Papers
11
Total Citations
272
H-Index
8
About
Dan Feldman is a leading researcher in robotics, machine learning, and computational geometry, best known for pioneering the theory and application of **coresets**—compact data summaries that enable efficient approximation of large-scale optimization problems. His major contributions include developing coreset-based methods for clustering, motion prediction, and visual summarization, which have become foundational in handling streaming and high-dimensional data. His highly cited work, "Core-Sets: Updated Survey" (2019, over 80 combined citations), provides a comprehensive framework that has influenced fields from sensor networks to autonomous systems. Feldman’s research on trajectory clustering for motion prediction (2012, 70 citations) introduced data-driven robotic path planning, learning repeated motion patterns to improve interception tasks. He also advanced robotic perception with coreset-based visual precis generation and loop closure (2014–2015, 50+ citations), enabling efficient video stream summarization for mobile robots. Notably, his work on communication coverage for independently moving robots (2012, 20 citations) and real-time quadcopter tracking via shape fitting (2017, 13 citations) demonstrates practical impact in multi-robot systems. With over 250 total citations, Feldman’s provable approximation algorithms continue to shape efficient, scalable solutions in robotics and data science.
Research Focus
Key Achievements
Top Papers
- 1Trajectory clustering for motion prediction70 citations · 2012
- 2Core-Sets: Updated Survey51 citations · 2019
- 3Core‐sets: An updated survey32 citations · 2019
- 4Visual precis generation using coresets26 citations · 2014
- 5Coresets for visual summarization with applications to loop closure24 citations · 2015
- 6Introduction to Core-sets: an Updated Survey21 citations · 2020
- 7Communication coverage for independently moving robots20 citations · 2012
- 8Quadcopter Tracks Quadcopter via Real-Time Shape Fitting13 citations · 2017
- 9Position Estimation of Moving Objects: Practical Provable Approximation7 citations · 2019
- 10K-robots clustering of moving sensors using coresets6 citations · 2013