HHAI KEML 2026 - 2nd International Workshop on Informing ML with Knowledge Engineering for Hybrid Intelligent Systems

[Shreya Bhowmick Banerjee]

We are excited to share that following last year’s success, we are hosting the HHAI-KEML workshop again this year! We are pleased to invite you to submit your valuable research to the 2nd International Workshop on Informing ML with Knowledge Engineering for Hybrid Intelligent Systems (HHAI-KEML 2026) at Brussels, Belgium, from July 6-7, 2026.

We would greatly appreciate your help in circulating this opportunity within your network. 

Please feel free to reach out with any questions. We look forward to receiving your submission and hope to welcome you to Brussels, Belgium!

Here are all the important links:

Conference Website: https://haim-lab.github.io/hhaikeml2026

CfP: https://easychair.org/cfp/HHAI-KEML2026

Submission link: https://easychair.org/conferences/?conf=hhaikeml2026

 Please note that though in-person participation is highly encouraged, in case of travel related challenges, we will facilitate remote attendance and presentations.
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HHAI-KEML 2026: 2nd International Workshop on Informing ML with Knowledge Engineering for Hybrid Intelligent Systems

Vrije Universiteit Brussel and Université Libre de Bruxelles

July 6-7, 2026

Overview

Integrating Knowledge Engineering (KE) with Machine Learning (ML) offers a promising approach to building trustworthy AI systems. By combining the strengths of data-driven learning with structured knowledge—such as electronic health records in healthcare, scientific axioms, or legal guidelines—AI systems gain the ability to perform commonsense reasoning, enhancing their reliability and making them more knowledge-aware. Although using knowledge representation and reasoning methods can sometimes limit scalability, their ability to provide verifiable, human-understandable explanations makes them especially valuable in mission-critical applications.

The workshop hosted by HHAI 2026 seeks to bridge the gap between KE and ML by exploring the synergies between these fields. A key focus is on developing hybrid human-AI systems that utilize multimodal approaches, incorporating various forms of data including text, speech, images, and video. This collaborative forum will bring together researchers and practitioners from academia and industry to discuss cutting-edge research and innovative strategies for integrating KE and ML. Ultimately, the goal is to advance the development of AI systems that are not only robust and efficient but also transparent and human-centric, addressing both the challenges and benefits of merging knowledge representation and reasoning with data-driven techniques.

Check out our previous year program and proceedings here HHAI-KEML 2025 Workshop

Important Dates

·         Paper Submission: May 16, 2026 (23:59 AoE)

·         Acceptance Notification: May 23

·         Camera-ready Version: May 29, 2026

·         Workshop: July 6 or 7, 2026

·         Conference: July 8–10, 2026



Organizing Committee

·         Shreya Banerjee, University of New Orleans

·         Atriya Sen, Oklahoma State University

·         Yuan Lin, Kristiania University of Applied Sciences

Program Committee

·         Shreya Banerjee, University of New Orleans

·         Atriya Sen, Oklahoma State University

·         Yuan Lin, Kristiania University of Applied Sciences

·         Anthony Marchiafava, Oklahoma State University

·         Henry Fordjour Ansah, University of New Orleans

·         Bithi Banik, Kristiania University of Applied Sciences

Topics of Interest

·         Neuro-Symbolic Knowledge Representation

·         KRR and Commonsense Reasoning in ML

·         Artificial General Intelligence

·         KE with Generative AI and Large Language Models

·         KE in Multi-Agent AI Systems

·         KRR in Hybrid AI Systems for Health and Other Application Domains

·         Human-Centric Multimodal AI

·         Human-AI Interaction and Human-in-the-loop

·         Knowledge Representation in World Model

·         Federated and Privacy-Preserving Learning in Hybrid AI

·         Evaluation, Interpretability, and Trustworthy AI

Paper Submission & Review Process

Authors should submit papers electronically in PDF format to Easychair. Please use CEURART style formatting to write single column papers to be published with CEUR-WS.

Paper Types:

·         Regular Paper: 10-12 pages (excluding references)

·         Short Paper: 5–9 pages (excluding references)

·         Abstract/Extended Abstract: Title, author, and abstract only

·         Poster Paper:A title, author and a very short text (less than 5 “standard” CEUR-WS pages). Poster papers will mostly be handled like an abstract.

All submissions will be peer-reviewed through a double-blind process. Papers should be anonymized and written in English. Submissions of regular and short papers should be original work without substantial overlap with pre-published papers. For further details, please see the submission guidelines.

Accepted submissions shall be submitted to CEUR-WS.org for online publication in CEUR Workshop Proceedings (Scopus indexed). Contributions will be presented either as oral presentations (lightning talks) or posters.

Thanks,
Shreya

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Thanks and Regards, 

Shreya Banerjee, Ph.d.

Assistant Professor of Computer Science

University of New Orleans