Edward McFowland

870 total citations · 1 hit paper
16 papers, 432 citations indexed

About

Edward McFowland is a scholar working on Artificial Intelligence, Management Science and Operations Research and Epidemiology. According to data from OpenAlex, Edward McFowland has authored 16 papers receiving a total of 432 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 4 papers in Management Science and Operations Research and 3 papers in Epidemiology. Recurrent topics in Edward McFowland's work include Anomaly Detection Techniques and Applications (5 papers), Explainable Artificial Intelligence (XAI) (4 papers) and Data-Driven Disease Surveillance (3 papers). Edward McFowland is often cited by papers focused on Anomaly Detection Techniques and Applications (5 papers), Explainable Artificial Intelligence (XAI) (4 papers) and Data-Driven Disease Surveillance (3 papers). Edward McFowland collaborates with scholars based in United States, Canada and India. Edward McFowland's co-authors include Fabrizio Dell’Acqua, François Candelon, Katherine C. Kellogg, Ethan Mollick, Karim R. Lakhani, Lisa Krayer, Hila Lifshitz‐Assaf, Daniel B. Neill, Skyler Speakman and Cosma Rohilla Shalizi and has published in prestigious journals such as Management Science, MIS Quarterly and Statistics in Medicine.

In The Last Decade

Edward McFowland

15 papers receiving 395 citations

Hit Papers

Navigating the Jagged Tec... 2023 2026 2024 2023 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality
    2023 318 citations Fabrizio Dell’Acqua, Edward McFowland et al. SSRN Electronic Journal profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Edward McFowland United States 6 153 73 56 51 44 16 432
David Askay United States 8 102 0.7× 54 0.7× 24 0.4× 86 1.7× 89 2.0× 16 463
Nicholas Frick Germany 11 188 1.2× 80 1.1× 107 1.9× 95 1.9× 39 0.9× 16 607
Emmanuel Letouzé United States 8 167 1.1× 237 3.2× 69 1.2× 184 3.6× 30 0.7× 13 583
Ekaterina Jussupow Germany 7 146 1.0× 141 1.9× 113 2.0× 57 1.1× 51 1.2× 14 431
Jim Samuel United States 12 177 1.2× 15 0.2× 27 0.5× 126 2.5× 45 1.0× 39 443
Dana Pessach Israel 4 219 1.4× 161 2.2× 71 1.3× 45 0.9× 44 1.0× 7 509
Nassim Dehouche Thailand 6 119 0.8× 42 0.6× 102 1.8× 238 4.7× 39 0.9× 14 612
Eva Thelisson Switzerland 5 224 1.5× 51 0.7× 41 0.7× 156 3.1× 29 0.7× 8 640
Luc Rocher United Kingdom 5 219 1.4× 39 0.5× 68 1.2× 123 2.4× 7 0.2× 7 477
Jenifer Sunrise Winter United States 10 58 0.4× 44 0.6× 31 0.6× 161 3.2× 61 1.4× 36 412

Countries citing papers authored by Edward McFowland

Since Specialization
Citations

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

Fields of papers citing papers by Edward McFowland

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Edward McFowland

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

All Works

16 of 16 papers shown
1.
Kellogg, Katherine C., Ethan Mollick, Fabrizio Dell’Acqua, et al.. (2025). Novice risk work: How juniors coaching seniors on emerging technologies such as generative AI can lead to learning failures. Information and Organization. 35(1). 100559–100559. 2 indexed citations
2.
McFowland, Edward, et al.. (2023). Provable Detection of Propagating Sampling Bias in Prediction Models. Proceedings of the AAAI Conference on Artificial Intelligence. 37(8). 9562–9569. 4 indexed citations
3.
Dell’Acqua, Fabrizio, Edward McFowland, Ethan Mollick, et al.. (2023). Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality. SSRN Electronic Journal. 318 indexed citations breakdown →
4.
Bapna, Ravi, et al.. (2022). So, Who Likes You? Evidence from a Randomized Field Experiment. Management Science. 69(7). 3939–3957. 2 indexed citations
5.
McFowland, Edward. (2022). Commentary on “Causal Decision Making and Causal Effect Estimation Are Not the Same… and Why It Matters”. RePEc: Research Papers in Economics. 1(1). 21–22. 1 indexed citations
6.
Yang, Mochen, Edward McFowland, Gordon Burtch, & Gediminas Adomavičius. (2022). Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem. RePEc: Research Papers in Economics. 1(2). 138–155. 1 indexed citations
7.
McFowland, Edward & Cosma Rohilla Shalizi. (2021). Estimating Causal Peer Influence in Homophilous Social Networks by Inferring Latent Locations. Figshare. 5 indexed citations
8.
McFowland, Edward, et al.. (2021). A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects. MIS Quarterly. 45(4). 1807–1832. 1 indexed citations
9.
Cintas, Celia, et al.. (2021). Pattern detection in the activation space for identifying synthesized content. Pattern Recognition Letters. 153. 207–213. 3 indexed citations
10.
11.
Yang, Mochen, Edward McFowland, Gordon Burtch, & Gediminas Adomavičius. (2019). Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem. SSRN Electronic Journal. 1 indexed citations
12.
Cintas, Celia, et al.. (2019). Anomalous Pattern Detection in Activations and Reconstruction Error of Autoencoders. 1 indexed citations
13.
McFowland, Edward, et al.. (2018). Automated Local Regression Discontinuity Design Discovery. 1512–1520. 6 indexed citations
14.
Speakman, Skyler, et al.. (2015). Penalized Fast Subset Scanning. Journal of Computational and Graphical Statistics. 25(2). 382–404. 16 indexed citations
15.
Speakman, Skyler, Edward McFowland, & Daniel B. Neill. (2014). Scalable Detection of Anomalous Patterns With Connectivity Constraints. Journal of Computational and Graphical Statistics. 24(4). 1014–1033. 26 indexed citations
16.
Neill, Daniel B., et al.. (2012). Fast subset scan for multivariate event detection. Statistics in Medicine. 32(13). 2185–2208. 29 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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