Tim Klinger
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Speech and dialogue systems
- Domain Adaptation and Few-Shot Learning
- Natural Language Processing Techniques
- Software top 10%
- Model-Driven Software Engineering Techniques
Papers in
-
- Reinforcement Learning in Robotics 5
- Topic Modeling 5
- Natural Language Processing Techniques 4
- Domain Adaptation and Few-Shot Learning 3
- Data Stream Mining Techniques 2
-
- Software Engineering Techniques and Practices 6
- Software Engineering Research 4
- Co-authors
- Bowen Zhou (2 shared papers)Clay E. Williams (5 shared papers)Peri L. Tarr (5 shared papers)Patrick A. Wagstrom (2 shared papers)Gerald J. Tesauro (5 shared papers)Kartik Talamadupula (3 shared papers)Iulian Vlad Serban (1 shared paper)Zhiguo Wang (1 shared paper)
- Journals
- Nature Machine Intelligence (1 paper)The Journal of Object Technology (1 paper)International Conference on Learning Representations (1 paper)arXiv (Cornell University) (1 paper)AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)) (1 paper)
- Partner nations
- United StatesIsraelChina
In The Last Decade
Tim Klinger
26 papers receiving 565 citations
Peers
Comparison fields: 5 of 42
- Artificial Intelligence 359
- Software 46
- Information Systems 211
- Health Informatics 4
- Computer Science Applications 7
Countries citing papers authored by Tim Klinger
This map shows the geographic impact of Tim Klinger'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 Tim Klinger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Klinger more than expected).
Fields of papers citing papers by Tim Klinger
This network shows the impact of papers produced by Tim Klinger. 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 Tim Klinger. The network helps show where Tim Klinger may publish in the future.
Co-authors
The 25 scholars most cited alongside Tim Klinger, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 182 | |
| 2 | 2017 | 129 | |
| 3 | 2011 | 79 | |
| 4 | 2019 | 32 | |
| 5 | 2005 | 21 | |
| 6 | 2008 | 16 | |
| 7 | 2022 | 16 | |
| 8 | 2009 | 15 | |
| 9 | 2012 | 13 | |
| 10 | 2012 | 13 | |
| 11 | 2008 | 11 | |
| 12 | Learning to Query, Reason, and Answer Questions On Ambiguous Texts | 2017 | 11 |
| 13 | 2015 | 10 | |
| 14 | 2010 | 9 | |
| 15 | 2019 | 7 | |
| 16 | 2006 | 4 | |
| 17 | 2019 | 4 | |
| 18 | Jazz as a research platform: experience from the Software Development Governance Group at IBM Research | 2008 | 3 |
| 19 | 2021 | 2 | |
| 20 | 2004 | 1 |
About Tim Klinger
Tim Klinger is a scholar working on Artificial Intelligence, Information Systems, Software, Language and Linguistics and Computational Theory and Mathematics, having authored 27 papers that have together received 584 indexed citations. Recurring topics across this work include Software Engineering Techniques and Practices (6 papers), Reinforcement Learning in Robotics (5 papers), Topic Modeling (5 papers), Software Engineering Research (4 papers), Natural Language Processing Techniques (4 papers), Domain Adaptation and Few-Shot Learning (3 papers), Syntax, Semantics, Linguistic Variation (2 papers) and Data Stream Mining Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (359 citations), Software (46 citations), Information Systems (211 citations), Health Informatics (4 citations) and Computer Science Applications (7 citations). Tim Klinger has collaborated with scholars based in United States, Israel and China. Frequent co-authors include Bowen Zhou, Clay E. Williams, Peri L. Tarr, Patrick A. Wagstrom, Gerald J. Tesauro, Kartik Talamadupula, Iulian Vlad Serban, Zhiguo Wang, Jing Jiang and Shiyu Chang. Their work appears in journals such as Nature Machine Intelligence, The Journal of Object Technology, International Conference on Learning Representations, arXiv (Cornell University) and AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)).
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.