Multidisciplinary Research and Education on Big Data + High-Performance Computing + Atmospheric Sciences

Part of NSF Initiative on Workforce Development for Cyberinfrastructure (CyberTraining)

Project Instructors

Dr. Jianwu Wang is an Assistant Professor at the Department of Information Systems, University of Maryland, Baltimore County (UMBC). His research interests include Big Data Analytics, Distributed Computing, Service Oriented Computing and Scientific Workflow. He has published 70+ papers with more than 1000 citations. He is an associate editor or editorial board member of four international journals, co-chair of three related workshops. He is also program committee member for over 30 conferences/workshops, and reviewer of over 15 journals or books. Since joining UMBC in 2015, he has received multiple grants as PI funded by NSF, NASA, DOE, State of Maryland, and Industry.

Dr. Matthias K. Gobbert works on numerical methods for PDEs, industrial mathematics, and in scientific and parallel computing, particularly on algorithms for modern architectures. He has over 60 publications including over 30 in peer-reviewed journals. Since 2010, led the creation of the UMBC High Performance Computing Facility (HPCF) in 2008, and is co-founder of the Center for Interdisciplinary Research and Consulting. He received the University System of Maryland Board of Regents Award for Excellence in Mentoring.

Dr. Zhibo Zhang, an atmospheric physicist, with a wide range of research interests in aerosol-cloud-radiation interactions, numerical simulation of radiative transfer, satellite remote sensing and climate modeling. Zhang has published more than 30 refereed journal articles and one book chapter. His research on Monte-Carlo simulation of radiative transfer in 3D cloud fields relies heavily on HPC. Zhang received the New (Early Career) Investigator award from NASA. In 2016, International Radiation Commission (IRC) selected Zhang for the IRC Young Scientist Award, which is usually given every 4 years to a single early career scientist who has made exceptional contributions to the fields of atmospheric radiation and remote sensing.

Dr. Aryya Gangopadhyay has published more than 90 refereed articles in the area of theoretical and applied machine learning. He has done multidisciplinary research with an emphasis on machine learning and big data analytics across domains such as geospatial applications, cybersecurity, material genomics, health IT and cyber-physical systems.