Hybrid Conferencee

International Conference on Human-Computer Interaction with Machine Learning (ICHCIML - 26)

14th - 15th November 2026 | Boston, USA

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Call for Papers Extended:
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Certificate of Presentation:
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Abstract Submissions Open:
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Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Boston conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Boston, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in Boston."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Conference Session Tracks

SDG Wheel

Aligned with

UN Sustainable Development Goals

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.

SDG 3
SDG 3 Good Health and Well-being
SDG 4
SDG 4 Quality Education
SDG 9
SDG 9 Industry, Innovation and Infrastructure
Track 01

User Behavior Modeling in HCI

This track focuses on the methodologies and techniques for modeling user behavior in human-computer interaction. Contributions that explore predictive analytics and user profiling to enhance user experience are particularly encouraged.

Track 02

Adaptive Interfaces and Personalization

This session examines the design and implementation of adaptive interfaces that respond to user needs and preferences. Papers that discuss personalized user experiences through machine learning techniques are welcome.

Track 03

Gesture Recognition and Interaction Techniques

This track investigates the advancements in gesture recognition technologies and their applications in HCI. Submissions should address novel interaction techniques that leverage gesture-based inputs for improved user engagement.

Track 04

Eye-Tracking Analysis in User Experience

This session explores the use of eye-tracking technology to analyze user interactions and experiences. Contributions that utilize eye-tracking data to inform design decisions and enhance usability are encouraged.

Track 05

Cognitive Modeling for Human-Centered AI

This track delves into cognitive modeling approaches that inform the development of human-centered AI systems. Papers should focus on how cognitive insights can enhance interaction design and user satisfaction.

Track 06

Anomaly Detection in User Interactions

This session addresses the challenges and solutions related to anomaly detection in user interactions with systems. Submissions that propose innovative methods for identifying and addressing unexpected user behaviors are invited.

Track 07

Feature Extraction Techniques in HCI

This track focuses on the development and application of feature extraction techniques for analyzing user interactions. Contributions that highlight the role of feature selection in improving machine learning models for HCI are welcome.

Track 08

Interaction Optimization through Machine Learning

This session investigates the use of machine learning algorithms to optimize user interactions with technology. Papers that present empirical studies or theoretical frameworks for interaction optimization are encouraged.

Track 09

AI-Assisted HCI: Challenges and Opportunities

This track explores the integration of AI technologies in enhancing human-computer interaction. Contributions that discuss the implications, challenges, and opportunities presented by AI-assisted interfaces are invited.

Track 10

Sensor-Based HCI: Innovations and Applications

This session focuses on the use of sensor technologies in human-computer interaction. Papers that explore innovative applications and the implications of sensor data for user experience design are encouraged.

Track 11

Deep Learning Applications in HCI

This track examines the application of deep learning techniques in the field of human-computer interaction. Contributions that demonstrate the effectiveness of deep learning for enhancing user experience and interaction design are welcome.