Fan is a PhD student of ECE Department at Rutgers University supervised by Prof. Manish Parashar. His current research focuses on building the programming and runtime support for enabling the execution of in-situ/in-transit scientific data processing workflow on emerging multi-core parallel architectures. Generally, Fan is interested in data management, programming framework for data analysis/processing on large scale HPC systems.
Moustafa AbdelBaky was a Ph.D. student at Rutgers University, an IBM Ph.D. Fellow, and an alumni of RDI2, TASSL, and NSFCAC. He completed his Ph.D. in Electrical and Computer Engineering and joined UC Berkeley as a Postdoctoral Scholar. Moustafa received his undergraduate degree from the Rutgers School of Engineering with a major in Electrical & Computer Engineering, and a major in Computer Science. He worked with IBM T.J. Watson Research Center on developing a framework that integrates IBM's Blue Gene supercomputer with public clouds, mobile and desktop peripherals to provide HPC as-a-service. He also worked on CometCloud, an autonomic cloud engine build on top of a robust and scalable overlay, which provides programming platforms (MapReduce, Workflow, Master/Worker/BOT) that run on dynamically federated HPC (HPC cluster, BlueGene/P) and Cloud infrastructure (Amazon EC2). Finally he worked on providing HPC as-a-service on all three levels (infrastructure, platform, and software as a service) using hybrid infrastructure such as Open Science Grid, Amazon EC2, Future Grid, and XSEDE. His past research experiences include DISCOVER, an interactive portal for interactive steering of scientific applications, using virtual reality for rehabilitation at the Human-Machine Interface Lab at Rutgers University in collaboration with Indiana University School of medicine, mobile development in collaboration with Bloomberg LP, experiments with Single Electron Transistors and nano technology at Rutgers University, and the development of ElVis (A Scientific Graphics for Visualization and Monitoring Software) in collaboration with Princeton's University Plasma Physics Laboratory.
He received both his Bachelors of Science and Masters of Science degree in Electrical & Computer Engineering from Rutgers School of Engineering.   His research interest are in parallel and distributed computing, cloud computing, data analysis and machine learning. He is currently working on trend analysis on abstract data. Currently using DOC (decentralized online clustering) to create data sets and imaging processing techniques for trend analysis.
Tong is a PhD candidate of ECE Department at Rutgers University, under the guidance of Prof. Manish Parashar. He is also a research assistant in The Applied Software Systems Laboratory (TASSL) and NSF Cloud and Autonomic Computing Center (CAC). Tong obtained his MS degree majoring in Computer Engineering in Rutgers University, USA, and BE degree in Nanjing University of Posts and Telecommunications, China. Tong's research interests are broadly in distributed and parallel computing, data intensive HPC system, cloud computing, and distributed wireless networked systems. His work has been featured in many presses like MIT Technical Review, HPCwire, CBC News, Discover Magazine, ACM Tech News, and NJ Star-ledger.

The National Science Foundation DARPA Dept of the Navy Science and Technology Department of Energy Department of Homeland Security

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