Tie-Jiun Hou
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- Particle physics theoretical and experimental studies 43
- High-Energy Particle Collisions Research 36
- Quantum Chromodynamics and Particle Interactions 33
- Particle Detector Development and Performance 4
- Dark Matter and Cosmic Phenomena 4
- Astronomy and Astrophysics top 10%
- Cosmology and Gravitation Theories 2
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- Computational Physics and Python Applications 2
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- Superconducting Materials and Applications 2
- Co-authors
- C.–P. YuanSayipjamal DulatCarl R. SchmidtJ. HustonJun GaoPavel NadolskyMarco GuzziJon Pumplin
- Cited by
- Nuclear and High Energy PhysicsAstronomy and AstrophysicsComputer Networks and Communications
- Journals
- SHILAP Revista de lepidopterología (7 papers)Physics Letters B (3 papers)Journal of High Energy Physics (1 paper)
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Tie-Jiun Hou
42 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 34
- Nuclear and High Energy Physics 1.4k
- Astronomy and Astrophysics 84
- Computer Networks and Communications 33
- Structural Biology 2
- Artificial Intelligence 34
Countries citing papers authored by Tie-Jiun Hou
This map shows the geographic impact of Tie-Jiun Hou'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 Tie-Jiun Hou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tie-Jiun Hou more than expected).
Fields of papers citing papers by Tie-Jiun Hou
This network shows the impact of papers produced by Tie-Jiun Hou. 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 Tie-Jiun Hou. The network helps show where Tie-Jiun Hou may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tie-Jiun Hou, 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 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 9 | |
| 4 | 2024 | 1 | |
| 5 | 2023 | 1 | |
| 6 | 2023 | 7 | |
| 7 | 2023 | 10 | |
| 8 | 2023 | 4 | |
| 9 | 2022 | 4 | |
| 10 | 2022 | 4 | |
| 11 | 2022 | 23 | |
| 12 | 2022 | 8 | |
| 13 | 2022 | 1 | |
| 14 | 2022 | 5 | |
| 15 | New CTEQ global analysis of quantum chromodynamics with high-precision data from the LHCbreakdown → | 2021 | 363 |
| 16 | 2020 | 11 | |
| 17 | 2019 | 3 | |
| 18 | 2016 | 2 | |
| 19 | 2014 | 13 | |
| 20 | 2007 | 3 |
About Tie-Jiun Hou
Tie-Jiun Hou is a scholar working on Nuclear and High Energy Physics, Astronomy and Astrophysics and Artificial Intelligence, having authored 45 papers that have together received 1.5k indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (43 papers), High-Energy Particle Collisions Research (36 papers), Quantum Chromodynamics and Particle Interactions (33 papers), Particle Detector Development and Performance (4 papers), Dark Matter and Cosmic Phenomena (4 papers), Cosmology and Gravitation Theories (2 papers), Superconducting Materials and Applications (2 papers) and Computational Physics and Python Applications (2 papers). The work is most often cited by research in Nuclear and High Energy Physics (1.4k citations), Astronomy and Astrophysics (84 citations) and Computer Networks and Communications (33 citations). Tie-Jiun Hou has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include C.–P. Yuan, Sayipjamal Dulat, Carl R. Schmidt, J. Huston, Jun Gao, Pavel Nadolsky, Marco Guzzi, Jon Pumplin, Daniel R. Stump and Keping Xie. Their work appears in journals such as SHILAP Revista de lepidopterología, Physics Letters B and Journal of High Energy Physics.
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.