Uncertainty quantification is used to determine how uncertainties in data affect a model. There are many different ways to quantify uncertainty. Choosing the correct method of quantification can be tough because there are many different factors. The different methods of quantification share similar operations. However, using the correct method can be complicated and is time-consumingContinue reading “Simplifying and Improving Uncertainty Quantification with UM-Bridge”
Joseph Coco
From Speedy Simulations to Trustworthy AI: Undergraduates Take on Research Challenges at Illinois Tech for the Summer
A dozen students from across the United States have been chosen for the 10-week Summer Undergraduate Research Experience (SURE) program at the Illinois Institute of Technology. The SURE program offers opportunities for conducting research in computational mathematics and data science. The students worked on one of the five different research topics. One group worked withContinue reading “From Speedy Simulations to Trustworthy AI: Undergraduates Take on Research Challenges at Illinois Tech for the Summer”
Innovative Investment Tool Qualifies Students for International Hackathon
Three Illinois Tech students, Narges Hosseinzadeh (M.S. Applied Mathematics 2023), Kan Zhang (Ph.D. Applied Mathematics 2023), and Thi Truong (Applied Mathematics 2023), worked together with Olivia Martin, a data science student from Northwestern, as well as Vasilios Farmak, a software and data engineer from Greece. The team was guided by Sou-Cheng Terrya Choi, Research AssociateContinue reading “Innovative Investment Tool Qualifies Students for International Hackathon”
QMCPY talks at the 14th International Conference on Monte Carlo Methods and Applications
The conference covers a wide range of topics related to Monte Carlo methods, including traditional areas such as computational statistical physics, Quasi Monte Carlo methods, and Markov Chain Monte Carlo in high dimensions. It also addresses emerging topics such as generative models, experimental design in Uncertainty Quantification, Monte Carlo simulations and High-Performance Computing, reinforcement learningContinue reading “QMCPY talks at the 14th International Conference on Monte Carlo Methods and Applications”
Open Source Software: An Important Tool for Advancing Science
Join us for a special event presented by Open Source Science (OSSci) and sponsored by ChiPy, as we explore the transformative power of open source in scientific research and discovery. In collaboration with PyData Chicago, this event brings together scientists and open-source developers to address the unique challenges faced by the scientific community and unlockContinue reading “Open Source Software: An Important Tool for Advancing Science”
Boosting Numerical Efficiency with Low Discrepancy Sampling: Enhancing Estimation and Integration in Diverse Fields from Fred Hickernell and the QMCPy Library
This talk will discuss how low discrepancy sampling can improve the efficiency of estimating an expectation or integral, which is an important topic in various fields such as high energy physics, Bayesian inference, image rendering, quantitative finance, and uncertainty quantification. The talk will emphasize low discrepancy sampling and its ability to improve the efficiency ofContinue reading “Boosting Numerical Efficiency with Low Discrepancy Sampling: Enhancing Estimation and Integration in Diverse Fields from Fred Hickernell and the QMCPy Library”
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”