Neuroinformatics and machine learning are driving significant advancements in brain research, combining tools and approaches from computer science, mathematics, and neuroscience to analyze, model, and interpret complex neural data and mechanisms. As these interdisciplinary fields continue to evolve, it is crucial to recognize the invaluable contributions of women scientists who have championed innovation and diversity in neuroinformatics and neuroscience-centered machine learning.Despite their critical roles, women remain underrepresented in these fields, making up less than 30% of researchers globally. Deep-rooted biases and gender stereotypes continue to discourage girls and women from entering and advancing in science, technology, engineering, and mathematics (STEM) research—including neuroinformatics, machine learning, and neuroscience. Yet, UNESCO highlights that promoting science and gender equality is essential for sustainable development. Given how instrumental women researchers have been in shaping scientific progress, and given how underrecognized their work is, it is imperative to promote gender equality, challenge stereotypes, and inspire more women and girls to pursue and flourish in STEM fields.In this context, Frontiers in Neuroinformatics presents the Research Topic "Women Pioneering Neuroinformatics and Neuroscience-Related Machine Learning", a collection that aims to reduce gender bias, reinforce diversity, and celebrate the achievements of women researchers within all areas of neuroinformatics and the application of machine learning in neuroscience. We invite the submission of original research articles, case studies, and review articles covering recent discoveries and advances contributed by women researchers or research teams with gender balance. Manuscripts addressing perspectives on gender equality, diversity, and the impact of women in neuroinformatics and neuroscience-specific machine learning are highly encouraged.Submissions where the lead and/or corresponding author is female are strongly encouraged. However, in the spirit of inclusivity, we welcome all manuscripts that fall within the defined scope, regardless of the gender of the authors.
Neuroinformatics and machine learning are driving significant advancements in brain research, combining tools and approaches from computer science, mathematics, and neuroscience to analyze, model, and interpret complex neural data and mechanisms. As these interdisciplinary fields continue to evolve, it is crucial to recognize the invaluable contributions of women scientists who have championed innovation and diversity in neuroinformatics and neuroscience-centered machine learning.Despite their critical roles, women remain underrepresented in these fields, making up less than 30% of researchers globally. Deep-rooted biases and gender stereotypes continue to discourage girls and women from entering and advancing in science, technology, engineering, and mathematics (STEM) research—including neuroinformatics, machine learning, and neuroscience. Yet, UNESCO highlights that promoting science and gender equality is essential for sustainable development. Given how instrumental women researchers have been in shaping scientific progress, and given how underrecognized their work is, it is imperative to promote gender equality, challenge stereotypes, and inspire more women and girls to pursue and flourish in STEM fields.In this context, Frontiers in Neuroinformatics presents the Research Topic "Women Pioneering Neuroinformatics and Neuroscience-Related Machine Learning", a collection that aims to reduce gender bias, reinforce diversity, and celebrate the achievements of women researchers within all areas of neuroinformatics and the application of machine learning in neuroscience. We invite the submission of original research articles, case studies, and review articles covering recent discoveries and advances contributed by women researchers or research teams with gender balance. Manuscripts addressing perspectives on gender equality, diversity, and the impact of women in neuroinformatics and neuroscience-specific machine learning are highly encouraged.Submissions where the lead and/or corresponding author is female are strongly encouraged. However, in the spirit of inclusivity, we welcome all manuscripts that fall within the defined scope, regardless of the gender of the authors.