Mathew Monfort is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering.
According to data from OpenAlex, Mathew Monfort has authored 11 papers receiving a total of 480 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 3 papers in Control and Systems Engineering. Recurrent topics in Mathew Monfort's work include Reinforcement Learning in Robotics (4 papers), Robot Manipulation and Learning (3 papers) and Human Pose and Action Recognition (3 papers). Mathew Monfort is often cited by papers focused on Reinforcement Learning in Robotics (4 papers), Robot Manipulation and Learning (3 papers) and Human Pose and Action Recognition (3 papers). Mathew Monfort collaborates with scholars based in United States, United Kingdom and China. Mathew Monfort's co-authors include Wongun Choi, Yizhou Wang, Ying Wu, Chris Baker, Yibiao Zhao, Yifei Xu, Brian D. Ziebart, Anqi Liu, Patrick Lucey and Iain Matthews and has published in prestigious journals such as DSpace@MIT (Massachusetts Institute of Technology), International Conference on Artificial Intelligence and Statistics and Proceedings of the AAAI Conference on Artificial Intelligence.
In The Last Decade
Mathew Monfort
11 papers
receiving
456 citations
Hit Papers
What are hit papers?
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.
Multi-Agent Tensor Fusion for Contextual Trajectory Prediction
2019320 citationsYifei Xu, Mathew Monfort et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Mathew Monfort
Since
Specialization
Citations
This map shows the geographic impact of Mathew Monfort'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 Mathew Monfort with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mathew Monfort more than expected).
This network shows the impact of papers produced by Mathew Monfort. 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 Mathew Monfort. The network helps show where Mathew Monfort may publish in the future.
Co-authorship network of co-authors of Mathew Monfort
This figure shows the co-authorship network connecting the top 25 collaborators of Mathew Monfort.
A scholar is included among the top collaborators of Mathew Monfort 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 Mathew Monfort. Mathew Monfort is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Chen, Xiangli, Mathew Monfort, Anqi Liu, & Brian D. Ziebart. (2016). Robust Covariate Shift Regression. International Conference on Artificial Intelligence and Statistics. 1270–1279.13 indexed citations
8.
Monfort, Mathew, Brenden M. Lake, Brian D. Ziebart, Patrick Lucey, & Joshua B. Tenenbaum. (2015). Softstar: heuristic-guided probabilistic inference. DSpace@MIT (Massachusetts Institute of Technology). 28. 2764–2772.3 indexed citations
9.
Lucey, Patrick, Alina Bialkowski, Mathew Monfort, Peter Carr, & Iain Matthews. (2015). "Quality vs Quantity": Improved Shot Prediction in Soccer using Strategic Features from Spatiotemporal Data. Queensland's institutional digital repository (The University of Queensland).55 indexed citations
10.
Byravan, Arunkumar, Mathew Monfort, Brian D. Ziebart, Byron Boots, & Dieter Fox. (2015). Graph-based inverse optimal control for robot manipulation. 1874–1890.13 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.