Daehyung Park

669 total citations
26 papers, 329 citations indexed

About

Daehyung Park is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Daehyung Park has authored 26 papers receiving a total of 329 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 15 papers in Artificial Intelligence and 11 papers in Control and Systems Engineering. Recurrent topics in Daehyung Park's work include Robot Manipulation and Learning (10 papers), Robotic Path Planning Algorithms (8 papers) and Topic Modeling (6 papers). Daehyung Park is often cited by papers focused on Robot Manipulation and Learning (10 papers), Robotic Path Planning Algorithms (8 papers) and Topic Modeling (6 papers). Daehyung Park collaborates with scholars based in United States, South Korea and India. Daehyung Park's co-authors include Charles C. Kemp, Zackory Erickson, Tapomayukh Bhattacharjee, Hokeun Kim, Ariel Kapusta, Rohan Paul, Subhro Roy, Nicholas Roy, Dohyun Kim and Nicholas Roy and has published in prestigious journals such as PLoS ONE, The International Journal of Robotics Research and Autonomous Robots.

In The Last Decade

Daehyung Park

24 papers receiving 319 citations

Peers

Daehyung Park

CSE

CVPR

CNC

Felix Duvallet United States

Yoichiro Maeda Japan

Ruffin White United States

Adrian Li United States

Daniel H. Grollman United States

Ing-Jr Ding Taiwan

Jacob Crossman United States

Haris Baltzakis Greece

Thomas M. Howard United States

Tijn van der Zant Netherlands

Felix Duvallet United States

Daehyung Park

117 ×0.7

95 ×0.6

CSE

113 ×1.1

CVPR

23 ×0.5

29 ×0.8

CNC

Citations per year, relative to Daehyung Park Daehyung Park (= 1×) peers Felix Duvallet

Countries citing papers authored by Daehyung Park

Since Specialization

Citations

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

Fields of papers citing papers by Daehyung Park

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daehyung Park

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

All Works

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20 of 20 papers shown

Kim, Do-Hyun, et al.. (2024). LINGO-Space: Language-Conditioned Incremental Grounding for Space. Proceedings of the AAAI Conference on Artificial Intelligence. 38(9). 10314–10322. 2 indexed citations

Han, Ji, Daehyung Park, & Min Jun Kim. (2024). Constrained Nonlinear Disturbance Observer for Robotic Systems. 3526–3532. 1 indexed citations

Kim, Dohyun, et al.. (2024). A survey on integration of large language models with intelligent robots. Intelligent Service Robotics. 17(5). 1091–1107. 30 indexed citations

Park, Daehyung, et al.. (2023). Inverse Constraint Learning and Generalization by Transferable Reward Decomposition. IEEE Robotics and Automation Letters. 9(1). 279–286.

Kim, Dohyun, et al.. (2023). SGGNet²: Speech-Scene Graph Grounding Network for Speech-guided Navigation. 1 indexed citations

Park, Daehyung, et al.. (2023). Learning-based Initialization of Trajectory Optimization for Path-following Problems of Redundant Manipulators. arXiv (Cornell University). 9686–9692. 3 indexed citations

Kim, Kanghyun, Daehyung Park, & Min Jun Kim. (2023). A Reachability Tree-Based Algorithm for Robot Task and Motion Planning. 3750–3756. 2 indexed citations

Park, Daehyung, et al.. (2022). GraphDistNet: A Graph-Based Collision-Distance Estimator for Gradient-Based Trajectory Optimization. IEEE Robotics and Automation Letters. 7(4). 11118–11125. 5 indexed citations

Park, Daehyung, et al.. (2022). Confidence-Based Robot Navigation Under Sensor Occlusion with Deep Reinforcement Learning. 2022 International Conference on Robotics and Automation (ICRA). 8231–8237. 9 indexed citations

10.

Kapusta, Ariel, et al.. (2019). A system for bedside assistance that integrates a robotic bed and a mobile manipulator. PLoS ONE. 14(10). e0221854–e0221854. 16 indexed citations

11.

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

12.

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

13.

Roy, Subhro, Michael D. Noseworthy, Rohan Paul, Daehyung Park, & Nicholas Roy. (2019). Leveraging Past References for Robust Language Grounding. 6 indexed citations

14.

Nyga, Daniel, Subhro Roy, Rohan Paul, et al.. (2018). Grounding Robot Plans from Natural Language Instructions with Incomplete World Knowledge. 714–723. 15 indexed citations

15.

Park, Daehyung, Hokeun Kim, & Charles C. Kemp. (2018). Multimodal anomaly detection for assistive robots. Autonomous Robots. 43(3). 611–629. 32 indexed citations

16.

Park, Daehyung, Zackory Erickson, Tapomayukh Bhattacharjee, & Charles C. Kemp. (2016). Multimodal execution monitoring for anomaly detection during robot manipulation. SMARTech Repository (Georgia Institute of Technology). 407–414. 58 indexed citations

17.

Kapusta, Ariel, Yash Chitalia, Daehyung Park, & Charles C. Kemp. (2016). Collaboration Between a Robotic Bed and a Mobile Manipulator May Improve Physical Assistance for People with Disabilities. SMARTech Repository (Georgia Institute of Technology). 4 indexed citations

18.

Kapusta, Ariel, Daehyung Park, & Charles C. Kemp. (2015). Task-centric selection of robot and environment initial configurations for assistive tasks. 2. 1480–1487. 5 indexed citations

19.

Park, Daehyung, Ariel Kapusta, Jeffrey Hawke, & Charles C. Kemp. (2014). Interleaving planning and control for efficient haptically-guided reaching in unknown environments. 88. 809–816.

20.

Park, Daehyung, et al.. (2014). Learning to reach into the unknown: Selecting initial conditions when reaching in clutter. SMARTech Repository (Georgia Institute of Technology). 21. 630–637. 5 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.

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