Kee-Eung Kim
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Cognitive Neuroscience top 10%
- Computer Networks and Communications top 10%
- Control and Systems Engineering top 10%
- Co-authors
- Nicolas MeuleauLeslie Pack KaelblingLeonid PeshkinThomas DeanYurong LiXiaohui LiuNianyin ZengHong Zhang
- Topics
- Reinforcement Learning in Robotics (23 papers)Speech and dialogue systems (10 papers)Topic Modeling (10 papers)
- Partner nations
- South KoreaUnited StatesCanada
In The Last Decade
Kee-Eung Kim
59 papers receiving 890 citations
Peers
Comparison fields: 5 of 110
- Artificial Intelligence 565
- Computer Vision and Pattern Recognition 144
- Cognitive Neuroscience 115
- Computer Networks and Communications 110
- Control and Systems Engineering 107
Countries citing papers authored by Kee-Eung Kim
This map shows the geographic impact of Kee-Eung Kim'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 Kee-Eung Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kee-Eung Kim more than expected).
Fields of papers citing papers by Kee-Eung Kim
This network shows the impact of papers produced by Kee-Eung Kim. 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 Kee-Eung Kim. The network helps show where Kee-Eung Kim may publish in the future.
Co-authorship network of co-authors of Kee-Eung Kim
This figure shows the co-authorship network connecting the top 25 collaborators of Kee-Eung Kim. A scholar is included among the top collaborators of Kee-Eung Kim 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 Kee-Eung Kim. Kee-Eung Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | Multi-View Representation Learning via Total Correlation Objective | 4 |
| 4 | 7 | |
| 5 | Monte-Carlo Tree Search for Constrained POMDPs | 17 |
| 6 | A Bayesian Approach to Generative Adversarial Imitation Learning | 7 |
| 7 | An Inverse Reinforcement Learning Approach to Car Following Behaviors | 3 |
| 8 | Bayesian nonparametric feature construction for inverse reinforcement learning | 19 |
| 9 | A POMDP Framework for Dynamic Task Allocation and Reconnaissance of Multiple Unmanned Aerial Vehicles | 2 |
| 10 | 2 | |
| 11 | Inverse Reinforcement Learning in Partially Observable Environments | 27 |
| 12 | Exploiting symmetries in POMDPs for point-based algorithms | 9 |
| 13 | Symbolic heuristic search value iteration for factored POMDPs | 9 |
| 14 | Signboard Recognition by Consistency Checking of Local Features | 0 |
| 15 | Hand grip pattern recognition for mobile user interfaces | 53 |
| 16 | Solving factored MDPs via non-homogeneous partitioning | 3 |
| 17 | Off-Policy Policy Search | 5 |
| 18 | 6 | |
| 19 | Solving very large weakly coupled Markov decision processes | 126 |
| 20 | Solving stochastic planning problems with large state and action spaces | 10 |
About Kee-Eung Kim
Kee-Eung Kim is a scholar working on Artificial Intelligence, Human-Computer Interaction and Management Science and Operations Research, having authored 63 papers that have together received 941 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (23 papers), Speech and dialogue systems (10 papers) and Topic Modeling (10 papers). The work is most often cited by research in Artificial Intelligence (565 citations), Human-Computer Interaction (67 citations) and Computer Vision and Pattern Recognition (144 citations). Kee-Eung Kim has collaborated with scholars based in South Korea, United States and Canada. Frequent co-authors include Nicolas Meuleau, Leslie Pack Kaelbling, Leonid Peshkin, Thomas Dean, Yurong Li, Xiaohui Liu, Nianyin Zeng, Hong Zhang, Zidong Wang and Pascal Poupart. Their work appears in journals such as Artificial Intelligence, IEEE Transactions on Cybernetics and Machine Learning.
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.