David Ha
Impact in
- Artificial Intelligence top 10%
- Reinforcement Learning in Robotics
- Evolutionary Algorithms and Applications
- Explainable Artificial Intelligence (XAI)
Papers in
-
- Evolutionary Algorithms and Applications 5
- Reinforcement Learning in Robotics 5
- Domain Adaptation and Few-Shot Learning 2
- Natural Language Processing Techniques 1
- Neural Networks and Applications 1
-
- Image Processing and 3D Reconstruction 1
- Co-authors
- Yujin Tang (2 shared papers)Ruben Villegas (1 shared paper)Honglak Lee (1 shared paper)James Davidson (1 shared paper)Timothy Lillicrap (1 shared paper)Danijar Hafner (1 shared paper)Ian Fischer (1 shared paper)Monica Dinculescu (1 shared paper)
- Journals
- Nano Energy (1 paper)ChemSusChem (1 paper)Nature Machine Intelligence (1 paper)Proceedings of the Genetic and Evolutionary Computation Conference Companion (3 papers)Proceedings of the Genetic and Evolutionary Computation Conference (1 paper)
- Partner nations
- United StatesSouth KoreaGermany
In The Last Decade
David Ha
16 papers receiving 217 citations
Peers
Comparison fields: 5 of 64
- Artificial Intelligence 121
- Human-Computer Interaction 17
- Computer Vision and Pattern Recognition 61
- Computer Graphics and Computer-Aided Design 8
- Control and Systems Engineering 42
Countries citing papers authored by David Ha
This map shows the geographic impact of David Ha'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 Ha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Ha more than expected).
Fields of papers citing papers by David Ha
This network shows the impact of papers produced by David Ha. 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 Ha. The network helps show where David Ha may publish in the future.
Co-authors
The 25 scholars most cited alongside David Ha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 99 | |
| 2 | 2022 | 40 | |
| 3 | 2019 | 36 | |
| 4 | 2022 | 17 | |
| 5 | 2022 | 12 | |
| 6 | 2016 | 6 | |
| 7 | 2025 | 5 | |
| 8 | 2020 | 5 | |
| 9 | Enforced Subpopulations (ESP) neuroevolution algorithm for balancing inverted double pendulum | 2015 | 3 |
| 10 | Learning via social awareness: improving sketch representations with facial feedback | 2018 | 2 |
| 11 | 2025 | 2 | |
| 12 | 2018 | 2 | |
| 13 | Learning to Predict Without Looking Ahead: World Models Without Forward Prediction | 2019 | 1 |
| 14 | 2025 | 1 | |
| 15 | 2019 | 1 | |
| 16 | 2020 | 1 | |
| 17 | detecting device orientation | 2014 | 1 |
About David Ha
David Ha is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Mechanical Engineering, Electrical and Electronic Engineering and Cognitive Neuroscience, having authored 17 papers that have together received 234 indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (5 papers), Reinforcement Learning in Robotics (5 papers), Modular Robots and Swarm Intelligence (4 papers), Domain Adaptation and Few-Shot Learning (2 papers), Natural Language Processing Techniques (1 paper), Image Processing and 3D Reconstruction (1 paper), Transition Metal Oxide Nanomaterials (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Artificial Intelligence (121 citations), Human-Computer Interaction (17 citations), Computer Vision and Pattern Recognition (61 citations), Computer Graphics and Computer-Aided Design (8 citations) and Control and Systems Engineering (42 citations). David Ha has collaborated with scholars based in United States, South Korea and Germany. Frequent co-authors include Yujin Tang, Ruben Villegas, Honglak Lee, James Davidson, Timothy Lillicrap, Danijar Hafner, Ian Fischer, Monica Dinculescu, Judith E. Fan and Yujin Tang. Their work appears in journals such as Nano Energy, ChemSusChem, Nature Machine Intelligence, Proceedings of the Genetic and Evolutionary Computation Conference Companion and Proceedings of the Genetic and Evolutionary Computation Conference.
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.