Sufola Das Chagas
Papers
1
Total Citations
2
H-Index
1
About
Sufola Das Chagas is a researcher at the forefront of sustainable technology, specializing in the intersection of embedded machine learning, robotics, and environmental engineering. Her work addresses critical challenges in waste management, particularly for technologically underdeveloped regions. Her most-cited paper, "Robotic Recyclables Segregation System using TinyML" (2024, 2 citations), introduces a cost-effective, low-power solution that leverages TinyML to enable robotic arms to identify and sort recyclable materials in real time. This innovation directly tackles the global waste crisis by offering an affordable alternative to expensive, high-maintenance recycling infrastructure. Beyond this flagship work, Chagas explores how edge AI can democratize automation, making smart recycling accessible where it is needed most. Her research has been recognized for its potential to bridge the gap between advanced robotics and practical, scalable environmental solutions. With a growing citation footprint, Chagas is establishing herself as a key voice in sustainable automation, inspiring students and researchers to harness AI for tangible, real-world impact.
Research Focus
Key Achievements
Top Papers
- 1Robotic Recyclables Segregation System using TinyML2 citations · 2024