Publications

Opportunities for enhancing MLCommons efforts while leveraging insights from educational MLCommons earthquake benchmarks efforts, Journal of Frontiers in High-Performance Computing, October 2023 Link

Fairness and Privacy in Federated Learning and Their Implications in Healthcare, arXiv preprint, August 2023 Link

Interpreting County-Level COVID 19 Infections using Transformer and Deep Learning Time Series Models, IEEE International Conference on Digital Health (ICDH), July 2023 Link

Does Differential Privacy Impact Bias in Pretrained NLP Models?, The Fourth AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-23), February 2023 Link

Intel Optane DCPMM and Serverless Computing, arXiv preprint, September 2021 Link

HySec-Flow: Privacy-Preserving Genomic Computing with SGX-based Big-Data Analytics Framework, IEEE 14th International Conference on Cloud Computing (CLOUD), September 2021 Link

Rank Position Forecasting in Car Racing, IEEE International Parallel and Distributed Processing Symposium (IPDPS), May 2021 Link

net.science: A cyberinfrastructure for sustained innovation in network science and engineering, Gateways Conference 2020, October 2020 Link

L. Chen, J. Li, C. Sahinalp, M. Marathe, A. Vullikanti, A. Nikolaev, E. Smirnov, R. Israfilov, and J. Qiu, “Subgraph2Vec: Highly-vectorized tree-like subgraph counting,” in 2019 IEEE International Conference on Big Data, IEEE, 2019. Link

J. Li, F. Wang, T. Araki and J. Qiu, “Generalized Sparse Matrix-Matrix Multiplication for Vector Engines and Graph Applications,” in MCHPC’19: Workshop on Memory Centric High Performance Computing, ACM, 2019. Link

C. Widanage, J. Li, S. Tyagi, R. Teja, B. Peng, S. Kamburugamuve, D. Baum, D. Smith, J. Qiu, and J. Koskey, “Anomaly detection over streaming data: Indy500 case study,” in 2019 IEEE 12th International Conference on Cloud Computing (CLOUD), pp. 9–16, IEEE, 2019. Link

B. Peng, L. Chen, J. Li, M. Jiang, S. Akkas, E. Smirnov, R. Israfilov, S. Khekhnev, A. Nikolaev, and J. Qiu, “HarpGBDT: Optimizing gradient boosting decision tree for parallel efficiency,” in 2019 IEEE International Conference on Cluster Computing (CLUSTER), pp. 1–11, IEEE, 2019. Link

G. Fox, J. A. Glazier, J. Kadupitiya, V. Jadhao, M. Kim, J. Qiu, J. P.Sluka, E. Somogyi, M. Marathe, A. Adiga, et al., “Learning everywhere : Pervasive machine learning for effective high-performance computation,” in 2019 HPCDC workshop of IPDPS conference, pp. 422–429, 2019. Link

M. Marathe, L. Jiang, and J. Qiu, “High-performance massive subgraph counting using pipelined adaptive-group communication,” Big Data and HPC: Ecosystem and Convergence, vol. 33, p. 173, 2018. Link

L. Jiang, L. Chen, and J. Qiu, “Performance characterization of multi-threaded graph processing applications on many-integrated-core architecture,” in 2018 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), pp. 199–208, IEEE, 2018. Link

Z. Zhao, L. Chen, M. Avram, M. Li, G. Wang, A. Butt, M. Khan, M. Marathe, J. Qiu, and A. Vullikanti, “Finding and counting tree-like subgraphs using mapreduce,” IEEE Transactions on Multi-Scale Computing Systems, vol. 4, no. 3, pp. 217–230, 2017. Link

B. Zhang, B. Peng, and J. Qiu, “Parallelizing big data machine learning applications with model rotation,” New Frontiers in High Performance Computing and Big Data, vol. 30, p. 199, 2017. Link

B. Peng, B. Zhang, L. Chen, M. Avram, R. Henschel, C. Stewart, S. Zhu, E. Mccallum, L. Smith, T. Zahniser, et al., “Harplda+: Optimizing Latent Dirichlet Allocation for Parallel Efficiency,” in 2017 IEEE International Conference on Big Data (Big Data), pp. 243–252, IEEE, 2017. Link

J. Qiu, S. Kamburugamuve, H. Lee, J. Mitchell, R. Caldwell, G. Bullock, and L. Hayden, “Teaching, learning and collaborating through cloud computing online classes,” in the proceedings of the Workshop on Education for High-Performance Computing (EduHPC-17), Denver, Colorado. November 13, 2017. Link

L. Chen, B. Peng, B. Zhang, T. Liu, Y. Zou, L. Jiang, R. Henschel, C. Stewart, Z. Zhang, E. Mccallum, et al., “Benchmarking Harp-DAAL: High Performance Hadoop on KNL clusters,” in 2017 IEEE 10th International Conference on Cloud Computing (CLOUD), pp. 82–89, IEEE, 2017. Link

C. A. Davis, G. L. Ciampaglia, L. M. Aiello, K. Chung, M. D. Conover, E. Ferrara, A. Flammini, G. C. Fox, X. Gao, B. Gon¸calves, et al., “Osome: the IUNI observatory on social media,” PeerJ Computer Science, vol. 2, p. e87, 2016. Link

T. Wu, B. Zhang, C. Davis, E. Ferrara, A. Flammini, F. Menczer, J. Qiu, M. Thai, H. Xiong, and W. Wu, “Scalable query and analysis for social networks: an integrated high-level dataflow system with Pig and Harp,” Big data in complex and social networks, 2016. Link

B. Zhang, B. Peng, and J. Qiu, “Model-Centric Computation Abstractions in Machine Learning Applications,” in Proceedings of the 3rd ACM SIGMOD Workshop on Algorithms and Systems for MapReduce and Beyond, p. 3, ACM, 2016. Link

B. Zhang, B. Peng, and J. Qiu, “High performance LDA through Collective Model Communication Optimization,” Procedia Computer Science, vol. 80, pp. 86–97, 2016. Link

G. Fox, J. Qiu, S. Jha, S. Ekanayake, and S. Kamburugamuve, “Big data, Simulations and HPC Convergence,” in Big Data Benchmarking, pp. 3–17, Springer, 2015. Link

G. Fox, S. Jha, J. Qiu, S Ekanazake, A. Luckow, “Towards a comprehensive set of big data benchmarks”, in Big Data and High Performance Computing, pp. 47-66, IOS Press, 2015. Link

B. Zhang, Y. Ruan, and J. Qiu, “Harp: Collective Communication on Hadoop,” in 2015 IEEE International Conference on Cloud Engineering, pp. 228–233, IEEE, 2015. Link

G. Fox, J. Qiu, S. Kamburugamuve, S. Jha, A. Luckow, “HPC-ABDS High Performance Computing Enhanced Apache Big Data Stack”. In CCGRID Conference, pp. 1057-1066, IEEE, 2015. Link

X. Gao, E. Ferrara, and J. Qiu, “Parallel Clustering of High-Dimensional Social Media Data Streams,” in 2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 323–332, IEEE, 2015. Link

X. Li and J. Qiu, Cloud computing for data-intensive applications, vol. 1. Springer, 2014. Link

X. Gao, E. Roth, K. McKelvey, C. Davis, A. Younge, E. Ferrara, F. Menczer, and J. Qiu, “Supporting a social media observatory with customizable index structures: architecture and performance,” in Cloud Computing for Data-Intensive Applications, pp. 401–427, Springer, 2014. Link

J. Qiu, S. Jha, A. Luckow, and G. C. Fox, “Towards HPC-ABDS: an initial high-performance big data stack,” Building Robust Big Data Ecosystem ISO/IEC JTC, vol. 1, pp. 18–21, 2014. Link

T.-L. Wu, A. Koppula, and J. Qiu, “Integrating pig with harp to support iterative applications with fast cache and customized communication,” in Proceedings of the 5th International Workshop on Data-Intensive Computing in the Clouds, pp. 33–39, IEEE Press, 2014. Link

S. Jha, J. Qiu, A. Luckow, P. Mantha, and G. C. Fox, “A tale of two data-intensive paradigms: Applications, Abstractions, and Architectures,” in 2014 IEEE International Congress on Big Data, pp. 645–652, IEEE, 2014. Link

T. Gunarathne, J. Qiu, and D. Gannon, “Towards a collective layer in the big data stack,” in 2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 236–245, IEEE, 2014. Link

X. Gao and J. Qiu, “Supporting queries and analyses of large-scale social media data with customizable and scalable indexing techniques over NOSQL databases,” in 2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 587–590, IEEE, 2014. Link

G. C. Fox, S. Jha, J. Qiu, and A. Luckow, “Towards an understanding of facets and exemplars of big data applications,” in Proceedings of the 20 Years of Beowulf Workshop on Honor of Thomas Sterling’s 65th Birthday, pp. 7–16, ACM, 2014. Link

X. Gao and J. Qiu, “Supporting end-to-end social media data analysis with the IndexedHbase platform,” in Proceedings of the 6th workshop on many- task computing on clouds, grids, and supercomputers (MTAGS) at SC13, Citeseer, 2013. Link

T. Gunarathne, B. Zhang, T.-L. Wu, and J. Qiu, “Scalable parallel computing on clouds using twister4azure iterative Mapreduce,” Future Generation Computer Systems, vol. 29, no. 4, pp. 1035–1048, 2013. Link

​J. Q. B. Zhang, “Mammoth data in the cloud: clustering social images,” Cloud computing and big data, vol. 23, p. 231, 2013. Link

K. Hwang, J. Dongarra, and G. C. Fox, Distributed and cloud computing: from parallel processing to the internet of things. Morgan Kaufmann, 2013. Link

​B. Zhang and J. Qiu, “High performance clustering of social images in a map-collective programming model,” in Proceedings of the 4th annual Symposium on Cloud Computing, p. 44, ACM, 2013. Link

​J. Qiu, J. Ekanayake, T. Gunarathne, J. Y. Choi, S.-H. Bae, Y. Ruan, S. Ekanayake, S. Wu, S. Beason, G. Fox, et al., “Data intensive computing for bioinformatics,” in Data Intensive Distributed Computing: Challenges and Solutions for Large-scale Information Management, pp. 207–241, IGI Global, 2012. Link

S. E. Abdelhamid, R. Alo, S. Arifuzzaman, P. Beckman, M. H. Bhuiyan, K. Bisset, E. A. Fox, G. C. Fox, K. Hall, S. S. Hasan, J. Qiu, et al., “CINET: A cyberinfrastructure for Network Science,” in 2012 IEEE 8th International Conference on E-Science, pp. 1–8, IEEE, 2012. Link

L. Stanberry, R. Higdon, W. Haynes, N. Kolker, W. Broomall, S. Ekanayake, A. Hughes, Y. Ruan, J. Qiu, E. Kolker, et al., “Visualizing the protein sequence universe,” in Proceedings of the 3rd international workshop on Emerging computational methods for the life sciences, pp. 13– 22, ACM, 2012. Link

A. Hughes, Y. Ruan, S. Ekanayake, S.-H. Bae, Q. Dong, M. Rho, J. Qiu, and G. Fox, “Interpolative multidimensional scaling techniques for the identification of clusters in very large sequence sets,” in BMC bioinformatics, vol. 13, p. S9, BioMed Central, 2012. Link

​Y. Ruan, Z. Guo, Y. Zhou, J. Qiu, and G. Fox, “Hymr: a hybrid mapreduce workflow system,” in Proceedings of the 3rd international workshop on Emerging computational methods for the life sciences, pp. 39–48, ACM, 2012. Link

J. Y. Choi, H. Abbasi, D. Pugmire, N. Podhorszki, S. Klasky, C. Capdevila, M. Parashar, M. Wolf, J. Qiu, and G. Fox, “Mining hidden mixture context with ADIOS-p to improve predictive pre-fetcher accuracy,” in 2012 IEEE 8th International Conference on E-Science, pp. 1–8, IEEE, 2012. Link

S.-H. Bae, J. Qiu, and G. Fox, “Adaptive interpolation of multidimensional scaling,” Procedia Computer Science, vol. 9, pp. 393–402, 2012. Link

H. Li, G. Fox, and J. Qiu, “Performance model for parallel matrix multiplication with dryad: Dataflow graph runtime,” in 2012 Second International Conference on Cloud and Green Computing, pp. 675–683, IEEE, 2012. Link

Y. Ruan, S. Ekanayake, M. Rho, H. Tang, S.-H. Bae, J. Qiu, and G. Fox, “Dacidr: deterministic annealed clustering with interpolative dimension reduction using a large collection of 16s RNA sequences,” in Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine, pp. 329–336, ACM, 2012. Link

J. Y. Choi, S.-H. Bae, J. Qiu, B. Chen, and D. Wild, “Browsing large-scale cheminformatics data with dimension reduction,” Concurrency and Computation: Practice and Experience, vol. 23, no. 17, pp. 2315–2325, 2011. Link

T. Gunarathne, B. Zhang, T.-L. Wu, and J. Qiu, “Portable parallel programming on cloud and HPC: Scientific applications of twister4azure,” in 2011 Fourth IEEE International Conference on Utility and Cloud Computing, pp. 97–104, IEEE, 2011. Link

H. Li, Y. Ruan, Y. Zhou, J. Qiu, and G. Fox, “Design patterns for scientific applications in DryadLinq CTP,” in Proceedings of the second international workshop on Data intensive computing in the clouds, pp. 61–70, ACM, 2011. Link

A. J. Younge, R. Henschel, J. T. Brown, G. Von Laszewski, J. Qiu, and G. C. Fox, “Analysis of virtualization technologies for high performance computing environments,” in 2011 IEEE 4th International Conference on Cloud Computing, pp. 9–16, IEEE, 2011. Link

Y. Luo, Z. Guo, Y. Sun, B. Plale, J. Qiu, and W. W. Li, “A hierarchical framework for cross-domain Mapreduce execution,” in Proceedings of the second international workshop on Emerging computational methods for the life sciences, pp. 15–22, ACM, 2011. Link

T. Gunarathne, T.-L. Wu, J. Y. Choi, S.-H. Bae, and J. Qiu, “Cloud Computing paradigms for pleasingly parallel biomedical applications,” Concurrency and Computation: Practice and Experience, vol. 23, no. 17, pp. 2338– 2354, 2011. Link

J. Y. Choi, S.-H. Bae, J. Qiu, B. Chen, and D. Wild, “Browsing large-scale cheminformatics data with dimension reduction,” Concurrency and Computation: Practice and Experience, vol. 23, no. 17, pp. 2315–2325, 2011. Link

​J. Qiu, J. Ekanayake, T. Gunarathne, J. Y. Choi, S.-H. Bae, H. Li, B. Zhang, T.-L. Wu, Y. Ruan, S. Ekanayake, et al., “Hybrid cloud and cluster computing paradigms for life science applications,” in BMC Bioinformatics, vol. 11, p. S3, BioMed Central, 2010. Link

J. Qiu, S. Beason, S.-H. Bae, S. Ekanayake, and G. Fox, “Performance of windows multicore systems on threading and MPI,” in 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, pp. 814–819, IEEE, 2010. Link

J. Ekanayake, H. Li, B. Zhang, T. Gunarathne, S.-H. Bae, J. Qiu, and G. Fox, “Twister: a runtime for iterative Mapreduce,” in Proceedings of the 19th ACM international symposium on high performance distributed computing, pp. 810–818, ACM, 2010. Link

J. Qiu, S. Beason, S.-H. Bae, S. Ekanayake, and G. Fox, “Performance of windows multicore systems on threading and MPI,” in 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, pp. 814–819, IEEE, 2010. Link

J. Y. Choi, S.-H. Bae, X. Qiu, and G. Fox, “High performance dimension reduction and visualization for large high-dimensional data analysis,” in Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, pp. 331–340, IEEE Computer Society, 2010. Link

J. Y. Choi, J. Qiu, M. Pierce, and G. Fox, “Generative topographic map- ping by deterministic annealing,” Procedia Computer Science, vol. 1, no. 1, pp. 47–56, 2010. Link

S.-H. Bae, J. Qiu, and G. C. Fox, “Multidimensional scaling by deterministic annealing with iterative majorization algorithm,” in 2010 IEEE sixth international conference on e-Science, pp. 222–229, IEEE, 2010. Link

B. Zhang, Y. Ruan, T.-L. Wu, J. Qiu, A. Hughes, and G. Fox, “Applying twister to scientific applications,” in 2010 IEEE Second International Conference on Cloud Computing Technology and Science, pp. 25–32, IEEE, 2010. Link

T. Gunarathne, T.-L. Wu, J. Qiu, and G. Fox, “Mapreduce in the clouds for science,” in 2010 IEEE second international conference on cloud computing technology and science, pp. 565–572, IEEE, 2010. Link

S.-H. Bae, J. Y. Choi, J. Qiu, and G. C. Fox, “Dimension reduction and visualization of large high-dimensional data via interpolation,” in Proceedings of the 19th ACM international symposium on high performance distributed computing, pp. 203–214, ACM, 2010. Link

J. Ekanayake and G. Fox, “High performance parallel computing with clouds and cloud technologies,” in International Conference on Cloud Computing, pp. 20–38, Springer, 2009. Link

G. Fox, S.-H. Bae, J. Ekanayake, X. Qiu, and H. Yuan, “Parallel Data Mining from Multicore to Cloudy Grids,” in High Performance Computing Workshop, vol. 18, pp. 311–340, 2009. Link

X. Qiu, J. Ekanayake, S. Beason, T. Gunarathne, G. Fox, R. Barga, and D. Gannon, “Cloud technologies for bioinformatics applications,” in Proceedings of the 2nd Workshop on Many-Task Computing on Grids and Supercomputers, p. 6, ACM, 2009. Link

G. Fox, X. Qiu, S. Beason, J. Choi, J. Ekanayake, T. Gunarathne, M. Rho, H. Tang, N. Devadasan, and G. Liu, “Biomedical case studies in data intensive computing,” in IEEE International Conference on Cloud Computing, pp. 2–18, Springer, 2009. Link

​X. Qiu, G. Fox, H. Yuan, S.-H. Bae, G. Chrysanthakopoulos, and H. Nielsen, “Parallel data mining on multicore clusters,” in 2008 Seventh International Conference on Grid and Cooperative Computing, pp. 41–49, IEEE, 2008. Link

X. Qiu, G. C. Fox, H. Yuan, S.-H. Bae, G. Chrysanthakopoulos, and H. F. Nielsen, “Performance of multicore systems on parallel data clustering with deterministic annealing,” in International Conference on Computational Science, pp. 407–416, Springer, 2008. Link

X. Qiu, G. C. Fox, H. Yuan, S.-H. Bae, G. Chrysanthakopoulos, and H. F. Nielsen, “Parallel clustering and dimensional scaling on multicore systems,” HIGH PERFORMANCE COMPUTING & SIMULATION (HPCS 2008), p. 67, 2008. Link

X. Qiu, G. C. Fox, H. Yuan, S.-H. Bae, G. Chrysanthakopoulos, and H. F. Nielsen, “High performance multi-paradigm messaging runtime integrating grids and multicore systems,” in Third IEEE International Conference on e-Science and Grid Computing (e-Science 2007), pp. 407–414, IEEE, 2007. Link

X. Qiu and A. Jooloor, “Web service architecture for e-learning,” Journal of Systemics, Cybernetics and Informatics, vol. 3, no. 5, pp. 92–101, 2006. Link

​X. Qiu, S. Pallickara, and A. Uyar, “Making SVG a Web Service in a Message-based MVC Architecture,” 2004. Link

X. Qiu, “Building desktop applications with web services in a Message-based MVC paradigm,” in Proceedings. IEEE International Conference on Web Services, pp. 765–768, IEEE, 2004. Link

G. Fox, D. Gannon, S.-H. Ko, S. Pallickara, X. Qiu, and A. Uyar, “Peer- to-Peer Grids,” 2003. Link

X. Qiu, B. Carpenter, and G. C. Fox, “Collaborative SVG as a web service,” in SVG Open 2003 Conference and Exhibition, Vancouver, Canada, 2003. Link

X. Qiu, B. Carpenter, G. C. Fox, et al., “Internet collaboration using the w3c document object model.,” in International Conference on Internet Computing, pp. 643–647, Citeseer, 2003. Link

G. Fox, H. Bulut, K. Kim, S.-H. Ko, S. Lee, S. Oh, S. Pallickara, X. Qiu, A. Uyar, M. Wang, et al., “Collaborative Web Services and Peer-to-Peer Grids,” SIMULATION SERIES, vol. 35, no. 1, pp. 3–12, 2003. Link

G. Fox, S.-H. Ko, M. Pierce, O. Balsoy, J. Kim, S. Lee, K. Kim, S. Oh, X. Rao, M. Varank, X. Qiu, et al., “Grid services for earthquake science,” Concurrency and Computation: Practice and Experience, vol. 14, no. 6-7, pp. 371–393, 2002. Link