Dantong Yu joined Brookhaven National Lab in 2001, and coordinated the Grid computing group at BNL. He currently leads the computer science group at the Computational Science Center. His research interests include high-speed network performance, network qualify of service, cluster/grid Computing, information retrieval, data mining, database, and data warehouse. He designed and implemented a novel high-dimensional indexing algorithm (termed ClusterTree) using the semantics of datasets. He has published papers in leading technical journal and conferences. He initiated and led the high performance network provision effort to bring cutting-edge network technologies into the big data management for science applications. He served in the review Panels of NSF CDI, DOE Early Career Principle Investigator for networking research and DOE Small Business Innovative Research (SBIR) and co-chair of several DOE Advanced Networking Workshops for Distributed Petascale Science.
Renewable energy research, data mining, data analyze, distributed data mining algorithm design, distributed workflow and data management systems, software defined networks, high performance data transfer, and photon science X-ray image reconstruction and processing.
2009 - Present, Brookhaven National Laboratory, Computer Science Lead
2001 - 2009, Brookhaven National Laboratory, Group Manager and Project Lead
Y. Ren, T. Li, D. Yu, S. Jin, T.G. Robertazzi, Design and Testbed Evaluation of RDMA-based Middleware for High-performance Data Transfer Applications, Accepted by Journal of Systems and Software, 2013.
X. Liu, C. Qiao, D. Yu and T. Jiang, "Application-Specific Resource Provisioning for Wide-Area Distributed Computing", IEEE Networks, SI on "Future Internet: New Applications and Emerging Services", Volume 24, February, 2010.
M.A. Moges, D. Yu, T.G. Robertazzi, “Grid scheduling divisible loads from two sources”, Computers and Mathematics with Applications, 1081-1092, 58, 2009.
D. Yu and A. Zhang, “ClusterTree: Integration of Cluster Representation and Nearest Neighbor Search for Large Datasets with High Dimensionality”, IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume 15, Number 5, September 2003.
D. Yu, G. Sheikholeslami, and A. Zhang, “FindOut: Finding Outliers in Very Large Datasets”, Knowledge and Information Systems (KAIS), An International Journal, Volume 4, Number 4, pp.387-412, October 2002.
Y. Ren, T. Li, D. Yu, S. Jin, T.G. Robertazzi, B. Tierney, E. Pouyoul: Protocols for wide-area data-intensive applications: design and performance issues. ACM/IEEE SuperComputing 2012.
H. Huang, H. Qin, S. Yoo, D. Yu: Local anomaly descriptor: a robust unsupervised algorithm for anomaly detection based on diffusion space. 21st ACM International Conference on Information and Knowledge Management (CIKM 2012).
Hao Huang, Hong Qin, Shinjae Yoo, Dantong Yu: A New Anomaly Detection Algorithm Based on Quantum Mechanics, International Conference on Data Mining (ICDM), 2012.
S. Sharma, D. Katramatos, D. Yu, L. Shi: Design and implementation of an intelligent end-to-end network QoS system. ACM/IEEE Supercomputing 2012.
Huang, H., Yoo, S., Qin, H., and Yu, D., A Robust Clustering Algorithm Based on Aggregated Heat Kernel Mapping, International Conference on Data Mining series (ICDM), IEEE International Conference on Data Mining, Vancouver, Canada, December 2011.
Sushant Sharm, Dimitrios Katramatos, and Dantong Yu, End-to-End Network QoS via Scheduling of Flexible Resource Reservation Requests, SuperComputing 2011, Seattle, WA.
Yi Gu, Qishi Wu, Xin Liu, Dantong Yu: Improving Throughput and Reliability of Distributed Scientific Workflows for Streaming Data Processing, HPCC 2011.