Dan Lo

953 total citations
73 papers, 597 citations indexed

About

Dan Lo is a scholar working on Information Systems, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Dan Lo has authored 73 papers receiving a total of 597 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Information Systems, 31 papers in Artificial Intelligence and 26 papers in Computer Networks and Communications. Recurrent topics in Dan Lo's work include Advanced Malware Detection Techniques (24 papers), Network Security and Intrusion Detection (14 papers) and Spam and Phishing Detection (8 papers). Dan Lo is often cited by papers focused on Advanced Malware Detection Techniques (24 papers), Network Security and Intrusion Detection (14 papers) and Spam and Phishing Detection (8 papers). Dan Lo collaborates with scholars based in United States, China and Italy. Dan Lo's co-authors include Kai Qian, Jing He, Hossain Shahriar, Ying Xie, Md Jobair Hossain Faruk, Ying Qian, Lixin Tao, Mohammad Masum, Fan Wu and Michael E. Whitman and has published in prestigious journals such as Nanotechnology, Land Use Policy and Brain Sciences.

In The Last Decade

Dan Lo

64 papers receiving 561 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dan Lo United States 12 317 291 283 158 63 73 597
Shahrulniza Musa Malaysia 14 386 1.2× 322 1.1× 146 0.5× 265 1.7× 71 1.1× 71 716
Krzysztof Cabaj Poland 13 449 1.4× 324 1.1× 392 1.4× 205 1.3× 62 1.0× 48 704
Quang Do United States 15 184 0.6× 253 0.9× 196 0.7× 392 2.5× 74 1.2× 29 802
Romain Rouvoy France 15 381 1.2× 439 1.5× 99 0.3× 271 1.7× 147 2.3× 78 722
Răzvan Beuran Japan 14 519 1.6× 238 0.8× 140 0.5× 67 0.4× 175 2.8× 72 747
Lotfi Ben Othmane United States 13 169 0.5× 386 1.3× 72 0.3× 199 1.3× 56 0.9× 31 582
Saad Khan United Kingdom 11 304 1.0× 247 0.8× 88 0.3× 177 1.1× 66 1.0× 41 580
Gary C. Kessler United States 13 183 0.6× 366 1.3× 256 0.9× 104 0.7× 58 0.9× 63 693

Countries citing papers authored by Dan Lo

Since Specialization
Citations

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

Fields of papers citing papers by Dan Lo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dan Lo

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

All Works

20 of 20 papers shown
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Shi, Yong, Hossain Shahriar, Dan Lo, et al.. (2023). Secure Software Development in Google Colab. 1. 398–402. 1 indexed citations
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Shahriar, Hossain, et al.. (2023). Quantum Machine Learning for Security Data Analysis. 460–465. 1 indexed citations
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Masum, Mohammad, Hossain Shahriar, Maria Valero, et al.. (2022). Scalable Machine Learning Using PySpark. 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC). 454–455. 3 indexed citations
7.
Lo, Dan, Hossain Shahriar, Kai Qian, Michael E. Whitman, & Fan Wu. (2021). Colab Cloud Based Portable and Shareable Hands-on Labware for Machine Learning to Cybersecurity. 2021 IEEE International Conference on Big Data (Big Data). 3311–3315. 1 indexed citations
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Lo, Dan, et al.. (2019). Tiered Financial Fraud Detection Utilizing Precision Stratified Random Forest Assembly. 57. 254–257. 1 indexed citations
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Lo, Dan, et al.. (2019). Big Data Analysis on Social Networking. 6220–6222. 4 indexed citations
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Lo, Dan, et al.. (2019). Subject-Oriented Data Retrieval and Analysis on Sina Weibo. 4431–4434. 1 indexed citations
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Qian, Kai, Dan Lo, Reza M. Parizi, et al.. (2018). Authentic Learning Secure Software Development (SSD) in Computing Education. 1–9. 11 indexed citations
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Hong, Liang, et al.. (2017). Strong Security Approach with Compromised Nodes Detection in Cognitive Radio Sensor Networks. International Journal of Networking and Computing. 7(1). 50–68. 1 indexed citations
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Lo, Dan, et al.. (2017). The Impact of Defensive Programming on I/O Cybersecurity Attacks. 102–111. 4 indexed citations
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Lo, Dan, et al.. (2017). Binary malware image classification using machine learning with local binary pattern. 4664–4667. 58 indexed citations
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Lo, Dan, et al.. (2015). Internet of Things-Based Temperature Tracking System. 13 indexed citations
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Qian, Kai, et al.. (2015). Spam filtering using Association Rules and Naïve Bayes Classifier. 638–642. 8 indexed citations
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Lo, Dan, Max M. North, & Sarah North. (2014). Hardware Components in Cybersecurity Education. DigitalCommons - Kennesaw State University (Kennesaw State University). 1(1). 30. 1 indexed citations
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Li, Keqin, et al.. (2013). Energy-efficient task scheduling algorithms on heterogeneous computers with continuous and discrete speeds. Sustainable Computing Informatics and Systems. 3(2). 109–118. 15 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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