Ni Lao

6.3k total citations · 5 hit papers
42 papers, 2.5k citations indexed

About

Ni Lao is a scholar working on Artificial Intelligence, Information Systems and Geography, Planning and Development. According to data from OpenAlex, Ni Lao has authored 42 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Artificial Intelligence, 11 papers in Information Systems and 11 papers in Geography, Planning and Development. Recurrent topics in Ni Lao's work include Topic Modeling (15 papers), Geographic Information Systems Studies (11 papers) and Natural Language Processing Techniques (10 papers). Ni Lao is often cited by papers focused on Topic Modeling (15 papers), Geographic Information Systems Studies (11 papers) and Natural Language Processing Techniques (10 papers). Ni Lao collaborates with scholars based in United States, China and United Kingdom. Ni Lao's co-authors include William W. Cohen, Xin Luna Dong, Kevin Murphy, Shaohua Sun, Evgeniy Gabrilovich, Wei Zhang, Geremy Heitz, Tom M. Mitchell, Gengchen Mai and Jonathan Berant and has published in prestigious journals such as ISPRS Journal of Photogrammetry and Remote Sensing, Machine Learning and International Journal of Applied Earth Observation and Geoinformation.

In The Last Decade

Ni Lao

40 papers receiving 2.3k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Knowledge vault

2014 892 citations Ni Lao et al. profile →
Relational retrieval using a combination of path-constrained random walks

2010 364 citations Ni Lao, William W. Cohen profile →
A review of location encoding for GeoAI: methods and applications

2022 92 citations Gengchen Mai, Krzysztof Janowicz et al. International Journal of Geographical Information Systems profile →
Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages

2023 85 citations Yingjie Hu, Gengchen Mai et al. International Journal of Geographical Information Systems profile →
On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper)

2024 45 citations Gengchen Mai, Weiming Huang et al. ACM Transactions on Spatial Algorithms and Systems profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ni Lao United States	19	1.9k	520	413	335	292	42	2.5k
Hongbo Deng China	23	901 0.5×	915 1.8×	127 0.3×	296 0.9×	219 0.8×	78	1.8k
Shou-De Lin Taiwan	24	983 0.5×	498 1.0×	143 0.3×	259 0.8×	229 0.8×	137	1.8k
Axel-Cyrille Ngonga Ngomo Germany	24	2.0k 1.1×	522 1.0×	596 1.4×	235 0.7×	277 0.9×	167	2.5k
Xiaochun Yang China	17	653 0.4×	306 0.6×	184 0.4×	235 0.7×	304 1.0×	130	1.3k
Lei Zhao China	21	697 0.4×	418 0.8×	110 0.3×	281 0.8×	282 1.0×	156	1.4k
Mikhail Bilenko United States	17	1.9k 1.1×	1.0k 1.9×	1.0k 2.5×	649 1.9×	456 1.6×	29	3.0k
Dingqi Yang China	27	1.3k 0.7×	716 1.4×	142 0.3×	352 1.1×	407 1.4×	68	2.8k
Tomoharu Iwata Japan	22	1.0k 0.5×	487 0.9×	74 0.2×	379 1.1×	185 0.6×	135	2.0k
Gideon Mann United States	19	1.4k 0.8×	294 0.6×	188 0.5×	219 0.7×	91 0.3×	30	1.7k

Countries citing papers authored by Ni Lao

Since Specialization

Citations

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

Fields of papers citing papers by Ni Lao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ni Lao

This figure shows the co-authorship network connecting the top 25 collaborators of Ni Lao. A scholar is included among the top collaborators of Ni Lao 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 Ni Lao. Ni Lao 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

Mai, Gengchen, Yiqun Xie, Xiaowei Jia, et al.. (2025). Towards the next generation of Geospatial Artificial Intelligence. International Journal of Applied Earth Observation and Geoinformation. 136. 104368–104368. 9 indexed citations

Janowicz, Krzysztof, Gengchen Mai, Weiming Huang, et al.. (2025). GeoFM: how will geo-foundation models reshape spatial data science and GeoAI?. International Journal of Geographical Information Systems. 39(9). 1849–1865. 2 indexed citations

Mai, Gengchen, Xiaobai Yao, Yiqun Xie, et al.. (2024). SRL: Towards a General-Purpose Framework for Spatial Representation Learning. 465–468. 3 indexed citations

Mai, Gengchen, Weiming Huang, Suhang Song, et al.. (2024). On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper). ACM Transactions on Spatial Algorithms and Systems. 10(2). 1–46. 45 indexed citations breakdown →

Zhou, Zhongliang, Zihan Guan, Ni Lao, et al.. (2024). Img2Loc: Revisiting Image Geolocalization using Multi-modality Foundation Models and Image-based Retrieval-Augmented Generation. 2749–2754. 7 indexed citations

Ermon, Stefano, Tanuja Ganu, Ni Lao, et al.. (2024). TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning. 81437–81460.

Gao, Luyu, Zhuyun Dai, Panupong Pasupat, et al.. (2023). RARR: Researching and Revising What Language Models Say, Using Language Models. 16477–16508. 50 indexed citations

Mai, Gengchen, Chris Cundy, Kristy Choi, et al.. (2022). Towards a foundation model for geospatial artificial intelligence (vision paper). 1–4. 38 indexed citations

Mai, Gengchen, Chiyu Jiang, Weiwei Sun, et al.. (2022). Towards general-purpose representation learning of polygonal geometries. GeoInformatica. 27(2). 289–340. 27 indexed citations

10.

Chen, Liang, Mohammad Norouzi, Jonathan Berant, Quoc V. Le, & Ni Lao. (2018). Memory Augmented Policy Optimization for Program Synthesis with Generalization. arXiv (Cornell University). 4 indexed citations

11.

Lao, Ni, Tom M. Mitchell, & William W. Cohen. (2018). Random Walk Inference and Learning in A Large Scale Knowledge Base. Figshare. 529–539. 189 indexed citations

12.

Lao, Ni, Amarnag Subramanya, Fernando Pereira, & William W. Cohen. (2018). Reading The Web with Learned Syntactic-Semantic Inference Rules. Figshare. 1017–1026. 18 indexed citations

13.

Chen, Liang, Jonathan Berant, Quoc V. Le, Kenneth D. Forbus, & Ni Lao. (2017). Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision. 23–33. 187 indexed citations

14.

Yang, Fan, et al.. (2017). LEARNING TO ORGANIZE KNOWLEDGE WITH N-GRAM MACHINES. arXiv (Cornell University). 1 indexed citations

15.

Lao, Ni, et al.. (2010). Efficient Relational Learning with Hidden Variable Detection. Neural Information Processing Systems. 23. 1234–1242. 4 indexed citations

16.

Lao, Ni, et al.. (2008). Complex Cross-lingual Question Answering as a Sequential Classification and Multi-Document Summarization Task. NTCIR. 4 indexed citations

17.

Zuo, Wenyun, Ni Lao, Yun Geng, & Keping Ma. (2008). GeoSVM: an efficient and effective tool to predict species' potential distributions. Journal of Plant Ecology. 1(2). 143–145. 4 indexed citations

18.

Lao, Ni, et al.. (2008). Query Expansion and Machine Translation for Robust Cross-Lingual Information Retrieval. NTCIR. 4 indexed citations

19.

Zuo, Wenyun, et al.. (2007). PREDICTING SPECIES′ POTENTIAL DISTRIBUTION—SVM COMPARED WITH GARP. Chinese Journal of Plant Ecology. 31(4). 711–719. 1 indexed citations

20.

Lao, Ni, Ji-Rong Wen, Wei‐Ying Ma, & Yi‐Min Wang. (2004). Combining High Level Symptom Descriptions and Low Level State Information for Configuration Fault Diagnosis. USENIX Large Installation Systems Administration Conference. 151–158. 14 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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