Aim and Scope

The development of computational methods specifically designed for mental health and well-being is critical to addressing global societal challenges, as these technologies have the potential to support prevention, assessment, and intervention at scale, while ensuring an ethical, responsible, and transformative impact on individual and collective outcomes. These methods could provide insights into the understanding, diagnosis, and monitoring of mental health conditions by delivering personalized and cost-effective solutions to improve health outcomes and quality of care, while enabling early intervention, real-time support, and long-term well-being. They could analyze and integrate data from brain activity, behavior, and symptom patterns to elucidate underlying mechanisms of psychological responses, as well as potential neuropsychiatric pathways and trajectories of care for mental disorders. However, the adoption of computational models in this specific context raises several challenges that must be addressed, ranging from the need for high-quality datasets, which require continuous interplay among researchers from different disciplines, to the design of systems that protect user privacy, ensure equity, and prevent algorithmic bias in sensitive mental health applications, to name a few. In this context, the Special Session on “Computational Methods for Mental Health and Well-Being” aims to foster cross-disciplinary exchange among computer science, psychology, mental healthcare, and ethics. It reflects the growing importance of technology in improving mental well-being and seeks to stimulate collaborative discussions focused on integrating computational methods into healthcare systems, identifying gaps in research and applications, and critically examining the opportunities and risks associated with the adoption of technologies for managing highly sensitive data.

Topics of Interest

• Computational models and statistical methods for early detection of mental health issues;
• Computational tools for continuous and longitudinal monitoring;
• Computational models for personalized and adaptive interventions;
• Computational models and statistical approaches for disease risk stratification and prognosis;
• Computational models for multimodal data analysis;
• Computational models for emotion recognition and affective computing;
• Digital phenotyping for mental health and well-being;
• Explainable and interpretable computational models for mental health applications;
• Bias, fairness, and equity in AI and statistical modeling for mental health and well-being;
• Privacy-preserving and secure AI methods for sensitive mental health data;
• Ethical, legal, and societal implications of computational mental health technologies;
• Integration and validation of computational methods in real-world clinical settings.

Target Audience

The Special Session is primarily addressed to researchers and practitioners working at the intersection of computational sciences and mental health. It welcomes contributions from computer scientists, data scientists, bioinformaticians, psychologists, psychiatrists, mental health professionals, and healthcare stakeholders interested in the development, validation, and ethical deployment of data-driven approaches for mental well-being. The session is also relevant to experts in digital health, biomedical engineering, and AI ethics who aim to address challenges related to data quality, privacy, fairness, and responsible innovation in sensitive healthcare contexts. By bringing together diverse perspectives, the session seeks to engage a multidisciplinary community committed to advancing rigorous, ethical, and impactful computational solutions for mental health.

Submissions

The Special Session invites the submission of original short papers (4–6 pages) presenting research contributions within the scope of computational intelligence methods applied to mental health and well-being. All submissions will undergo a double-blind peer review process. Submission link: Easychair.

Authors must prepare their manuscript according to the following requirements:

• Papers must be 4-6 pages in length;
• Manuscripts must be prepared using one of the official CIBB 2026 templates;
• Submissions must be uploaded in PDF format via the EasyChair platform;
• The review process is double-blind. Authors must ensure that the submitted manuscript does not contain names, affiliations, acknowledgements, self-identifying references, or any other information that could reveal the authors' identities.

The following templates are available for manuscript preparation:

• Word template
• LaTeX template
• Overleaf template
• LibreOffice template

Publication Opportunities

Authors of accepted short papers will be invited to submit extended versions of their contributions to the Lecture Notes in Bioinformatics (LNBI) series by Springer or to high-impact journals in the areas represented at CIBB. Further details about partner journals will be announced on the conference website.

Important Dates

• Submission deadline: May 3rd, 2026
• Acceptance notification: June 15th, 2026
• Camera-ready deadline: July 7th, 2026

Special Session Chairs

For further information, please do not hesitate to contact the Special Session Chairs:

• Stefania Coelli, Polytechnic University of Milan, Milan, Italy
• Marco Viviani, University of Milano-Bicocca, Milan, Italy

Other Session Organizers

• Anna Maria Bianchi, Polytechnic University of Milan, Milan, Italy
• Cristina Crocamo, University of Milano-Bicocca, Milan, Italy
• Francesca Gasparini, University of Milano-Bicocca, Milan, Italy