Two Master of Science in Data Science (MSDS) students presented posters at the University of Delaware Data Science Symposium on November 15, 2019. This event brought together data science faculty, students, researchers and practitioners from the University of Delaware and from across the region. Leaders and experts from government, academia and industry participated in the event.
Mu He, a second-year student in the MSDS program, presented a poster on the research topic of learning management systems in educational institutions that are used to predict student performance. By coupling the learning management system data and institutional data, he built several machine learning models based on dissimilar data sources. Afterward, a hybrid model was created by applying ensemble methods.
Abdul Qadir, a second-year student in the MSDS program, presented a poster on Machine-learning based multi-temporal radar image classification for monsoon crops using a cloud-computing platform. In this work, a machine-learning-based random forest (RF) classifier was applied for monsoon crop monitoring in India. For validation of the proposed method, stratified random samples were collected in a contiguous region composed of eight different agro-ecological areas in India.
The one-day symposium was organized and sponsored by the University of Delaware’s Data Science Institute. DSI director Cathy Wu (Edward G. Jefferson Chair of Bioinformatics & Computational Biology) and conference co-chairs Greg Dobler (Assistant Professor, School of Public Policy & Administration;) and Zachary Collier (DSI resident faculty and Assistant Professor, School of Education/CRESP) organized a packed event in the University of Delaware’s Audion in the STAR Tower.
The symposium was also attended by MSDS students Aashish Phatak, Desi Pilla, Farid Qamar, Soma Somasundaram and Vishruta Yawatkar. All of the MSDS students thought it was an exciting and fast-paced day, and all of us look forward to the next edition of the Delaware Data Science Symposium.