Mark Nitzberg

1.5k total citations
14 papers, 880 citations indexed

About

Mark Nitzberg is a scholar working on Computer Vision and Pattern Recognition, Safety Research and Molecular Biology. According to data from OpenAlex, Mark Nitzberg has authored 14 papers receiving a total of 880 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computer Vision and Pattern Recognition, 4 papers in Safety Research and 3 papers in Molecular Biology. Recurrent topics in Mark Nitzberg's work include Ethics and Social Impacts of AI (4 papers), Digital Economy and Work Transformation (3 papers) and Gene expression and cancer classification (3 papers). Mark Nitzberg is often cited by papers focused on Ethics and Social Impacts of AI (4 papers), Digital Economy and Work Transformation (3 papers) and Gene expression and cancer classification (3 papers). Mark Nitzberg collaborates with scholars based in United States and Japan. Mark Nitzberg's co-authors include Takahiro Shiota, David Mumford, D. Mumford, John Zysman, Gavin Sherlock, Catherine A. Ball, Zita Zachariah, János Demeter, Jin Huang and Dieter Maier and has published in prestigious journals such as Nucleic Acids Research, IEEE Transactions on Pattern Analysis and Machine Intelligence and Journal of European Public Policy.

In The Last Decade

Mark Nitzberg

14 papers receiving 820 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mark Nitzberg United States	9	439	218	104	76	71	14	880
Raj Acharya United States	19	412 0.9×	423 1.9×	30 0.3×	145 1.9×	57 0.8×	132	1.4k
David Letscher United States	13	220 0.5×	717 3.3×	106 1.0×	50 0.7×	33 0.5×	33	1.4k
Ronggang Wang China	22	1.7k 3.8×	123 0.6×	69 0.7×	79 1.0×	462 6.5×	179	2.2k
Yaohua Hu China	17	187 0.4×	216 1.0×	215 2.1×	61 0.8×	21 0.3×	71	871
Limin Luo China	20	1.2k 2.8×	63 0.3×	65 0.6×	82 1.1×	260 3.7×	57	1.5k
Júnior Barrera Brazil	16	315 0.7×	329 1.5×	35 0.3×	280 3.7×	58 0.8×	105	989
Arunava Banerjee United States	17	386 0.9×	65 0.3×	123 1.2×	153 2.0×	120 1.7×	54	986
Stefan Steinerberger United States	11	101 0.2×	168 0.8×	30 0.3×	94 1.2×	8 0.1×	99	657

Countries citing papers authored by Mark Nitzberg

Since Specialization

Citations

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

Fields of papers citing papers by Mark Nitzberg

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Nitzberg

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

All Works

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14 of 14 papers shown

Zysman, John & Mark Nitzberg. (2024). Generative AI and the Future of Work: Augmentation or Automation?. SSRN Electronic Journal. 2 indexed citations

Nitzberg, Mark, et al.. (2024). When code isn’t law: rethinking regulation for artificial intelligence. Policy and Society. 44(1). 85–97. 7 indexed citations

Nitzberg, Mark & John Zysman. (2022). Algorithms, data, and platforms: the diverse challenges of governing AI. Journal of European Public Policy. 29(11). 1753–1778. 35 indexed citations

Nitzberg, Mark & John Zysman. (2021). Algorithms, Data, and Platforms: The Diverse Challenges of Governing AI. SSRN Electronic Journal. 5 indexed citations

Zysman, John & Mark Nitzberg. (2020). Governing AI: Understanding the Limits, Possibility, and Risks of AI in an Era of Intelligent Tools and Systems. SSRN Electronic Journal. 10 indexed citations

Zysman, John, et al.. (2019). AI and Domain Knowledge: Implications of the Limits of Statistical Inference. SSRN Electronic Journal. 1 indexed citations

Demeter, János, Jin Huang, M. Mao, et al.. (2008). Implementation of GenePattern within the Stanford Microarray Database. Nucleic Acids Research. 37(Database). D898–D901. 88 indexed citations

Marinelli, Robert J., Kelli Montgomery, Nigam H. Shah, et al.. (2007). The Stanford Tissue Microarray Database. Nucleic Acids Research. 36(Database). D871–D877. 74 indexed citations

Demeter, János, Jeremy Gollub, Tina Hernandez‐Boussard, et al.. (2006). The Stanford Microarray Database: implementation of new analysis tools and open source release of software. Nucleic Acids Research. 35(Database). D766–D770. 123 indexed citations

10.

Nitzberg, Mark & D. Mumford. (2002). The 2.1-D sketch. 138–144. 64 indexed citations

11.

Yuille, Alan, D. Snow, & Mark Nitzberg. (2002). Signfinder: using color to detect, localize and identify informational signs. 628–633. 21 indexed citations

12.

Nitzberg, Mark, David Mumford, & Takahiro Shiota. (1993). Filtering, Segmentation and Depth. Lecture notes in computer science. 246 indexed citations

13.

Nitzberg, Mark & Takahiro Shiota. (1992). Nonlinear image filtering with edge and corner enhancement. IEEE Transactions on Pattern Analysis and Machine Intelligence. 14(8). 826–833. 202 indexed citations

14.

Nitzberg, Mark. (1991). Depth from overlap. 2 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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