World's Best Scientists 2026 revealed!
Gordon E. Willmot

Gordon E. Willmot

D-Index & Metrics

Mathematics

D-Index
40
Citations
8892
World Ranking
2011
National Ranking
76

Overview

Gordon E. Willmot is affiliated with the University of Waterloo in Canada. Their research spans multiple areas within decision sciences, with a concentration on probability, risk models, and statistical distribution estimation. Willmot's work also touches on topics related to risk and portfolio optimization, health systems and economic evaluations, decision-making and behavioral economics, Bayesian methods and mixture models, as well as insurance, mortality, demography, and risk management.

The scientist has contributed to several publication venues, including:

  • Mathematics of Operations Research
  • Scandinavian Actuarial Journal
  • Applied Mathematics and Computation
  • Insurance Mathematics and Economics

Among the recent papers featuring Gordon E. Willmot as an author are:

  • "Remarks on a generalized inverse Gaussian type integral with applications," 2022, Applied Mathematics and Computation

Other papers listing Willmot as an author or co-author include:

  • "Characterization, Robustness, and Aggregation of Signed Choquet Integrals," 2020, Mathematics of Operations Research
  • "Finite-time ruin probabilities using bivariate Laguerre series," 2022, Scandinavian Actuarial Journal
  • "IME's Editorial Board," 2023, Insurance Mathematics and Economics

Frequent co-authors collaborating with Gordon E. Willmot are:

  • Jae-Kyung Woo
  • Ruodu Wang
  • Yunran Wei
  • Eric C.K. Cheung
  • Hayden Lau

Willmot's main fields of study encompass decision sciences, specifically within management science and operations research, statistics and probability, economics and econometrics, general decision sciences, and artificial intelligence. Their work integrates methodological approaches from these disciplines to address practical and theoretical questions in areas such as risk, optimization, and economic evaluation.

Best Publications

  • Loss Models: From Data to Decisions

    Stuart A. Klugman;Harry H. Panjer;Gordon E. Willmot

  • Insurance risk models

    Patrick L. Brockett;Harry H. Panjer;Gordon E. Willmot

  • Lundberg Approximations for Compound Distributions with Insurance Applications

    Gordon E. Willmot;X. Sheldon Lin

  • The classical risk model with a constant dividend barrier: analysis of the Gerber–Shiu discounted penalty function

    X. Sheldon Lin;Gordon E. Willmot;Steve Drekic

  • The Poisson-Inverse Gaussian distribution as an alternative to the negative binomial

    Gordon E. Willmot

  • Analysis of a defective renewal equation arising in ruin theory

    X.Sheldon Lin;Gordon E. Willmot

  • A mixed poisson–inverse‐gaussian regression model

    C. Dean;J. F. Lawless;G. E. Willmot

  • The moments of the time of ruin, the surplus before ruin, and the deficit at ruin

    X.Sheldon Lin;Gordon E. Willmot

  • Ruin probabilities in the compound binomial model

    Gordon E. Willmot

  • A generalized defective renewal equation for the surplus process perturbed by diffusion

    Cary Chi-Liang Tsai;Gordon E. Willmot

  • On the Class of Erlang Mixtures with Risk Theoretic Applications

    Gordon E. Willmot;Jae-Kyung Woo

  • THE DENSITY OF THE TIME TO RUIN IN THE CLASSICAL POISSON RISK MODEL

    David C.M. Dickson;Gordon E. Willmot

  • On the discounted penalty function in the renewal risk model with general interclaim times

    Gordon E. Willmot

  • Sundt and Jewell's Family of Discrete Distributions

    Gordon Willmot

  • Loss Models: From Data to Decisions, 2nd edition

    Stuart A. Klugman;Harry H. Panjer;Gordon E. Willmot

  • Structural properties of Gerber-Shiu functions in dependent Sparre Andersen models

    Eric C.K. Cheung;David Landriault;Gordon E. Willmot;Jae-Kyung Woo

  • Mixed Compound Poisson Distributions

    Unknown

  • On recursive evaluation of mixed poisson probabilities and related quantities

    Gordon E. Willmot

  • The discrete stationary renewal risk model and the Gerber-Shiu discounted penalty function

    Kristina P. Pavlova;Gordon E. Willmot

  • The Gerber-Shiu discounted penalty function in the stationary renewal risk model

    Gordon E. Willmot;David C.M. Dickson

  • On the Gerber–Shiu discounted penalty function in the Sparre Andersen model with an arbitrary interclaim time distribution

    David Landriault;Gordon Willmot

Frequent Co-Authors

Qihe Tang
Qihe Tang University of New South Wales
Hailiang Yang
Hailiang Yang University of Hong Kong
Patrick L. Brockett
Patrick L. Brockett The University of Texas at Austin
Jan Dhaene
Jan Dhaene KU Leuven

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For students interested in expanding their career options alongside a Mathematics degree, exploring related online degrees can be a strategic move. Many professionals transition into business roles by pursuing an MBA, and knowing whether you can transfer credits into an MBA program can save time and money during this transition.

Another valuable pathway is a master in data analytics. This degree complements mathematical skills by focusing on extracting insights from data, a highly sought-after expertise in today’s job market.

For those concerned about admission hurdles, there are easiest MBA programs designed for quicker entry, providing more accessible options for busy students or working professionals.

Additionally, if flexibility is paramount, exploring the easiest online MBA programs can offer a convenient way to advance education while balancing other responsibilities.

Choosing the right online degree aligned with mathematics can open diverse career pathways in business, analytics, and technology, making this a crucial consideration for any student planning their future.

Best Scientists Citing Gordon E. Willmot

Trending Scientists