Zeming Lin

37.4k total citations · 3 hit papers
19 papers, 9.2k citations indexed

About

Zeming Lin is a scholar working on Artificial Intelligence, Plant Science and Molecular Biology. According to data from OpenAlex, Zeming Lin has authored 19 papers receiving a total of 9.2k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 8 papers in Plant Science and 6 papers in Molecular Biology. Recurrent topics in Zeming Lin's work include Artificial Intelligence in Games (6 papers), Plant Molecular Biology Research (6 papers) and Plant nutrient uptake and metabolism (5 papers). Zeming Lin is often cited by papers focused on Artificial Intelligence in Games (6 papers), Plant Molecular Biology Research (6 papers) and Plant nutrient uptake and metabolism (5 papers). Zeming Lin collaborates with scholars based in China, Israel and United States. Zeming Lin's co-authors include Soumith Chintala, Adam Lerer, Sam Gross, Edward Z. Yang, Luca Antiga, Adam Paszke, Alban Desmaison, Zachary DeVito, Alexander Rives and Tom Sercu and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and New Phytologist.

In The Last Decade

Zeming Lin

19 papers receiving 8.9k citations

Hit Papers

Automatic differentiation in PyTorch 2017 2026 2020 2023 2017 2023 2021 1000 2.0k 3.0k 4.0k 5.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Zeming Lin China 8 3.1k 2.9k 2.6k 750 646 19 9.2k
Pushmeet Kohli United Kingdom 60 2.4k 0.8× 8.0k 2.7× 3.4k 1.3× 769 1.0× 383 0.6× 201 15.9k
Karsten Borgwardt Germany 42 2.6k 0.8× 2.0k 0.7× 4.0k 1.5× 653 0.9× 345 0.5× 132 9.8k
Edward R. Dougherty United States 59 7.4k 2.4× 2.3k 0.8× 2.7k 1.0× 1.5k 2.0× 352 0.5× 489 13.6k
De-Shuang Huang China 58 4.1k 1.3× 3.4k 1.2× 2.6k 1.0× 890 1.2× 346 0.5× 331 11.1k
Gunnar Rätsch Germany 52 5.1k 1.6× 4.6k 1.6× 4.9k 1.9× 653 0.9× 330 0.5× 167 16.1k
Michael M. Bronstein Switzerland 50 1.0k 0.3× 7.1k 2.4× 2.5k 1.0× 836 1.1× 386 0.6× 177 14.3k
Massimiliano Pontil United Kingdom 45 1.2k 0.4× 3.7k 1.2× 4.8k 1.9× 550 0.7× 249 0.4× 139 10.7k
Shuiwang Ji United States 43 996 0.3× 3.1k 1.1× 3.5k 1.3× 275 0.4× 784 1.2× 134 7.4k
Sungroh Yoon South Korea 40 2.7k 0.9× 1.0k 0.4× 1.5k 0.6× 421 0.6× 292 0.5× 234 7.2k
Jun Zhu China 42 2.0k 0.6× 2.7k 0.9× 4.8k 1.8× 325 0.4× 248 0.4× 243 10.2k

Countries citing papers authored by Zeming Lin

Since Specialization
Citations

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

Fields of papers citing papers by Zeming Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zeming Lin

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

All Works

19 of 19 papers shown
1.
Lin, Zeming, Chenglei Zhu, Yan Liu, et al.. (2024). Identification of pectin acetylesterase genes in moso bamboo (Phyllostachys edulis) reveals PePAE6 involved in pectin accumulation of leaves. Industrial Crops and Products. 222. 119650–119650. 1 indexed citations
2.
Zhu, Chenglei, et al.. (2024). A bamboo bHLH transcription factor PeRHL4 has dual functions in enhancing drought and phosphorus starvation tolerance. Plant Cell & Environment. 47(8). 3015–3029. 14 indexed citations
3.
Zhu, Chenglei, et al.. (2024). Systematic identification and validation of the reference genes from 447 transcriptome datasets of moso bamboo (Phyllostachys edulis). Horticultural Plant Journal. 11(3). 1353–1363. 3 indexed citations
4.
Yang, Kebin, et al.. (2024). Comparison analysis of ABCG subfamily in bamboo and the potential function of PeABCG15 in monolignol transport. Plant Physiology and Biochemistry. 217. 109278–109278. 2 indexed citations
5.
Zhu, Chenglei, Zeming Lin, Kebin Yang, et al.. (2024). A bamboo ‘PeSAPK4‐PeMYB99‐PeTIP4‐3’ regulatory model involved in water transport. New Phytologist. 243(1). 195–212. 7 indexed citations
6.
Lin, Zeming, Chenglei Zhu, Kebin Yang, et al.. (2024). Identification and characterization of FBA genes in moso bamboo reveals PeFBA8 related to photosynthetic carbon metabolism. International Journal of Biological Macromolecules. 275(Pt 1). 132885–132885. 4 indexed citations
7.
Zhu, Chenglei, et al.. (2024). A Bamboo HD‐Zip Transcription Factor PeHDZ72 Conferred Drought Tolerance by Promoting Sugar and Water Transport. Plant Cell & Environment. 48(1). 310–322. 7 indexed citations
8.
Zhu, Chenglei, et al.. (2024). Evolutionary relationship of moso bamboo forms and a multihormone regulatory cascade involving culm shape variation. Plant Biotechnology Journal. 22(9). 2578–2592. 6 indexed citations
9.
Lin, Zeming, Halil Akin, Roshan Rao, et al.. (2023). Evolutionary-scale prediction of atomic-level protein structure with a language model. Science. 379(6637). 1123–1130. 1968 indexed citations breakdown →
10.
Rives, Alexander, Joshua Meier, Tom Sercu, et al.. (2021). Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences. Proceedings of the National Academy of Sciences. 118(15). 1429 indexed citations breakdown →
11.
Lin, Zeming, Jonas Gehring, Vasil Khalidov, & Gabriel Synnaeve. (2021). STARDATA: A StarCraft AI Research Dataset. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 13(1). 50–56. 3 indexed citations
12.
Nardelli, Nantas, Gabriel Synnaeve, Zeming Lin, et al.. (2018). Value Propagation Networks.. Oxford University Research Archive (ORA) (University of Oxford). 6 indexed citations
13.
Sukhbaatar, Sainbayar, Zeming Lin, Ilya Kostrikov, et al.. (2018). Intrinsic motivation and automatic curricula via asymmetric self-play. International Conference on Learning Representations. 27 indexed citations
14.
Synnaeve, Gabriel, Zeming Lin, Jonas Gehring, et al.. (2018). Forward Modeling for Partial Observation Strategy Games - A StarCraft Defogger. arXiv (Cornell University). 31. 10738–10748. 6 indexed citations
15.
Usunier, Nicolas, Gabriel Synnaeve, Zeming Lin, & Soumith Chintala. (2017). Episodic Exploration for Deep Deterministic Policies for StarCraft Micromanagement. International Conference on Learning Representations. 5 indexed citations
16.
Churchill, David G., Zeming Lin, & Gabriel Synnaeve. (2017). An Analysis of Model-Based Heuristic Search Techniques for StarCraft Combat Scenarios. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 13(2). 8–14. 6 indexed citations
17.
Gao, Ji, Beilun Wang, Zeming Lin, Weilin Xu, & Yanjun Qi. (2017). DeepCloak: Masking Deep Neural Network Models for Robustness Against Adversarial Samples. International Conference on Learning Representations. 4 indexed citations
18.
Paszke, Adam, Sam Gross, Soumith Chintala, et al.. (2017). Automatic differentiation in PyTorch. 5707 indexed citations breakdown →
19.
Lin, Zeming, Jack Lanchantin, & Yanjun Qi. (2016). MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-Based Protein Structure Prediction. Proceedings of the AAAI Conference on Artificial Intelligence. 30(1). 28 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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