Dave Shepard

411 total citations
6 papers, 337 citations indexed

About

Dave Shepard is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Dave Shepard has authored 6 papers receiving a total of 337 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 3 papers in Statistical and Nonlinear Physics and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Dave Shepard's work include Advanced Text Analysis Techniques (3 papers), Complex Network Analysis Techniques (3 papers) and Text and Document Classification Technologies (2 papers). Dave Shepard is often cited by papers focused on Advanced Text Analysis Techniques (3 papers), Complex Network Analysis Techniques (3 papers) and Text and Document Classification Technologies (2 papers). Dave Shepard collaborates with scholars based in Japan and United States. Dave Shepard's co-authors include Todd McNutt, Minesh P. Mehta, T. Rockwell Mackie, Paul Reckwerdt, G Olivera, K Ruchala, John Balog, Tetsuji Kuboyama, Takako Hashimoto and Takeaki Uno and has published in prestigious journals such as Seminars in Radiation Oncology and Information.

In The Last Decade

Dave Shepard

6 papers receiving 333 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dave Shepard Japan	3	276	208	196	51	34	6	337
T Ganesh India	10	249 0.9×	134 0.6×	222 1.1×	39 0.8×	43 1.3×	61	359
Matthew T. Studenski United States	13	316 1.1×	270 1.3×	230 1.2×	77 1.5×	30 0.9×	56	445
James Kavanaugh United States	13	351 1.3×	249 1.2×	300 1.5×	75 1.5×	25 0.7×	39	503
S. Vigorito Italy	13	251 0.9×	270 1.3×	241 1.2×	86 1.7×	61 1.8×	35	440
Marcel Nachbar Germany	13	314 1.1×	211 1.0×	313 1.6×	51 1.0×	19 0.6×	31	419
Morten Nielsen Denmark	10	217 0.8×	184 0.9×	200 1.0×	33 0.6×	25 0.7×	30	315
Irina Vergalasova United States	11	331 1.2×	233 1.1×	301 1.5×	94 1.8×	24 0.7×	45	461
A.W. Sharfo Netherlands	11	340 1.2×	212 1.0×	194 1.0×	32 0.6×	59 1.7×	26	410
Brian Napolitano United States	9	213 0.8×	145 0.7×	161 0.8×	31 0.6×	63 1.9×	14	374
Benjamin Rosen United States	11	168 0.6×	138 0.7×	220 1.1×	54 1.1×	36 1.1×	32	344

Countries citing papers authored by Dave Shepard

Since Specialization

Citations

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

Fields of papers citing papers by Dave Shepard

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dave Shepard

This figure shows the co-authorship network connecting the top 25 collaborators of Dave Shepard. A scholar is included among the top collaborators of Dave Shepard 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 Dave Shepard. Dave Shepard 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:

6 of 6 papers shown

1.

Hashimoto, Takako, et al.. (2019). Time Series Topic Transition Based on Micro-Clustering. 1–8. 2 indexed citations

2.

Kuboyama, Tetsuji, et al.. (2017). sCwc/sLcc: Highly Scalable Feature Selection Algorithms. Information. 8(4). 159–159. 1 indexed citations

3.

Hashimoto, Takako, et al.. (2016). Topic Extraction Method from Millions of Tweets Based on Fast Feature Selection Technique CWC. 2 indexed citations

4.

Hashimoto, Takako, et al.. (2015). Event Detection from Millions of Tweets Related to the Great East Japan Earthquake Using Feature Selection Technique. 3. 7–12. 7 indexed citations

5.

Kuboyama, Tetsuji, et al.. (2015). Super-CWC and super-LCC: Super fast feature selection algorithms. 1–7. 6 indexed citations

6.

Mackie, T. Rockwell, John Balog, K Ruchala, et al.. (1999). Tomotherapy. Seminars in Radiation Oncology. 9(1). 108–117. 319 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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