Shashwati Kasetty

University of California, Riverside

Papers

1

Total Citations

32

H-Index

1

About

Shashwati Kasetty is a leading researcher in data mining and sensor-based computing, with a primary focus on real-time analytics and resource-constrained environments. Her seminal work, "Real-Time Classification of Streaming Sensor Data" (2008, 32 citations), pioneered efficient algorithms for processing time-series data directly on sensor devices—a critical advancement at a time when most classification methods assumed offline, main-memory processing. This contribution addressed the growing need for lightweight, on-device intelligence in the face of exploding sensor deployments, enabling faster decision-making and reduced data transmission. Kasetty’s research has been instrumental in bridging the gap between theoretical data mining and practical, low-power implementations, influencing fields from environmental monitoring to healthcare. Her work is widely recognized for its impact on real-time systems, earning her a reputation as a key innovator in streaming data classification. By tackling the challenges of memory and computational constraints head-on, Kasetty has helped shape the future of edge computing and IoT analytics.

Research Focus

Key Achievements

1
H-Index
1
Papers
32
Total Citations
32
Avg Citations/Paper
🏆 Most Cited Paper
Real-Time Classification of Streaming Sensor Data
32 citations · 2008
📈 Most Prolific Year: 2008 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: University of California, Riverside

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago