Hasan Güçlü

3.2k total citations · 1 hit paper
28 papers, 2.1k citations indexed

About

Hasan Güçlü is a scholar working on Modeling and Simulation, Economics and Econometrics and Computer Networks and Communications. According to data from OpenAlex, Hasan Güçlü has authored 28 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Modeling and Simulation, 5 papers in Economics and Econometrics and 4 papers in Computer Networks and Communications. Recurrent topics in Hasan Güçlü's work include COVID-19 epidemiological studies (7 papers), Pharmaceutical industry and healthcare (3 papers) and Complex Network Analysis Techniques (3 papers). Hasan Güçlü is often cited by papers focused on COVID-19 epidemiological studies (7 papers), Pharmaceutical industry and healthcare (3 papers) and Complex Network Analysis Techniques (3 papers). Hasan Güçlü collaborates with scholars based in United States, Türkiye and Taiwan. Hasan Güçlü's co-authors include Zoltán Toroczkai, V. S. Anil Kumar, Nan Wang, Madhav Marathe, Aravind Srinivasan, Stephen Eubank, Felicia Wu, David Galloway, William D. Wheaton and Donald S. Burke and has published in prestigious journals such as Nature, PLoS ONE and Scientific Reports.

In The Last Decade

Hasan Güçlü

26 papers receiving 2.0k citations

Hit Papers

Modelling disease outbreaks in realistic urban social net... 2004 2026 2011 2018 2004 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hasan Güçlü United States 13 828 614 379 281 275 28 2.1k
Nan Wang China 18 696 0.8× 601 1.0× 303 0.8× 230 0.8× 264 1.0× 104 2.3k
Paolo Bajardi Italy 18 849 1.0× 280 0.5× 463 1.2× 209 0.7× 451 1.6× 31 1.7k
Roni Rosenfeld United States 36 666 0.8× 274 0.4× 625 1.6× 180 0.6× 51 0.2× 134 5.5k
Luca Ferretti United Kingdom 24 1.0k 1.3× 138 0.2× 466 1.2× 178 0.6× 81 0.3× 78 3.1k
Michele Tizzoni Italy 24 1.1k 1.3× 304 0.5× 685 1.8× 232 0.8× 712 2.6× 55 2.3k
V. S. Anil Kumar United States 18 765 0.9× 643 1.0× 342 0.9× 248 0.9× 356 1.3× 39 2.8k
Laurent Hébert‐Dufresne United States 21 615 0.7× 719 1.2× 150 0.4× 302 1.1× 35 0.1× 87 1.7k
Sen Pei United States 24 2.0k 2.4× 608 1.0× 777 2.1× 393 1.4× 111 0.4× 116 4.3k
Chiara Poletto France 27 1.8k 2.1× 398 0.6× 677 1.8× 640 2.3× 229 0.8× 58 3.1k
Zi‐Ke Zhang China 31 320 0.4× 1.8k 2.9× 120 0.3× 410 1.5× 205 0.7× 108 3.9k

Countries citing papers authored by Hasan Güçlü

Since Specialization
Citations

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

Fields of papers citing papers by Hasan Güçlü

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hasan Güçlü

This figure shows the co-authorship network connecting the top 25 collaborators of Hasan Güçlü. A scholar is included among the top collaborators of Hasan Güçlü 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 Hasan Güçlü. Hasan Güçlü 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
2.
Güçlü, Hasan, et al.. (2022). Evaluation of the Association between Lumbar Spinal Stenosis and Lumbar Subcutaneous Fat Tissue Thickness by MRI: A Novel Perspective. Journal of College of Physicians And Surgeons Pakistan. 32(2). 147–151.
3.
Grantz, Kyra H., Derek A. T. Cummings, Shanta M. Zimmer, et al.. (2021). Age-specific social mixing of school-aged children in a US setting using proximity detecting sensors and contact surveys. Scientific Reports. 11(1). 2319–2319. 7 indexed citations
4.
Maral, İşıl, et al.. (2021). Evaluation of Non-Pharmaceutical Interventions for Reducing Contact Rate in COVID-19 Pandemic: R0 Estimation and Modeling for Istanbul. Mikrobiyoloji Bulteni. 55(3). 389–405. 3 indexed citations
5.
Ağırbaşlı, Mehmet, et al.. (2021). Can Hemogram Parameters Predict a Positive PCR Result in COVID-19?. Bangladesh Journal of Medical Science. 118–124. 1 indexed citations
6.
Chang, Chung‐Chou H., Haiden A. Huskamp, Walid F. Gellad, et al.. (2019). Association between physician adoption of a new oral anti-diabetic medication and Medicare and Medicaid drug spending. BMC Health Services Research. 19(1). 703–703. 1 indexed citations
7.
Kalcıoğlu, M. Tayyar, et al.. (2019). Ossicular chain erosion in chronic otitis media patients with cholesteatoma or granulation tissue or without those: analysis of 915 cases. European Archives of Oto-Rhino-Laryngology. 276(5). 1301–1305. 10 indexed citations
8.
Donohue, Julie M., Hasan Güçlü, Walid F. Gellad, et al.. (2018). Influence of peer networks on physician adoption of new drugs. PLoS ONE. 13(10). e0204826–e0204826. 41 indexed citations
9.
Ankaralı, Handan, et al.. (2018). Pain Threshold, Pain Severity and Sensory Effects of Pain in Fibromyalgia Syndrome Patients: A new scale study. Bangladesh Journal of Medical Science. 17(3). 342–350. 3 indexed citations
10.
Anderson, Timothy S., Wei‐Hsuan Lo‐Ciganic, Walid F. Gellad, et al.. (2017). Patterns and predictors of physician adoption of new cardiovascular drugs. Healthcare. 6(1). 33–40. 18 indexed citations
11.
Güçlü, Hasan, Jonathan M. Read, Charles J. Vukotich, et al.. (2016). Social Contact Networks and Mixing among Students in K-12 Schools in Pittsburgh, PA. PLoS ONE. 11(3). e0151139–e0151139. 19 indexed citations
12.
Güçlü, Hasan, Supriya Kumar, David Galloway, et al.. (2016). An Agent-Based Model for Addressing the Impact of a Disaster on Access to Primary Care Services. Disaster Medicine and Public Health Preparedness. 10(3). 386–393. 7 indexed citations
13.
Bocour, Angelica, et al.. (2016). Impact on Primary Care Access Post-Disaster: A Case Study From the Rockaway Peninsula. Disaster Medicine and Public Health Preparedness. 10(3). 492–495. 4 indexed citations
14.
Güçlü, Hasan, et al.. (2014). Aflatoxin Regulations and Global Pistachio Trade: Insights from Social Network Analysis. PLoS ONE. 9(3). e92149–e92149. 54 indexed citations
15.
Grefenstette, John J., Shawn T. Brown, Roni Rosenfeld, et al.. (2013). FRED (A Framework for Reconstructing Epidemic Dynamics): an open-source software system for modeling infectious diseases and control strategies using census-based populations. BMC Public Health. 13(1). 940–940. 154 indexed citations
16.
Wu, Felicia & Hasan Güçlü. (2013). Global Maize Trade and Food Security: Implications from a Social Network Model. Risk Analysis. 33(12). 2168–2178. 83 indexed citations
17.
Wu, Felicia & Hasan Güçlü. (2012). Aflatoxin Regulations in a Network of Global Maize Trade. PLoS ONE. 7(9). e45151–e45151. 124 indexed citations
18.
Güçlü, Hasan, et al.. (2010). Ad-hoc limited scale-free models for unstructured peer-to-peer networks. Peer-to-Peer Networking and Applications. 4(2). 92–105. 7 indexed citations
19.
Güçlü, Hasan, et al.. (2007). Proximity Networks and Epidemics. Bulletin of the American Physical Society. 1 indexed citations
20.
Eubank, Stephen, Hasan Güçlü, V. S. Anil Kumar, et al.. (2004). Modelling disease outbreaks in realistic urban social networks. Nature. 429(6988). 180–184. 1387 indexed citations breakdown →

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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