, Computer Vision, Knowledge Graph, Natural Language Processing, and Conversational computing. He has published over 20 international papers and book chapters and holds more than 30 patents in AI/ML. He was recognized as one of the top 10 data scientists in India in 2015 and Top 10 most influential Analytics Leaders in India in 2020 by Analytics India Magazine. Dr. Kumar holds a Masters and PhD in AI from UT-Austin and B.Tech. in Computer Science from IIT-Varanasi.

What to submit

We welcome both traditional research papers and exploratory or non-traditional contributions, including early-stage or in-progress work, experience reports, reflections, open problems, research visions, and speculative ideas. Submissions should present work or perspectives that are likely to spark engaging discussion at the workshop or that the authors explicitly seek feedback and mentoring on. We encourage contributions that propose new designs for human-centered data management systems, empirically study how people interact with data systems, or draw from perspectives across database systems, HCI, visualization, machine learning, industry practice, and organizational or social contexts.

Example topics of interest include, but are not limited to:

  • Human–AI and human–LLM collaboration in data analysis workflows
  • Interactive query refinement, exploration, and visualization
  • Human-assisted data integration, labeling, and cleaning
  • Perception-aware and context-aware data processing
  • Cognitive models of data understanding and decision-making
  • Fairness, ethics, and accountability in data-driven systems
  • Provenance, explanation, and interpretability in AI-assisted data systems
  • Human-in-the-loop learning, debugging, and evaluation
  • Crowd-powered and community-driven data infrastructure
  • Design and evaluation of data systems for social good, sustainability, and inclusion

Mentoring-Centered Workshop Format

HILDA 2026 continues its mentoring-focused format introduced in 2022. Authors of accepted papers can opt in to a mentoring program, where they will be paired with a program committee member for feedback and guidance before the camera ready submission.. This model aims to foster constructive discussion, skill development, and interdisciplinary collaboration, particularly supporting early-career researchers and new contributors to the HILDA community.

All accepted papers will be presented at the workshop, which will emphasize discussion and engagement over static presentations. The workshop will also feature invited keynote speakers from the visualization, AI ethics, and human-centered computing communities to broaden the interdisciplinary dialogue.

Review and Mentorship Process

Reviews are single-blind. Each submission will be reviewed by at least three reviewers, where the reviewers will assess:

  • Fit with HILDA's scope and mentoring model
  • Quality and clarity of the work
  • Potential for future impact and discussion

Authors of accepted papers can opt in to the mentoring program and will be paired with a program committee member. Authors and mentors may withdraw from a pairing without repercussions in the case of unforeseen conflicts, and the program chairs will assign an alternative mentor when possible.

Submission Instructions

Submissions should reflect the current state of the research and include a brief discussion of limitations, open challenges, or questions the authors would like feedback on from mentors and the HILDA community.

The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.

Proceedings

We will provide links to accepted papers in the program here as well as publish them for a year through the ACM Digital Library.

Important Dates

  • Workshop Date: May 31, 2026
  • Submission: March 23, 2026 (AOE)
  • Notification of outcome: April 15, 2026
  • Camera-ready due: May 10, 2026 (AOE)

Workshop Chairs

Program Committee

  • Aamod Khatiwada (Microsoft)
  • Andra Ionescu (KTH Royal Institute of Technology)
  • Avigdor Gal (Technion - Israel Institute of Technology)
  • Cindy Xiong Bearfield (Georgia Tech)
  • Danyel Fisher (Independent Consultant)
  • Enrico Bertini (Northeastern University)
  • Fatemeh Nargesian (University of Rochester)
  • George Fletcher (Eindhoven University of Technology)
  • Grace Fan (New York University)
  • Kaustav Bhattacharjee (NJIT)
  • Roee Shraga (WPI)
  • Romila Pradhan (Purdue University)
  • Yuval Moskovitch (Ben Gurion University)
  • Zafeiria Moumoulidou (Meta)
  • Zhengjie Miao (Simon Fraser University)

Steering Committee

  • Carsten Binnig (TU Darmstadt)
  • Juliana Freire (New York University)
  • Aditya Parameswaran (University of California, Berkeley)
  • Arnab Nandi (Ohio State University)

Contact

For questions, please email the workshop chairs directly.