Ping Hou

1.0k total citations
24 papers, 753 citations indexed

About

Ping Hou is a scholar working on Artificial Intelligence, Environmental Engineering and Industrial and Manufacturing Engineering. According to data from OpenAlex, Ping Hou has authored 24 papers receiving a total of 753 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 7 papers in Environmental Engineering and 6 papers in Industrial and Manufacturing Engineering. Recurrent topics in Ping Hou's work include Environmental Impact and Sustainability (6 papers), Bayesian Modeling and Causal Inference (5 papers) and Logic, Reasoning, and Knowledge (3 papers). Ping Hou is often cited by papers focused on Environmental Impact and Sustainability (6 papers), Bayesian Modeling and Causal Inference (5 papers) and Logic, Reasoning, and Knowledge (3 papers). Ping Hou collaborates with scholars based in United States, China and Japan. Ping Hou's co-authors include Ming Xu, Shen Qu, Olivier Jolliet, Ji Zhu, Sai Liang, William Yeoh, Xi Tian, Morteza Taiebat, Shelie A. Miller and Christian M. Lastoskie and has published in prestigious journals such as Environmental Science & Technology, Journal of Cleaner Production and Environment International.

In The Last Decade

Ping Hou

23 papers receiving 744 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ping Hou United States 13 213 197 115 99 98 24 753
Rembrandt Koppelaar United Kingdom 15 190 0.9× 179 0.9× 218 1.9× 37 0.4× 216 2.2× 21 1.1k
Michele John Australia 17 132 0.6× 129 0.7× 95 0.8× 134 1.4× 121 1.2× 37 819
Jigeng Li China 17 145 0.7× 219 1.1× 57 0.5× 37 0.4× 216 2.2× 49 1.0k
Ioan Iordache Romania 13 55 0.3× 78 0.4× 88 0.8× 66 0.7× 112 1.1× 32 802
Tak Hur South Korea 16 218 1.0× 414 2.1× 147 1.3× 84 0.8× 274 2.8× 45 1.1k
Mohamed Abdallah United Arab Emirates 22 596 2.8× 243 1.2× 159 1.4× 101 1.0× 116 1.2× 67 1.4k
Ricardo de Araújo Kalid Brazil 17 73 0.3× 128 0.6× 126 1.1× 24 0.2× 130 1.3× 64 1.1k
Sandylove Afrane China 22 114 0.5× 303 1.5× 292 2.5× 243 2.5× 350 3.6× 41 1.4k
Changqing Xu China 14 375 1.8× 359 1.8× 177 1.5× 40 0.4× 340 3.5× 29 1.5k
Evanthia A. Nanaki Greece 16 104 0.5× 216 1.1× 78 0.7× 281 2.8× 304 3.1× 40 1.1k

Countries citing papers authored by Ping Hou

Since Specialization
Citations

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

Fields of papers citing papers by Ping Hou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ping Hou

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

All Works

20 of 20 papers shown
1.
Hou, Ping, Bu Zhao, Olivier Jolliet, et al.. (2020). Rapid Prediction of Chemical Ecotoxicity Through Genetic Algorithm Optimized Neural Network Models. ACS Sustainable Chemistry & Engineering. 8(32). 12168–12176. 23 indexed citations
2.
Zhi, Xiyang, et al.. (2020). Fusing deep learning and statistical visual features for no-reference image quality assessment. Journal of Electronic Imaging. 29(4). 1–1. 1 indexed citations
3.
Hou, Ping, Pei Guo, Peng Wu, et al.. (2020). A Deep Learning Model for Detecting Dust in Earth's Atmosphere from Satellite Remote Sensing Data. Maryland Shared Open Access Repository (USMAI Consortium). 196–201. 7 indexed citations
4.
Hou, Ping, Olivier Jolliet, Ji Zhu, & Ming Xu. (2019). Estimate ecotoxicity characterization factors for chemicals in life cycle assessment using machine learning models. Environment International. 135. 105393–105393. 97 indexed citations
5.
Hou, Ping, Jiarui Cai, Shen Qu, & Ming Xu. (2018). Estimating Missing Unit Process Data in Life Cycle Assessment Using a Similarity-Based Approach. Environmental Science & Technology. 52(9). 5259–5267. 39 indexed citations
6.
Hou, Ping, et al.. (2018). Life cycle assessment of end-of-life treatments for plastic film waste. Journal of Cleaner Production. 201. 1052–1060. 111 indexed citations
7.
Hou, Ping, et al.. (2017). Infinite-Horizon Proactive Dynamic DCOPs. Adaptive Agents and Multi-Agents Systems. 212–220. 7 indexed citations
8.
Tian, Xi, Yufeng Wu, Ping Hou, et al.. (2017). Environmental impact and economic assessment of secondary lead production: Comparison of main spent lead-acid battery recycling processes in China. Journal of Cleaner Production. 144. 142–148. 131 indexed citations
9.
Hou, Ping, et al.. (2017). New Metrics and Algorithms for Stochastic Goal Recognition Design Problems. 4455–4462. 12 indexed citations
10.
Hou, Ping, et al.. (2016). Goal recognition design with stochastic agent action outcomes. International Joint Conference on Artificial Intelligence. 3279–3285. 23 indexed citations
11.
Fioretto, Ferdinando, et al.. (2016). Proactive Dynamic Distributed Constraint Optimization. Adaptive Agents and Multi-Agents Systems. 597–605. 12 indexed citations
12.
Hou, Ping, William Yeoh, & Pradeep Varakantham. (2016). Solving Risk-Sensitive POMDPs With and Without Cost Observations. Proceedings of the AAAI Conference on Artificial Intelligence. 30(1). 7 indexed citations
13.
Hou, Ping, et al.. (2016). Product life cycle assessment based on online survey along supply chain. Acta Ecologica Sinica. 36(22). 1 indexed citations
14.
Chen, Yifei, Ping Hou, & Bernard Manderick. (2014). An ensemble self-training protein interaction article classifier. Bio-Medical Materials and Engineering. 24(1). 1323–1332. 7 indexed citations
15.
Hou, Ping, William Yeoh, & Tran Cao Son. (2014). Solving Uncertain MDPs by Reusing State Information and Plans. Proceedings of the AAAI Conference on Artificial Intelligence. 28(1).
16.
Hou, Ping, William Yeoh, & Pradeep Varakantham. (2014). Revisiting Risk-Sensitive MDPs: New Algorithms and Results. Proceedings of the International Conference on Automated Planning and Scheduling. 24. 136–144. 14 indexed citations
17.
Hou, Ping, et al.. (2012). GreenHouse gas emission factors of Chinese power grids for organization and product carbon footprint. China Environmental Science. 32(6). 961–967. 18 indexed citations
18.
Hou, Ping. (2010). Method and basic model for development of Chinese reference life cycle database. Acta Scientiae Circumstantiae. 60 indexed citations
19.
Hou, Ping, et al.. (2010). FO(FD): Extending classical logic with rule-based fixpoint definitions. Theory and Practice of Logic Programming. 10(4-6). 581–596. 8 indexed citations
20.
Hou, Ping & Marc Denecker. (2009). A logic of fixpoint definitions. Lirias (KU Leuven). 1–15. 1 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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