Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Randomized Kinodynamic Motion Planning with Moving Obstacles
2002540 citationsDavid Hsu et al.The International Journal of Robotics Researchprofile →
OpenComet: An automated tool for comet assay image analysis
2014501 citationsP. S. Thiagarajan, David Hsu et al.profile →
This map shows the geographic impact of David Hsu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Hsu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Hsu more than expected).
This network shows the impact of papers produced by David Hsu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Hsu. The network helps show where David Hsu may publish in the future.
Co-authorship network of co-authors of David Hsu
This figure shows the co-authorship network connecting the top 25 collaborators of David Hsu.
A scholar is included among the top collaborators of David Hsu based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with David Hsu. David Hsu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Hsu, David, et al.. (2018). Particle Filter Networks: End-to-End Probabilistic Localization From Visual Observations.. arXiv (Cornell University).3 indexed citations
6.
Gao, Wei, et al.. (2017). Intention-Net: Integrating Planning and Deep Learning for Goal-Directed Autonomous Navigation. 185–194.8 indexed citations
7.
Lim, Zhan Wei, David Hsu, & Wee Sun Lee. (2017). Shortest Path under Uncertainty: Exploration versus Exploitation.. Uncertainty in Artificial Intelligence.6 indexed citations
Lim, Zhan Wei, David Hsu, & Wee Sun Lee. (2015). Adaptive stochastic optimization: from sets to paths. Neural Information Processing Systems. 28. 1585–1593.3 indexed citations
10.
Zhang, Zongzhang, David Hsu, & Wee Sun Lee. (2014). Covering Number for Efficient Heuristic-based POMDP Planning. International Conference on Machine Learning. 28–36.11 indexed citations
11.
Ye, Nan, et al.. (2013). DESPOT: Online POMDP Planning with Regularization. National University of Singapore. 26. 1772–1780.142 indexed citations
Hsu, David, et al.. (2007). Accelerating point-based POMDP algorithms through successive approximations of the optimal reachable space.3 indexed citations
Hsu, David & David S. L. Wei. (1995). Permutation Routing and Sorting on Directed de Bruijn Networks.. Proceedings of the International Conference on Parallel Processing. 96–100.3 indexed citations
20.
Alt, Helmut, David Hsu, & Jack Snoeyink. (1994). Computing the largest inscribed isothetic rectangle. Canadian Conference on Computational Geometry. 67–72.16 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.