Piyush Bagad
Papers
1
Total Citations
3
H-Index
1
About
Piyush Bagad’s research sits at the compelling intersection of physics, perception, and machine learning, with a particular focus on inferring hidden physical properties from sensory data. His most-cited work, “The Sound of Water: Inferring Physical Properties from Pouring Liquids” (2025), exemplifies this approach by demonstrating how audio alone can reveal the liquid level, container shape, and pouring dynamics—transforming a mundane everyday sound into a rich source of physical insight. Though early in its citation trajectory, this paper has already sparked interest for its novel framing of physics-informed audio analysis. Bagad’s contributions push beyond traditional computer vision, showing how machines can “hear” the physical world. His work is notable for bridging intuitive human experience with rigorous computational modeling, offering a fresh perspective on how AI can learn from multimodal, real-world phenomena. For students and researchers, Bagad’s research is a compelling example of how everyday actions can become powerful testbeds for understanding physical inference through sound.
Research Focus
Key Achievements
Top Papers
- 1The Sound of Water: Inferring Physical Properties from Pouring Liquids3 citations · 2025