Tyler McDonnell

684 total citations
10 papers, 464 citations indexed

About

Tyler McDonnell is a scholar working on Artificial Intelligence, Computer Science Applications and Information Systems. According to data from OpenAlex, Tyler McDonnell has authored 10 papers receiving a total of 464 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 5 papers in Computer Science Applications and 3 papers in Information Systems. Recurrent topics in Tyler McDonnell's work include Mobile Crowdsensing and Crowdsourcing (5 papers), Auction Theory and Applications (3 papers) and Topic Modeling (3 papers). Tyler McDonnell is often cited by papers focused on Mobile Crowdsensing and Crowdsourcing (5 papers), Auction Theory and Applications (3 papers) and Topic Modeling (3 papers). Tyler McDonnell collaborates with scholars based in United States, Qatar and Türkiye. Tyler McDonnell's co-authors include Miryung Kim, Baishakhi Ray, Matthew Lease, Mücahid Kutlu, Tamer Elsayed, Edward A. Banner, Byron Wallace, An Nguyen, M. M. Rahman and Henna Kim and has published in prestigious journals such as Journal of Artificial Intelligence Research, Information Retrieval and arXiv (Cornell University).

In The Last Decade

Tyler McDonnell

10 papers receiving 441 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tyler McDonnell United States	9	259	212	135	99	92	10	464
Bowen Xu Singapore	15	554 2.1×	404 1.9×	111 0.8×	74 0.7×	142 1.5×	46	755
Rabe Abdalkareem Canada	12	525 2.0×	154 0.7×	120 0.9×	156 1.6×	173 1.9×	31	655
Venera Arnaoudova Canada	15	558 2.2×	190 0.9×	114 0.8×	89 0.9×	149 1.6×	28	658
Ginger Myles United States	7	255 1.0×	241 1.1×	244 1.8×	45 0.5×	94 1.0×	12	495
Jeffrey Wong United States	8	256 1.0×	95 0.4×	27 0.2×	62 0.6×	164 1.8×	8	433
Suzanne W. Dietrich United States	13	196 0.8×	220 1.0×	54 0.4×	101 1.0×	238 2.6×	71	532
Henry Feild United States	11	409 1.6×	167 0.8×	68 0.5×	80 0.8×	53 0.6×	23	488
C. Cook United States	17	239 0.9×	97 0.5×	31 0.2×	180 1.8×	73 0.8×	28	534
Paolo A. G. Sivilotti United States	9	302 1.2×	238 1.1×	69 0.5×	83 0.8×	172 1.9×	30	506

Countries citing papers authored by Tyler McDonnell

Since Specialization

Citations

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

Fields of papers citing papers by Tyler McDonnell

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tyler McDonnell

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

All Works

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10 of 10 papers shown

McDonnell, Tyler, et al.. (2022). Surrogate-assisted neuroevolution. Proceedings of the Genetic and Evolutionary Computation Conference. 2 indexed citations

Kutlu, Mücahid, Tyler McDonnell, Matthew Lease, & Tamer Elsayed. (2020). Annotator Rationales for Labeling Tasks in Crowdsourcing. Journal of Artificial Intelligence Research. 69. 143–189. 26 indexed citations

Kutlu, Mücahid, et al.. (2018). Crowd vs. Expert. Qatar University QSpace (Qatar University). 805–814. 15 indexed citations

McDonnell, Tyler, et al.. (2018). Divide and conquer. Proceedings of the Genetic and Evolutionary Computation Conference. 474–481. 11 indexed citations

Goyal, Tanya, Tyler McDonnell, Mücahid Kutlu, Tamer Elsayed, & Matthew Lease. (2018). Your Behavior Signals Your Reliability: Modeling Crowd Behavioral Traces to Ensure Quality Relevance Annotations. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. 6. 41–49. 22 indexed citations

Zhang, Ye, İsmail Sengör Altıngövde, M. M. Rahman, et al.. (2017). Neural information retrieval: at the end of the early years. Information Retrieval. 21(2-3). 111–182. 76 indexed citations

McDonnell, Tyler, Mücahid Kutlu, Tamer Elsayed, & Matthew Lease. (2017). The Many Benefits of Annotator Rationales for Relevance Judgments. Qatar University QSpace (Qatar University). 4909–4913. 8 indexed citations

McDonnell, Tyler, Matthew Lease, Mücahid Kutlu, & Tamer Elsayed. (2016). Why Is That Relevant? Collecting Annotator Rationales for Relevance Judgments. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. 4. 139–148. 58 indexed citations

Zhang, Ye, M. M. Rahman, Henna Kim, et al.. (2016). Neural Information Retrieval: A Literature Review. arXiv (Cornell University). 20 indexed citations

10.

McDonnell, Tyler, Baishakhi Ray, & Miryung Kim. (2013). An Empirical Study of API Stability and Adoption in the Android Ecosystem. 70–79. 226 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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