The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Cornelis W. Oosterlee sits on this spectrum.
This scientist: 287 publications — 84th percentile
84% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 537 publications or more.
The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Cornelis W. Oosterlee sits on this spectrum.
This scientist: 48 D-Index — 67th percentile
67% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 86 D-Index or more.
Cornelis W. Oosterlee is affiliated with Utrecht University in the Netherlands. Their research primarily intersects the fields of Economics, Econometrics, and Finance, with a focus on topics that include stochastic processes and financial applications, model reduction and neural networks, financial risk and volatility modeling, credit risk and financial regulations, insurance, mortality, demography, and risk management, fluid dynamics and turbulent flows, as well as probabilistic and robust engineering design.
Oosterlee's scholarly output spans various publication venues where they have contributed multiple works. Frequent venues for their research include:
Key recent papers from Oosterlee and their coauthors reflect an emphasis on computational methods, neural networks, and applications to financial mathematics and pattern recognition. Selected recent works include:
Their collaboration network includes frequent coauthors such as Lech A. Grzelak, Pasquale Cirillo, Luis Antonio Souto Arias, Shuaiqiang Liu, and Nikolaj T. Mücke, indicating a multidisciplinary approach and engagement with diverse research communities.
The scientific topics addressed in Oosterlee's work show a strong orientation towards integrating advanced mathematical methods and neural network techniques into financial and engineering contexts. The range of subfields covered includes:
Overall, Oosterlee's research portfolio demonstrates an emphasis on quantitative modeling, the application of computational algorithms to partial differential equations, machine learning methods, and their utilization in finance and risk management. This is reflected across a substantial number of publications and sustained collaboration within the research community.
F. Fang;C. W. Oosterlee
Anastasia Borovykh;Sander Bohte;Cornelis W. Oosterlee
Y. A. Erlangga;C. W. Oosterlee;C. Vuik
Y. A. Erlangga;C. Vuik;C. W. Oosterlee
R. Lord;F. Fang;F. Bervoets;C. W. Oosterlee
F. Fang;C. W. Oosterlee
Lech A. Grzelak;Cornelis W. Oosterlee
P. Wesseling;C. W. Oosterlee
Ariel Almendral;Cornelis W. Oosterlee
C.W. Oosterlee
Fang Fang;Cornelis W. Oosterlee
Shuaiqiang Liu;Cornelis W. Oosterlee;Sander M. Bohte
Marjon Ruijter;Cornelis Oosterlee
Anastasia Borovykh;Sander Bohte;Cornelis W. Oosterlee
Remco van der Meer;Cornelis W. Oosterlee;Anastasia Borovykh
Y. A. Erlangga;C. Vuik;C. W. Oosterlee
A. Segal;P. Wesseling;J. Van Kan;C. W. Oosterlee
Shuaiqiang Liu;Anastasia Borovykh;Lech A. Grzelak;Cornelis W. Oosterlee;Cornelis W. Oosterlee
C. D. Riyanti;A. Kononov;Y. A. Erlangga;C. Vuik
C.W. Oosterlee;P. Wesseling;A. Segal;E. Brakkee
Bowen Zhang;Cornelis W. Oosterlee
C. W. Oosterlee;T. Washio
Anthonie W. Van Der Stoep;Lech A. Grzelak;Cornelis W. Oosterlee
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