Welcome to the Online Interdisciplinary Big Data Analytics in Science and Engineering REU (Research Experience for Undergraduates) Site program at UMBC. This Big Data REU program is funded by NSF in 2021 to conduct undergraduate research training in 2021-2023.
This REU Site program will provide 8-week summer online research experiences to undergraduates on how to utilize modern data science and high-performance computing (HPC) techniques to process and analyze big data in many science and engineering disciplines such as Atmospheric Science, Mechanical Engineering, and Medicine.
The REU Site program will be conducted purely online to allow students to conduct research without traveling and work with experts nationwide. In recent years, astronomical growth of available datasets in many science and engineering disciplines often requires big data analytics techniques to efficiently and effectively process the large datasets and gain knowledge from them. The program will help students identify frontier research challenges when facing big data in science and engineering, and guide students to conduct research to tackle the research challenges using advanced cyberinfrastructure software technologies (big data, distributed machine/deep learning, HPC, etc.) and hardware resources (including big data cluster, CPU cluster and GPU cluster). The program will provide development of the national workforce in areas of critical need on “Data + Computing + X”.
The application for Summer 2023 is open. To receive full consideration, please submit your application before 03/01/2023. More at Summer 2023 Tab. Flyer for summer 2023 program.. We plan to notify the results around 03/31/2023.
Each participant who successfully finishes the program and completes all requirements will receive $5,000 stipend and support to conference traveling to present his/her research.
The training will leverage experiences from two previous related efforts: 1) High-Performance Computing (HPC) REU Site at UMBC from 2010 to 2017, 2) Online training on big data + HPC + atmospheric sciences at UMBC from 2018 to 2020.
- 2022/11: The application for Summer 2023 is open. More at Summer 2023 Tab. Flyer for summer 2023 program.
- 2022/11: Our 2022 REU participants, Jorge López González, Kathryn Chen, Nithya Navarathna and Joseph Clark, received travel award from the 9th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT 2022).
- 2022/10: The extended version of our 2022 REU team 2’s technical report, titled “Multi-Layer Recurrent Neural Networks for the Classification of Compton Camera Based Imaging Data for Proton Beam Cancer Treatment”, is accepted by the 2022 National Symposium for NSF REU Research in Data Science, Systems, and Security (REU 2022 Symposium).
- 2022/10: The extended version of our 2022 REU team 1’s technical report, titled “Atmospheric Gravity Wave Detection Using Transfer Learning Techniques”, is accepted by the 9th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT 2022).
- 2021/10: Our 2021 REU participant, Eliot Kim, received travel award for 2021 REU team 1’s publication at 2021 IEEE International Conference on Big Data (BigData 2021).
- 2021/11: The extended version of our 2021 REU team 2’s technical report, titled “Promising Hyperparameter Configurations for Deep Fully Connected Neural Networks to Improve Image Reconstruction in Proton Radiotherapy”, is accepted by the 2021 National Symposium for NSF REU Research in Data Science, Systems, and Security (REU 2021 Symposium).
- 2021/10: The extended version of our 2021 REU team 1’s technical report, titled “Multi-Task Deep Learning Based Spatiotemporal Arctic Sea Ice Forecasting”, is accepted by the 2021 IEEE International Conference on Big Data (BigData 2021).
The program is funded by the grant REU Site: Online Interdisciplinary Big Data Analytics in Science and Engineering (grant no. OAC-2050943) from the National Science Foundation (NSF).