Tianyi Liu

581 total citations
29 papers, 369 citations indexed

About

Tianyi Liu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Condensed Matter Physics. According to data from OpenAlex, Tianyi Liu has authored 29 papers receiving a total of 369 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Condensed Matter Physics. Recurrent topics in Tianyi Liu's work include Topic Modeling (12 papers), Text and Document Classification Technologies (6 papers) and Natural Language Processing Techniques (6 papers). Tianyi Liu is often cited by papers focused on Topic Modeling (12 papers), Text and Document Classification Technologies (6 papers) and Natural Language Processing Techniques (6 papers). Tianyi Liu collaborates with scholars based in China, Macao and United States. Tianyi Liu's co-authors include Jiantao Zhou, Weijia Jia, Jiandian Zeng, Weijia Jia, Xinsong Zhang, Wenmian Yang, Martin Head‐Gordon, Yuezhi Mao, Teresa Head‐Gordon and Omar Demerdash and has published in prestigious journals such as Angewandte Chemie International Edition, The Journal of Chemical Physics and ACS Nano.

In The Last Decade

Tianyi Liu

24 papers receiving 365 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tianyi Liu China	11	213	59	58	46	36	29	369
Dániel Ábel Hungary	6	60 0.3×	25 0.4×	16 0.3×	17 0.4×	57 1.6×	8	294
Takashi Shibuya Japan	9	179 0.8×	20 0.3×	69 1.2×	32 0.7×	14 0.4×	38	329
Jian Ren China	8	59 0.3×	23 0.4×	93 1.6×	49 1.1×	3 0.1×	25	235
Cory Stephenson United States	6	91 0.4×	12 0.2×	18 0.3×	28 0.6×	4 0.1×	12	225
Mahima Arya India	7	37 0.2×	35 0.6×	13 0.2×	52 1.1×	6 0.2×	11	264
Siqi Huang China	9	27 0.1×	44 0.7×	12 0.2×	27 0.6×	43 1.2×	16	495
S. KONNO Japan	11	36 0.2×	25 0.4×	42 0.7×	11 0.2×	46 1.3×	31	291
Y. Tu China	5	47 0.2×	27 0.5×	5 0.1×	20 0.4×	77 2.1×	9	258
Zihan Wang China	9	198 0.9×	24 0.4×	4 0.1×	33 0.7×	13 0.4×	40	278

Countries citing papers authored by Tianyi Liu

Since Specialization

Citations

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

Fields of papers citing papers by Tianyi Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tianyi Liu

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Liu, Tianyi, Hang Shi, Guo‐Xing Zhang, et al.. (2025). Molecular‐Level Design of Polymeric Semiconductor Nanomotors with Multichannel Sensitive 3D Motion for Microorganism Inactivation. Angewandte Chemie International Edition. 64(37). e202508705–e202508705. 1 indexed citations

Sun, Ning, Rui Tu, Changjiang Yang, et al.. (2025). Systematic Regulation of Ternary Covalent Organic Frameworks for Boosted Photocatalytic Hydrogen Evolution. ACS Catalysis. 15(22). 18976–18986.

Liu, Tianyi, et al.. (2025). Ceno: Non-uniform, Segment and Parallel Zero-Knowledge Virtual Machine. Journal of Cryptology. 38(2).

Tang, Kezong, et al.. (2025). MAS-KCL: knowledge component graph structure learning with large language model-based agentic workflow. The Visual Computer. 41(9). 6453–6464.

Liu, Tianyi, et al.. (2024). Multimodal Guidance Network for Missing- Modality Inference in Content Moderation. 1–4.

Liu, Wenyang, Kejun Wu, Tianyi Liu, et al.. (2024). ByteNet: Rethinking Multimedia File Fragment Classification Through Visual Perspectives. IEEE Transactions on Multimedia. 27. 1305–1319. 4 indexed citations

Liu, Tianyi, Tiancheng Xie, Jiaheng Zhang, Dawn Song, & Yupeng Zhang. (2024). Pianist: Scalable zkRollups via Fully Distributed Zero-Knowledge Proofs. 1777–1793. 8 indexed citations

Li, Jie, et al.. (2024). Effects of aeolian deposition on soil properties and microbial carbon metabolism function in farmland of Songnen Plain, China. Scientific Reports. 14(1). 14791–14791. 4 indexed citations

Liu, Tianyi, Lei Xie, Jie Zeng, et al.. (2022). Interfacial Superassembly of Light-Responsive Mechanism-Switchable Nanomotors with Tunable Mobility and Directionality. ACS Applied Materials & Interfaces. 14(13). 15517–15528. 34 indexed citations

10.

Zeng, Jiandian, Jiantao Zhou, & Tianyi Liu. (2022). Mitigating Inconsistencies in Multimodal Sentiment Analysis under Uncertain Missing Modalities. 2924–2934. 13 indexed citations

11.

Zeng, Jiandian, Tianyi Liu, & Jiantao Zhou. (2022). Tag-assisted Multimodal Sentiment Analysis under Uncertain Missing Modalities. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 1545–1554. 41 indexed citations

12.

Hu, Wei, et al.. (2021). Machine-Learning based MOOC Education Data Analysis. 11. 315–319. 1 indexed citations

13.

Lin, Xiangyu, Tianyi Liu, Weijia Jia, & Zhiguo Gong. (2021). Distantly Supervised Relation Extraction using Multi-Layer Revision Network and Confidence-based Multi-Instance Learning. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 165–174. 4 indexed citations

14.

Zhang, Xinsong, et al.. (2020). Fine-grained relation extraction with focal multi-task learning. Science China Information Sciences. 63(6). 1 indexed citations

15.

Liu, Tianyi, et al.. (2020). Regularized Attentive Capsule Network for Overlapped Relation Extraction. 6388–6398. 8 indexed citations

16.

Zhang, Xinsong, et al.. (2020). Robust Neural Relation Extraction via Multi-Granularity Noises Reduction. IEEE Transactions on Knowledge and Data Engineering. 33(9). 3297–3310. 16 indexed citations

17.

Jia, Weijia, et al.. (2019). Improving Abstractive Document Summarization with Salient Information Modeling. 2132–2141. 31 indexed citations

18.

Wang, Xin, Huiqing Sun, Xian Yang, et al.. (2018). Performance enhancement of AlGaN-based UV-LEDs inserted with a pin-doped AlGaN layer between the active region and electron-blocking layer. Materials Science in Semiconductor Processing. 83. 133–138. 9 indexed citations

19.

Liu, Tianyi, et al.. (2018). Neural Relation Extraction via Inner-Sentence Noise Reduction and Transfer Learning. 36 indexed citations

20.

Demerdash, Omar, Yuezhi Mao, Tianyi Liu, Martin Head‐Gordon, & Teresa Head‐Gordon. (2017). Assessing many-body contributions to intermolecular interactions of the AMOEBA force field using energy decomposition analysis of electronic structure calculations. The Journal of Chemical Physics. 147(16). 161721–161721. 36 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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