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Welcome to the Big Data Analytics Lab (BDAL)

In big data era, many traditional data analytics tasks need scalable solutions and many new opportunities appear. Our lab studies different aspects of big data analytics, including scalable causality analytics, scalable data aggregation and anomaly detection, with current application focuses on climate and manufacturing. We integrate techniques in distributed computing, data mining and machine learning. We work with academic and industry collaborators to achieve multidisciplinary research and social impacts.

Looking for Students!

Our lab is looking for undergraduate, master, Ph.D. and visiting students to work on big data analytics related research through volunteering, independent study, hourly paid position and Research Assistant. Please contact our lab’s director, Dr. Jianwu Wang, if you are interested.

News

  • 2024/06: Congratulations to, Dr. Sahara Ali, for defending her PhD thesis successfully. Her thesis title: Spatiotemporal Forecasting and Causality Methods for Arctic Amplification. As the 6th graduated PhD student from our lab, Dr. Ali will join the Department of Information Science at University of North Texas (UNT) as an Assistant Professor this Fall.
  • 2024/05: Two papers accepted by the ECML-PKDD 2024 conference. More at Publications.
  • 2024/05: Congratulations to lab PhD students, Seraj Mostafa and Francis Nji for receiving poster awards at the college’s 2024 Research Day.
  • 2023/10: Dr. Wang received a new grant from National Science Foundation (NSF) on Big Data REU Site. More at https://bigdatareu.umbc.edu/
  • 2023/07: Congratulations to, Dr. Xin Huang, for defending his PhD thesis successfully. His thesis title: Deep Learning based Cloud Retrieval Techniques using Multiple Satellite Remote Sensing Data. As the 5th graduated PhD student from our lab, Dr. Huang will join the Department of Computer and Information Sciences at Towson University as an Assistant Professor this Fall.
  • 2022/08: Dr. Wang received a new sub-grant from Lawrence Livermore National Laboratory (LLNL) to work on Multivariate Atmospheric Data Clustering for Studying Aerosol-cloud Interactions.
  • 2022/07: Dr. Wang received a new grant from National Science Foundation (NSF) to provide Student Travel Awards for students to attend the 9th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT 2022) and the 15th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2022).
  • 2022/07: Congratulations to Xingyan Li, our PhD student, for receiving one year graduate fellowship from the Goddard Earth Sciences Technology and Research (GESTAR) II. She will conduct research on Deep Learning based Cloud Mask Retrieval for the Future NASA PACE Mission in collaboration with NASA scientists.
  • 2022/05: Congratulations to, Dr. Xin (Starly) Wang, for defending her PhD thesis successfully. Her thesis title: Secure, Reproducible And Adaptive Machine Learning In Distributed Systems.
  • 2022/01: Our lab received a new interdisciplinary research grant from NASA to conduct machine learning based automatic detection of upper atmosphere gravity waves from NASA satellite images.
  • 2021/12: Congratulations to, Dr. Pei Guo (PhD’21) from our lab, for being a finalist of the BenchCouncil Distinguished Doctoral Dissertation Award.
  • 2021/11: Congratulations to, Sahara Ali, our PhD student, who will be an ESIP Community Fellow and help bridge the gap between informatics and Earth science
  • 2021/10: UMBC to lead climate-focused NSF data science institute through $13M award

Acknowledgement

We acknowledge the research funding from federal agencies, state, university and industry, including: National Science Foundation (NSF), Army Research Lab (ARL), National Aeronautics and Space Administration (NASA), Department of Energy (DOE), Earth Science Information Partners (ESIP), State of Maryland, UMBC, Amazon and Microsoft.