Combining the expertise of the StaSASticians and a commitment to ESG principles to deliver comprehensive wealth management and investment.

The StaSASticians are a group of five people who created an innovative solution for better investing during the SAS hackathon. Three students from IIT applied mathematics, Narges, Kan, and Thi, were part of the group. Their solution simplifies investment for both institutions and individuals. Their user-friendly application enables responsible and profitable investments by filtering companiesContinue reading “Combining the expertise of the StaSASticians and a commitment to ESG principles to deliver comprehensive wealth management and investment.”

Illinois Tech receives NSF grant to offer intensive summer research program in computational mathematics and data science for undergraduates

Illinois Institute of Technology has secured a grant from the National Science Foundation’s Research Experiences for Undergraduates program to allow students across the country to participate in an intensive summer research project. The grant will allow ten undergraduate students to spend ten weeks working on computational mathematics and data science research projects on the IllinoisContinue reading “Illinois Tech receives NSF grant to offer intensive summer research program in computational mathematics and data science for undergraduates”

QMCPy Events Coming Soon

Our team is excited to announce that we will be presenting on QMCPy at the following upcoming events SAMO 2022: The Tenth International Conference on Sensitivity of Model Output. March 14 – 16, 2022.  2022 CORS/INFORMS International Conference. June 5 – 8, 2022. MCQMC 2022: The 15th International Conference on Monte Carlo and Quasi-Monte CarloContinue reading “QMCPy Events Coming Soon”

Quasi-Monte Carlo Software Article

We recently uploaded an article on Quasi-Monte Carlo Software to https://arxiv.org/abs/2102.07833. Abstract: Practitioners wishing to experience the efficiency gains from using low discrepancy sequences need correct, well-written software. This article, based on our MCQMC 2020 tutorial, describes some of the better quasi-Monte Carlo (QMC) software available. We highlight the key software components required to approximateContinue reading “Quasi-Monte Carlo Software Article”

QMCPy Version 1.0

The developers of QMCPy are happy to announce the release of version 1.0 on February 12, 2021, Chinese New Year! We would like to thank all those who have made this development possible. A special thank you to Developers: Sou-Cheng T. Choi, Fred J. Hickernell, Michael McCourt, Jagadeeswaran Rathinavel, and Aleksei Sorokin; Collaborators: Mike Giles,Continue reading “QMCPy Version 1.0”