Special Interest Group Machine Learning

Organisation team

Machine Learning Applications


The Machine Learning Fundamentals and Applications Special Interest Group (SIG ML:FA) is dedicated to fostering a dynamic synergy between the foundational aspects of machine learning and its diverse applications across various domains. This SIG is envisioned as a collaborative platform that bridges the gap between machine learning experts and application-oriented researchers, encouraging a mutual exchange of knowledge and expertise.

Our aims:

  1. Integrate Fundamentals with Real-world Impact: Establish a comprehensive understanding of the fundamental principles of machine learning while emphasizing their practical application in solving real-world challenges across diverse domains.
  2. Cultivate a Two-way Learning Experience: Facilitate an environment where quantitative researchers become acquainted with the potential benefits of machine learning in their specific fields, and machine learning experts gain insights into the wide spectrum of applications for their expertise.
  3. Encourage Innovative Collaborations: Stimulate, facilitate, and actively participate in collaborative projects that push the boundaries of machine learning applications, with an emphasis on high-risk, high-gain endeavors. These projects aim to address novel scientific questions and contribute to advancements in both machine learning and diverse scientific domains.

Our Approach

  1. Showcasing Diversity through Speed Presentations: Organize speed presentations that highlight ongoing projects, showcasing the diverse applications of machine learning across various topics. This serves to inspire collaboration and cross-disciplinary engagement.
  2. Targeted Meetings for Specific Fields: Host meetings focused on applying machine learning to specific fields or addressing generic challenges that span multiple domains. These meetings aim to stimulate the creation of joint project proposals and foster interdisciplinary collaboration.
  3. Seed Funding for Innovation: Provide small-scale seed funding to support innovative projects that demonstrate the potential for significant contributions to scientific fields through the application of machine learning.