Daniel Russo

2.2k citations
66 papers · 1.2k · 1 hit paper · h-index 18

Impact in

Papers in

Daniel Russo

63 papers receiving 1.2k citations

Daniel Russo's Hit Papers

Navigating the Complexity of Generative AI Adoption in Software Engineering 2024 · 74 citations
740+1Years since publication204060

Peers

Daniel Russo
Comparison fields: 5 of 129
  • Computer Science Applications 156
  • Information Systems 384
  • Management Information Systems 152
  • Energy Engineering and Power Technology 49
  • Software 59
Replace Lorna Uden with:
Lorna Uden United Kingdom
Ning Nan China
Marcos Kalinowski Brazil
Katia Romero Felizardo Brazil
Timothy J. Ellis United States
Markku Tukiainen Finland
Xia Feng China
Ira Monarch United States
Edna Dias Canedo Brazil
Anne Cleven Switzerland
Daniel Russo relative to Lorna Uden United Kingdom Lorna Uden's profile →
Citations per field
00.5×4.9×
Lorna Uden · 1×
Citations per year

Countries citing papers authored by Daniel Russo

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Russo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Russo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Russo Line = papers co-authored together Daniel Russo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 66 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021139
2 2021119
3 2020104
4
Navigating the Complexity of Generative AI Adoption in Software Engineering
Hit paper breakdown →
202474
5 202174
6 202040
7
Controlling Bias in Adaptive Data Analysis Using Information Theory
201538
8 202138
9 202237
10 202235
11 197933
12 202227
13 201627
14 202224
15 201724
16 201923
17 201818
18 202417
19 200517
20 201916

About Daniel Russo

Daniel Russo is a scholar working on Information Systems, Management Information Systems, Computer Science Applications, Artificial Intelligence and Electrical and Electronic Engineering, having authored 66 papers that have together received 1.2k indexed citations. Recurring topics across this work include Software Engineering Techniques and Practices (22 papers), Software Engineering Research (16 papers), Integrated Energy Systems Optimization (6 papers), Open Source Software Innovations (5 papers), Teaching and Learning Programming (5 papers), Big Data and Business Intelligence (4 papers), Water-Energy-Food Nexus Studies (4 papers) and Online Learning and Analytics (3 papers). The work is most often cited by research in Computer Science Applications (156 citations), Information Systems (384 citations), Management Information Systems (152 citations), Energy Engineering and Power Technology (49 citations) and Software (59 citations). Daniel Russo has collaborated with scholars based in Italy, Denmark and United States. Frequent co-authors include Klaas-Jan Stol, Paolo Ciancarini, Niels van Berkel, Paul H. P. Hanel, James Zou, Sebastian Sterl, Wim Thiery, Carolyn Brown, Ann van Griensven and Celray James Chawanda. Their work appears in journals such as ACM Transactions on Software Engineering and Methodology, Empirical Software Engineering, Journal of Systems and Software, IEEE Transactions on Software Engineering and Aquaculture.

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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