Students

Former PhD students, graduation year, dissertation title, placement:

• Ruilong Yue, 2024. Global active subspace method. Wells Fargo, Charlotte.
  
  
• Alyssa Duan, 2023. Computational methods for estimating global sensitivity indices and Shapley values. Wells Fargo, Charlotte.
  
  
• Yiran Chen, 2022. Simulation and goodness-of-fit tests of copulas. Citi, Tampa.
  
  
• Arun Polala, 2020. Multilevel Monte Carlo and debiased Monte Carlo Methods in Financial Engineering. Wells Fargo, NYC.
  
  
• Jamie Fox, 2020. Applications of Polynomial Chaos to Monte Carlo Simulation. Wells Fargo, Charlotte.
  
  
• Nima Salehy, 2019. Belief Function Theory: Monte Carlo Methods and Applications to Stock Markets. Goldman Sachs, Dallas.
  
  
• Serdar Cellat, 2018. Metric Learning for Shape Classification: A Fast and Efficient Approach with Monte Carlo Methods. Amazon, Boston. (co-directed with Dr. Washington Mio)
  
  
• Jian Wang, 2017. Ensemble Methods for Capturing Dynamics of Limit Order Books. Byton, Santa Clara. (co-directed with Dr. Jinfeng Zhang)
  
  
• Yu-Ying Tzeng, 2017. Quasi-Monte Carlo and Markov Chain Quasi-Monte Carlo Methods in Estimation and Prediction of Time Series Models. Assistant Professor, Department of Risk Management and Insurance, National Cheng-Chi University, Taiwan. (co-directed with Dr. Paul Beaumont)
  
  
• David Mandel, 2017. Random Sobol' Sensitivity Analysis and Model Robustness. J.P. Morgan, NYC. (co-directed with Dr. Yousuff Hussaini)
  
  
• Linlin Xu, 2015. GPU Computing in Financial Engineering. Barclays, NYC.
  
  
• Wei Yuan, 2015. Estimating Sensitivities of Exotic Options Using Monte Carlo Methods. Wells Fargo, Charlotte. (co-directed with Dr. Kyounghee Kim)
  
  
• Nguyen Nguyet, 2014. Probabilistic methods in estimation and prediction of financial models. Assistant Professor of Mathematics, Youngstown State University.
  
  
• Yaning Liu, 2013. Nonintrusive Methods for Probabilistic Uncertainty Quantification and Global Sensitivity Analysis in Nonlinear Stochastic Phenomena. Postdoc, Lawrence Berkeley National Laboratory. (co-directed with Dr. Yousuff Hussaini)
  
  
• Wanwan Huang, 2013. Stochastic Modeling of Financial Derivatives. Assistant Professor of Mathematics, Roosevelt University. (co-directed with Dr. Brian Ewald)
  
  
• Ibukun Amusan, 2013. Parameter Estimation for a Stochastic Volatility Model with Coupled Additive and Multiplicative Noise. Assistant Professor of Mathematics, Kentucky State University. (co-directed with Dr. Brian Ewald)
  
  
• Ahmet Göncü, 2009. Monte Carlo and Quasi-Monte Carlo Methods in Financial Derivative Pricing. Assistant Professor of Mathematics, Xi’an Jiaotong - Liverpool University, China.
  
  
• Emmanuel Salta, 2008. Variance Reduction Techniques in Pricing Financial Derivatives. Wilshire Associates, Los Angeles.
  
  
• Manan Shah, 2008. Quasi-Monte Carlo and Genetic Algorithms with Applications to Endogenous Mortgage Rate Computation. Gaming Laboratories, New Jersey. (co-directed with Dr. Yevgeny Goncharov)

• Connor Jonston, 2023. Honors thesis: A Novel Monte Carlo Algorithm for Pricing Barier Options. PhD student in industrial engineering at UF.


• Chace Gordon, 2016. Honors thesis: Efficient Monte Carlo Simulation of Barrier Option Prices under the Jump-Diffusion Framework. MS student in finance at MIT.