Nicholas Roy

2.4k total citations · 1 hit paper
36 papers, 1.4k citations indexed

About

Nicholas Roy is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Aerospace Engineering. According to data from OpenAlex, Nicholas Roy has authored 36 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 18 papers in Computer Vision and Pattern Recognition and 10 papers in Aerospace Engineering. Recurrent topics in Nicholas Roy's work include Robotics and Sensor-Based Localization (10 papers), Robotic Path Planning Algorithms (8 papers) and Reinforcement Learning in Robotics (8 papers). Nicholas Roy is often cited by papers focused on Robotics and Sensor-Based Localization (10 papers), Robotic Path Planning Algorithms (8 papers) and Reinforcement Learning in Robotics (8 papers). Nicholas Roy collaborates with scholars based in United States, United Kingdom and Canada. Nicholas Roy's co-authors include Andrew McCallum, Thomas Kollar, Sebastian Thrun, Geoffrey J. Gordon, Emma Brunskill, Abraham Bachrach, Adam Bry, Charles Richter, Finale Doshi‐Velez and Kyel Ok and has published in prestigious journals such as Advanced Materials, IEEE Transactions on Pattern Analysis and Machine Intelligence and The International Journal of Robotics Research.

In The Last Decade

Nicholas Roy

36 papers receiving 1.3k citations

Hit Papers

Toward Optimal Active Learning through Sampling Estimatio... 2001 2026 2009 2017 2001 100 200 300 400 500
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.

  1. Toward Optimal Active Learning through Sampling Estimation of Error Reduction
    2001 566 citations Nicholas Roy, Andrew McCallum International Conference on Machine Learning profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Nicholas Roy United States 15 834 506 357 187 142 36 1.4k
Stéphane Ross United States 12 620 0.7× 367 0.7× 212 0.6× 194 1.0× 126 0.9× 17 1.0k
Hanna Kurniawati Australia 14 504 0.6× 714 1.4× 426 1.2× 315 1.7× 192 1.4× 38 1.3k
Haobin Shi China 18 371 0.4× 433 0.9× 193 0.5× 227 1.2× 138 1.0× 91 1.0k
Adi Botea Ireland 19 758 0.9× 612 1.2× 122 0.3× 149 0.8× 359 2.5× 79 1.3k
Xudong Zhang China 20 541 0.6× 463 0.9× 523 1.5× 85 0.5× 230 1.6× 106 1.6k
Aleksandra Faust United States 17 359 0.4× 440 0.9× 299 0.8× 316 1.7× 158 1.1× 44 992
Alexei Makarenko Australia 15 456 0.5× 570 1.1× 611 1.7× 210 1.1× 356 2.5× 32 1.2k
Guanzheng Tan China 15 344 0.4× 309 0.6× 110 0.3× 177 0.9× 117 0.8× 87 952
Ching‐Chang Wong Taiwan 20 510 0.6× 297 0.6× 142 0.4× 643 3.4× 78 0.5× 120 1.3k
Gang Hu China 19 605 0.7× 303 0.6× 91 0.3× 185 1.0× 126 0.9× 130 1.5k

Countries citing papers authored by Nicholas Roy

Since Specialization
Citations

This map shows the geographic impact of Nicholas Roy'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 Nicholas Roy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas Roy more than expected).

Fields of papers citing papers by Nicholas Roy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nicholas Roy. 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 Nicholas Roy. The network helps show where Nicholas Roy may publish in the future.

Co-authorship network of co-authors of Nicholas Roy

This figure shows the co-authorship network connecting the top 25 collaborators of Nicholas Roy. A scholar is included among the top collaborators of Nicholas Roy 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 Nicholas Roy. Nicholas Roy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Domeshek, Maya, Dallas Burtraw, Karen Palmer, Nicholas Roy, & Jhih‐Shyang Shih. (2024). Leveraging the Inflation Reduction Act to Achieve 80x30 in the US Electricity Sector. Economics of Energy and Environmental Policy. 13(2). 1 indexed citations
2.
Roy, Nicholas, et al.. (2024). Generating Sparse Probabilistic Graphs for Efficient Planning in Uncertain Environments. 133–139. 1 indexed citations
3.
4.
Joseph, Joshua, et al.. (2021). Deep Learning Unlocks X‐ray Microtomography Segmentation of Multiclass Microdamage in Heterogeneous Materials. Advanced Materials. 34(11). e2107817–e2107817. 23 indexed citations
5.
6.
Liu, Katherine, Kyel Ok, & Nicholas Roy. (2021). VoluMon: Weakly-Supervised Volumetric Monocular Estimation with Ellipsoid Representations. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 5686–5693. 1 indexed citations
7.
Roy, Nicholas, et al.. (2021). Toward Robust and Efficient Online Adaptation for Deep Stereo Depth Estimation. 12192–12198. 1 indexed citations
8.
9.
Noseworthy, Michael D., Rohan Paul, Subhro Roy, Daehyung Park, & Nicholas Roy. (2019). Task-Conditioned Variational Autoencoders for Learning Movement Primitives. 933–944. 4 indexed citations
10.
Park, Daehyung, Michael D. Noseworthy, Rohan Paul, Subhro Roy, & Nicholas Roy. (2019). Inferring Task Goals and Constraints using Bayesian Nonparametric Inverse Reinforcement Learning. 1005–1014. 4 indexed citations
11.
Stein, G., et al.. (2018). Learning over Subgoals for Efficient Navigation of Structured, Unknown Environments.. 213–222. 11 indexed citations
12.
Roy, Nicholas, et al.. (2018). Efficient Planning for Near-Optimal Compliant Manipulation Leveraging Environmental Contact. 215–222. 13 indexed citations
13.
Doshi‐Velez, Finale, David Pfau, Frank Wood, & Nicholas Roy. (2015). Bayesian Nonparametric Methods for Partially-Observable Reinforcement Learning. DSpace@MIT (Massachusetts Institute of Technology). 6 indexed citations
14.
Doniec, Marek, et al.. (2014). Nonparametric Bayesian inference on multivariate exponential families. DSpace@MIT (Massachusetts Institute of Technology). 27. 2546–2554. 20 indexed citations
15.
Kelly, Jonathan, Nicholas Roy, & Gaurav S. Sukhatme. (2014). Determining the Time Delay Between Inertial and Visual Sensor Measurements. IEEE Transactions on Robotics. 30(6). 1514–1523. 26 indexed citations
16.
Geramifard, Alborz, Joshua Redding, James Joseph, Nicholas Roy, & Jonathan P. How. (2012). Model estimation within planning and learning. 793–799. 2 indexed citations
17.
Doshi‐Velez, Finale, David Wingate, Nicholas Roy, & Joshua B. Tenenbaum. (2010). Nonparametric Bayesian Policy Priors for Reinforcement Learning. DSpace@MIT (Massachusetts Institute of Technology). 23. 532–540. 18 indexed citations
18.
Kollar, Thomas & Nicholas Roy. (2009). Utilizing object-object and object-scene context when planning to find things. 2168–2173. 77 indexed citations
19.
Brunskill, Emma, Leslie Pack Kaelbling, Tomás Lozano‐Pérez, & Nicholas Roy. (2008). Continuous-State POMDPs with Hybrid Dynamics. 25 indexed citations
20.
Roy, Nicholas & Andrew McCallum. (2001). Toward Optimal Active Learning through Sampling Estimation of Error Reduction. International Conference on Machine Learning. 441–448. 566 indexed citations breakdown →

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Stéphane Ross Breakdown of academic impact, for papers by Hanna Kurniawati Breakdown of academic impact, for papers by Haobin Shi Breakdown of academic impact, for papers by Adi Botea Breakdown of academic impact, for papers by Xudong Zhang Breakdown of academic impact, for papers by Aleksandra Faust Breakdown of academic impact, for papers by Alexei Makarenko Breakdown of academic impact, for papers by Guanzheng Tan Breakdown of academic impact, for papers by Ching‐Chang Wong Breakdown of academic impact, for papers by Gang Hu
Rankless by CCL
2026