WHAT: TWed Talk: Thilanka Munasinghe on "Evaluating the Feasibility of Quantum Machine Learning Application Development Using NASA Earth Observational Data and US Census Bureau's Socioeconomic Datasets"
WHEN: 4p, Weds, 26 Mar 2025 (pizza et.al. 3:30p)
WHERE: Winslow 1140
WEBEX: https://rensselaer.webex.com/meet/erickj4
VIDEO: TBD
SLIDES: TBD
POSTER: https://ntrs.nasa.gov/citations/20240011142 (August 28, 2024)
EVENT PAGE: https://bit.ly/3FEjqYT
Thilanka Munasinghe will lead us in what promises to be a fascinating discussion on "Evaluating the Feasibility of Quantum Machine Learning Application Development Using NASA Earth Observational Data and US Census Bureau's Socioeconomic Datasets"
DESCRIPTION: Recent studies have shown the feasibility of applying Quantum Computing (QC) methods in diverse domains, spanning from manufacturing, engineering and pharmaceutical studies to weather and climate studies as well as human mobility and migration to evaluate the applicability of QC in those fields as a benchmark approach. This study explores the potential of using Quantum Machine Learning (QML) techniques on climate and weather data obtained from NASA Earth Observational satellites, county-to-county human migration data, and socioeconomic and demographic data obtained from the US Census Bureau. We used two QML algorithms, the Quantum Support Vector Classifier (QSVC) and the Variational Quantum Classifier (VQC) models, using the IBM Qiskit ML 0.7.2 ecosystem. We used an actual 127-Qubit IBM Quantum Computer (IBM 127-qubit Eagle) in this study and compared the results with classical ML models. The experiences gained from applying and evaluating quantum ML results on climate and weather data obtained from NASA satellites as a novel practical application of quantum computing.
BIO: Thilanka Munasinghe is the Lead Research Specialist at Future of Computing Institute (FOCI) at Rensselaer. He works on developing Quantum Machine Learning applications using RPI's 127-qubit IBM Quantum System One. From 2018-2024, Thilanka was a lecturer in Information Technology & Web Science (ITWS), where he developed and taught both graduate-level and undergraduate-level Data Science, Data Analytics, and Xinformatics (Informatics) courses, and the Web-Systems undergraduate course. https://idea.rpi.edu/people/staff/thilanka-munasinghe
Pizzas and salads will be delivered at approx. 3:30p; the talk will begin at 4p.