Daswin De Silva
Centre International de Recherche sur le Cancer, La Trobe University
Papers
6
Total Citations
99
H-Index
5
About
Daswin De Silva is a multidisciplinary researcher whose work spans autonomous robotics, unsupervised machine learning, and applied artificial intelligence, with earlier contributions in bioinformatics and laboratory systems. His research career reflects a compelling evolution from developing robust data management infrastructure — most notably a Laboratory Information Management System (LIMS) for high-throughput genetic mutation screening (2007, 27 citations) — toward pioneering intelligent systems for autonomous robots. De Silva has made significant contributions to sensory fusion and perception in robotics, developing bio-inspired and unsupervised machine learning architectures that enable robots to meaningfully interpret complex, multimodal environments. His work on scalable fusion for active perception (2019, 23 citations) and distributed Growing Self-Organizing Maps for skill transfer learning (2021) demonstrates a consistent focus on scalable, biologically motivated approaches to robotic intelligence. Notably, he has also bridged AI with healthcare analytics, applying machine learning to patient-reported outcomes in prostate cancer treatment comparisons (2018, 21 citations), showcasing the breadth of his impact. His more recent exploration of Vector Symbolic Architectures and blockchain-based smart contracts for robotic motion intelligence signals a forward-looking research agenda addressing transparency and adaptability in AI-driven robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Unsupervised Machine Learning Based Scalable Fusion for Active Perception23 citations · 2019
- 3
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- 5Bio-Inspired Multisensory Fusion for Autonomous Robots12 citations · 2018
- 6