Jarutas actively contributes to diverse data science projects, including MSTAC—an initiative focused on COVID-19 chest X-ray classification using stacked CNN models. She is also involved in an AI chest X-ray screening proof of concept funded by the Global Challenges Research Fund and an interactive tele-rehabilitation system for osteoarthritis patients supported by Thaicom.

Additionally, she plays a role in data analytics, monitoring flooding incidents in Hat Yai through Twitter data analysis. Furthermore, Jarutas serves on a consultancy committee for AI procedures with the Royal College of Radiologists in Thailand.

Her primary research goal is to leverage technology for healthcare enhancement, improved accessibility to advanced medical technologies, and optimized teaching and learning through AI and machine learning analysis of health and educational data.

Beyond healthcare, Jarutas extends her research interest into the education domain. She applies teaching and learning pedagogy to enhance student performance and learning processes effectively. Notably, she has publications in conferences, covering topics such as content co-creation for novice programmers, enhancing students' programming comprehension through a collaborative creation approach, and breaking barries: empowering non-stem students in data skills through inquiry-based and collaborative learning.