Linfeng Zhang

Mathematics Tower 430

231 W. 18th Ave.

Columbus, OH 43210

I am an assistant professor of Actuarial Science at the Ohio State University. I earned my Ph.D. degree in Mathematics with the concentration in Actuarial Science and Risk Analytics at the University of Illinois at Urbana-Champaign under the supervision of Dr. Runhuan Feng and Dr. Wing Fung (Alfred) Chong.

I worked at the Drake University, Iowa, as a visiting assistant professor of Actuarial Science during my last year of PhD study from Fall 2022 to Summer 2023.

Prior to my doctoral study, I worked as a research assistant at the Critical Infrastructure Resilience Institute and had three years of research experience in topics related to cyber risk and cyber insurance. During my doctoral program, I worked on several projects as a research assistant or a PI funded by the Society of Actuaries, the Fundación MAPFRE, and Cisco.

I published peer-reviewed academic papers about a variety of aspects of cyber risk in actuarial science, engineering, and law review journals, such as Geneva Papers on Risk and Insurance: Issues and Practice, IEEE Transactions on Emerging Topics in Computing, and Connecticut Insurance Law Journal. I am also working on other emerging topics in the field of actuarial science and risk management, such as pandemic risk and privacy risk.

selected publications

NLP-Powered Repository and Search Engine for Academic Papers: A Case Study on Cyber Risk Literature with CyLit

Linfeng Zhang, Changyue Hu, and Zhiyu Quan

North American Actuarial Journal 2024

Bib HTML

@article{cylit_naaj_2020,
  title = {NLP-Powered Repository and Search Engine for Academic Papers: A Case Study on Cyber Risk Literature with CyLit},
  volume = {0},
  copyright = {All rights reserved},
  issn = {1092-0277},
  doi = {10.1080/10920277.2024.2416903},
  language = {en},
  number = {0},
  journal = {North American Actuarial Journal},
  author = {Zhang, Linfeng and Hu, Changyue and Quan, Zhiyu},
  year = {2024},
  pages = {1--32}
}

Pandemic risk management: Resources contingency planning and allocation

Xiaowei Chen, Wing Fung Chong, Runhuan Feng, and Linfeng Zhang

Insurance: Mathematics and Economics 2021

Bib HTML

@article{chen_pandemic_2021,
  title = {Pandemic risk management: {Resources} contingency planning and allocation},
  volume = {101},
  copyright = {All rights reserved},
  issn = {01676687},
  shorttitle = {Pandemic risk management},
  doi = {10.1016/j.insmatheco.2021.08.001},
  language = {en},
  urldate = {2022-12-20},
  journal = {Insurance: Mathematics and Economics},
  author = {Chen, Xiaowei and Chong, Wing Fung and Feng, Runhuan and Zhang, Linfeng},
  year = {2021},
  pages = {359--383},
}

When Is a Cyber Incident Likely to Be Litigated and How Much Will It Cost? An Empirical Study

Jay P. Kesan, and Linfeng Zhang

Connecticut Insurance Law Journal 2020

Bib HTML

@article{kesan_when_2020,
  title = {When {Is} a {Cyber} {Incident} {Likely} to {Be} {Litigated} and {How} {Much} {Will} {It} {Cost}? {An} {Empirical} {Study}},
  volume = {27},
  copyright = {All rights reserved},
  shorttitle = {When {Is} a {Cyber} {Incident} {Likely} to {Be} {Litigated} and {How} {Much} {Will} {It} {Cost}?},
  journal = {Connecticut Insurance Law Journal},
  author = {Kesan, Jay P. and Zhang, Linfeng},
  year = {2020},
  pages = {529},
}

Analysis of Cyber Incident Categories Based on Losses

Jay P. Kesan, and Linfeng Zhang

ACM Transactions on Management Information Systems 2020

Bib HTML

@article{kesan_analysis_2020,
  title = {Analysis of {Cyber} {Incident} {Categories} {Based} on {Losses}},
  volume = {11},
  copyright = {All rights reserved},
  issn = {2158-656X, 2158-6578},
  doi = {10.1145/3418288},
  language = {en},
  number = {4},
  urldate = {2021-01-27},
  journal = {ACM Transactions on Management Information Systems},
  author = {Kesan, Jay P. and Zhang, Linfeng},
  year = {2020},
  pages = {1--28}
}

An Empirical Investigation of the Relationship between Local Government Budgets, IT Expenditures and Cyber Losses

J. P. Kesan, and Linfeng Zhang

IEEE Transactions on Emerging Topics in Computing 2019

Bib HTML

@article{kesan_empirical_2019,
  title = {An {Empirical} {Investigation} of the {Relationship} between {Local} {Government} {Budgets}, {IT} {Expenditures} and {Cyber} {Losses}},
  copyright = {All rights reserved},
  issn = {2168-6750, 2376-4562},
  doi = {10.1109/TETC.2019.2915098},
  urldate = {2021-01-27},
  journal = {IEEE Transactions on Emerging Topics in Computing},
  author = {Kesan, J. P. and Zhang, Linfeng},
  year = {2019},
  pages = {1--1}
}

Cyber risk and insurance for transportation infrastructure

Gina Tonn, Jay P. Kesan, Linfeng Zhang, and Jeffrey Czajkowski

Transport Policy 2019

Bib HTML

@article{tonn_cyber_2019,
  title = {Cyber risk and insurance for transportation infrastructure},
  volume = {79},
  copyright = {All rights reserved},
  issn = {0967070X},
  doi = {10.1016/j.tranpol.2019.04.019},
  language = {en},
  urldate = {2021-01-27},
  journal = {Transport Policy},
  author = {Tonn, Gina and Kesan, Jay P. and Zhang, Linfeng and Czajkowski, Jeffrey},
  year = {2019},
  pages = {103--114}
}

Reducing Informational Disadvantages to Improve Cyber Risk Management†

Sachin Shetty, Michael McShane, Linfeng Zhang, Jay P. Kesan, and 3 more authors

The Geneva Papers on Risk and Insurance - Issues and Practice 2018

Bib HTML

@article{shetty_reducing_2018,
  title = {Reducing {Informational} {Disadvantages} to {Improve} {Cyber} {Risk} {Management}†},
  volume = {43},
  copyright = {All rights reserved},
  issn = {1018-5895, 1468-0440},
  doi = {10.1057/s41288-018-0078-3},
  language = {en},
  number = {2},
  urldate = {2021-01-27},
  journal = {The Geneva Papers on Risk and Insurance - Issues and Practice},
  author = {Shetty, Sachin and McShane, Michael and Zhang, Linfeng and Kesan, Jay P. and Kamhoua, Charles A. and Kwiat, Kevin and Njilla, Laurent L.},
  year = {2018},
  pages = {224--238}
}

Epidemic Compartmental Models and Their Insurance Applications

Runhuan Feng, José Garrido, Longhao Jin, Sooie-Hoe Loke, and 1 more author

2022

Abs Bib HTML

Abstract Our society’s efforts to fight pandemics rely heavily on our ability to understand, model and predict the transmission dynamics of infectious diseases. Compartmental models are among the most commonly used mathematical tools to explain reported infections and deaths. This chapter offers a brief overview of basic compartmental models as well as several actuarial applications, ranging from product design and reserving of epidemic insurance, to the projection of healthcare demand and the allocation of scarce resources. The intent is to bridge classical epidemiological models with actuarial and financial applications that provide healthcare coverage and utilise limited healthcare resources during pandemics.
@incollection{boado-penas_epidemic_2022, address = {Cham}, title = {Epidemic {Compartmental} {Models} and {Their} {Insurance} {Applications}}, copyright = {All rights reserved}, isbn = {978-3-030-78333-4 978-3-030-78334-1}, url = {https://link.springer.com/10.1007/978-3-030-78334-1_2}, language = {en}, urldate = {2022-12-20}, booktitle = {Pandemics: {Insurance} and {Social} {Protection}}, publisher = {Springer International Publishing}, author = {Feng, Runhuan and Garrido, José and Jin, Longhao and Loke, Sooie-Hoe and Zhang, Linfeng}, editor = {Boado-Penas, María del Carmen and Eisenberg, Julia and Şahin, Şule}, year = {2022}, doi = {10.1007/978-3-030-78334-1_2}, note = {Series Title: Springer Actuarial}, pages = {13--40} }