Deena Francis

Deena Francis is an Assistant Professor at the Department of Engineering Technology and Didactics within the Energy Technology and Computer Science school at the Technical University of Denmark (DTU). Her research focuses on digital twins, machine learning applications in smart manufacturing and precision livestock farming, and sensor technology for chemical detection. She leads and participates in high-impact projects such as SEAL (Seabed Environmental Analyzer for Methane Leakage) and Machine Learning for Beehives Monitoring, addressing environmental and agricultural sustainability challenges.

Key research areas include reinforcement learning for digital twin systems, dimensionality reduction techniques, and data-driven decision support in agriculture. Her work bridges theoretical advancements in kernel methods and explicit feature maps with practical applications in manufacturing optimization and environmental sensing. Francis has collaborated internationally and contributed to over 15 peer-reviewed publications, with a focus on smart systems and sensor-based solutions.

• Education: Not explicitly stated in the text.
• Labs/Teams: Involved in the InnoTech TaskForce, focusing on green transition technologies and data-driven innovation.

Her advisory role includes supervising PhD student S. Gopalakrishnan on metal-organic framework arrays for liquid-phase sensing. Francis’s projects often emphasize interdisciplinary collaboration, combining engineering, computer science, and environmental science to address global challenges.