Marco Cusumano-Towner

835 total citations
8 papers, 486 citations indexed

About

Marco Cusumano-Towner is a scholar working on Artificial Intelligence, Human-Computer Interaction and Control and Systems Engineering. According to data from OpenAlex, Marco Cusumano-Towner has authored 8 papers receiving a total of 486 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 2 papers in Human-Computer Interaction and 1 paper in Control and Systems Engineering. Recurrent topics in Marco Cusumano-Towner's work include Bayesian Modeling and Causal Inference (5 papers), Machine Learning and Algorithms (3 papers) and Machine Learning and Data Classification (3 papers). Marco Cusumano-Towner is often cited by papers focused on Bayesian Modeling and Causal Inference (5 papers), Machine Learning and Algorithms (3 papers) and Machine Learning and Data Classification (3 papers). Marco Cusumano-Towner collaborates with scholars based in United States and Switzerland. Marco Cusumano-Towner's co-authors include Pieter Abbeel, Jeremy Maitin-Shepard, Arjun Singh, James F. O’Brien, Stephen D. Miller, Vikash K. Mansinghka, David M. Maslove, Gomathi Krishnan, Timon Gehr and Michael Carbin and has published in prestigious journals such as Journal of the American Medical Informatics Association, ACM SIGPLAN Notices and Proceedings of the ACM on Programming Languages.

In The Last Decade

Marco Cusumano-Towner

8 papers receiving 459 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Marco Cusumano-Towner United States	6	277	166	97	94	94	8	486
Sebastian Höfer Germany	10	223 0.8×	216 1.3×	88 0.9×	28 0.3×	107 1.1×	21	447
Jiang Yun China	10	441 1.6×	268 1.6×	229 2.4×	23 0.2×	93 1.0×	31	682
Gilbert Bernstein United States	13	153 0.6×	281 1.7×	23 0.2×	158 1.7×	24 0.3×	30	571
Ignacy Dulȩba Poland	9	279 1.0×	273 1.6×	100 1.0×	20 0.2×	82 0.9×	43	461
Zoe McCarthy United States	10	434 1.6×	220 1.3×	188 1.9×	10 0.1×	52 0.6×	13	668
Dejan Milutinović United States	15	232 0.8×	224 1.3×	85 0.9×	46 0.5×	363 3.9×	80	761
Rico Jonschkowski Germany	8	233 0.8×	173 1.0×	79 0.8×	6 0.1×	125 1.3×	12	401

Countries citing papers authored by Marco Cusumano-Towner

Since Specialization

Citations

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

Fields of papers citing papers by Marco Cusumano-Towner

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marco Cusumano-Towner. 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 Marco Cusumano-Towner. The network helps show where Marco Cusumano-Towner may publish in the future.

Co-authorship network of co-authors of Marco Cusumano-Towner

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

All Works

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8 of 8 papers shown

Cusumano-Towner, Marco, et al.. (2019). Trace types and denotational semantics for sound programmable inference in probabilistic languages. Proceedings of the ACM on Programming Languages. 4(POPL). 1–32. 11 indexed citations

Cusumano-Towner, Marco, et al.. (2019). Gen: a general-purpose probabilistic programming system with programmable inference. 221–236. 40 indexed citations

Cusumano-Towner, Marco, Benjamin Bichsel, Timon Gehr, Martin Vechev, & Vikash K. Mansinghka. (2018). Incremental inference for probabilistic programs. ACM SIGPLAN Notices. 53(4). 571–585. 1 indexed citations

Cusumano-Towner, Marco & Vikash K. Mansinghka. (2018). A design proposal for Gen: probabilistic programming with fast custom inference via code generation. 16. 52–57. 5 indexed citations

Cusumano-Towner, Marco, Benjamin Bichsel, Timon Gehr, Martin Vechev, & Vikash K. Mansinghka. (2018). Incremental inference for probabilistic programs. 571–585. 7 indexed citations

Cusumano-Towner, Marco, et al.. (2013). A social network of hospital acquired infection built from electronic medical record data. Journal of the American Medical Informatics Association. 20(3). 427–434. 23 indexed citations

Cusumano-Towner, Marco, Arjun Singh, Stephen D. Miller, James F. O’Brien, & Pieter Abbeel. (2011). Bringing clothing into desired configurations with limited perception. 3893–3900. 110 indexed citations

Maitin-Shepard, Jeremy, et al.. (2010). Cloth grasp point detection based on multiple-view geometric cues with application to robotic towel folding. 2308–2315. 289 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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