Hanna Pasula

1.0k total citations
12 papers, 679 citations indexed

About

Hanna Pasula is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Hanna Pasula has authored 12 papers receiving a total of 679 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Molecular Biology. Recurrent topics in Hanna Pasula's work include AI-based Problem Solving and Planning (5 papers), Bayesian Modeling and Causal Inference (4 papers) and Bayesian Methods and Mixture Models (3 papers). Hanna Pasula is often cited by papers focused on AI-based Problem Solving and Planning (5 papers), Bayesian Modeling and Causal Inference (4 papers) and Bayesian Methods and Mixture Models (3 papers). Hanna Pasula collaborates with scholars based in United States. Hanna Pasula's co-authors include Stuart Russell, Leslie Pack Kaelbling, Luke Zettlemoyer, Bhaskara Marthi, Ilya Shpitser, Brian Milch, Michael Ostland, Ya’acov Ritov, Dieter Fox and Richard Newton and has published in prestigious journals such as Journal of Artificial Intelligence Research, Neural Information Processing Systems and International Joint Conference on Artificial Intelligence.

In The Last Decade

Hanna Pasula

12 papers receiving 598 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hanna Pasula United States	9	422	211	135	92	91	12	679
Chiara Piacentini United Kingdom	8	270 0.6×	132 0.6×	35 0.3×	51 0.6×	41 0.5×	20	481
Wai Kit Wong Malaysia	10	710 1.7×	243 1.2×	33 0.2×	32 0.3×	304 3.3×	46	994
Nicholas K. Jong United States	10	305 0.7×	128 0.6×	44 0.3×	101 1.1×	244 2.7×	12	673
Anshumali Shrivastava United States	15	426 1.0×	403 1.9×	34 0.3×	36 0.4×	91 1.0×	70	749
Mingxuan Sun United States	14	205 0.5×	219 1.0×	54 0.4×	24 0.3×	144 1.6×	53	659
Haitham Bou Ammar United States	14	332 0.8×	152 0.7×	43 0.3×	50 0.5×	17 0.2×	44	589
Thomas M. Strat United States	12	150 0.4×	242 1.1×	76 0.6×	66 0.7×	16 0.2×	27	452
Craig Sayers United States	8	276 0.7×	106 0.5×	41 0.3×	26 0.3×	129 1.4×	30	516
Zhongqiang Huang China	17	1.1k 2.7×	207 1.0×	80 0.6×	13 0.1×	72 0.8×	57	1.3k

Countries citing papers authored by Hanna Pasula

Since Specialization

Citations

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

Fields of papers citing papers by Hanna Pasula

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hanna Pasula

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

All Works

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12 of 12 papers shown

Zettlemoyer, Luke, Hanna Pasula, & Leslie Pack Kaelbling. (2008). Logical Particle Filtering. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 0. 7 indexed citations

Pasula, Hanna, et al.. (2007). Voronoi random fields: extracting the topological structure of indoor environments via place labeling. International Joint Conference on Artificial Intelligence. 2109–2114. 94 indexed citations

Pasula, Hanna, Luke Zettlemoyer, & Leslie Pack Kaelbling. (2007). Learning Symbolic Models of Stochastic Domains. Journal of Artificial Intelligence Research. 29. 309–352. 111 indexed citations

Zettlemoyer, Luke, Hanna Pasula, & Leslie Pack Kaelbling. (2005). Learning planning rules in noisy stochastic worlds. National Conference on Artificial Intelligence. 911–918. 36 indexed citations

Zettlemoyer, Luke, Hanna Pasula, & Leslie Pack Kaelbling. (2005). Learning Planning Rules in Stochastic Worlds. National Conference on Artificial Intelligence. 1 indexed citations

Pasula, Hanna, Luke Zettlemoyer, & Leslie Pack Kaelbling. (2004). Learning probabilistic relational planning rules. 73–81. 30 indexed citations

Pasula, Hanna, et al.. (2004). Learning and Planning with Probabilistic Relational Rules. 1 indexed citations

Marthi, Bhaskara, Hanna Pasula, Stuart Russell, & Yuval Peres. (2002). Decayed MCMC iltering. Uncertainty in Artificial Intelligence. 319–326. 18 indexed citations

Pasula, Hanna, Bhaskara Marthi, Brian Milch, Stuart Russell, & Ilya Shpitser. (2002). Identity Uncertainty and Citation Matching. Neural Information Processing Systems. 15. 1425–1432. 176 indexed citations

10.

Shilman, Michael, Hanna Pasula, Stuart Russell, & Richard Newton. (2002). Statistical Visual Language Models for Ink Parsing. 53 indexed citations

11.

Pasula, Hanna & Stuart Russell. (2001). Approximate inference for first-order probabilistic languages. International Joint Conference on Artificial Intelligence. 52(7). 741–748. 26 indexed citations

12.

Pasula, Hanna, Stuart Russell, Michael Ostland, & Ya’acov Ritov. (1999). Tracking many objects with many sensors. 1160–1167. 126 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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