Recent Papers and Presentations by Students at SDM Group

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• J. Bellavita, A. Sim (advisor), K. Wu (advisor), "Predicting Scientific Dataset Popularity Using dCache Logs",
  Poster (in PDF), Summary (in PDF)
  ACM/IEEE The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC'22), ACM Student Research Competition, 2022.
• C. Sim, C. Guok (advisor), A. Sim (advisor), K. Wu (advisor), "Data Throughput Performance Trends of Regional Scientific Data Cache",
  Poster (in PDF), Summary (in PDF)
  ACM/IEEE The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC'22), ACM Student Research Competition, 2022.
• R. Shao, J. Kim A. Sim, K. Wu, "Predicting Slow Connections in Scientific Computing", 5th ACM International Workshop on System and Network Telemetry and Analysis (SNTA) 2022, 2022. doi:10.1145/3526064.3534112.
• J. Bellavita, A. Sim, K. Wu, I. Monga, C. Guok, F. Wurthwein, D. Davila, "Studying Scientific Data Lifecycle in On-demand Distributed Storage Caches", 5th ACM International Workshop on System and Network Telemetry and Analysis (SNTA), 2022. doi:10.1145/3526064.3534111. http://arxiv.org/abs/2205.05598
• R. Han, A. Sim, K. Wu, I. Monga, C. Guok, F. Wurthwein, D. Davila, J. Balcas, H. Newman, "Access Trends of In-network Cache for Scientific Data", 5th ACM International Workshop on System and Network Telemetry and Analysis (SNTA), 2022. doi:10.1145/3526064.3534110. http://arxiv.org/abs/2205.05563.
  
  
• Jason Cheung, "Performance Prediction of Large Data Transfers", ACM/IEEE The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC21), ACM Student Research Competition (SRC).
• Elizabeth Copps, "Analyzing scientific data-sharing patterns for in-network data caching",
  Poster (in PDF), Summary (in PDF) Slides (in PDF)
  ACM Richard Tapia Celebration of Diversity in Computing (TAPIA 2021), 2021. ACM Student Research Competition (SRC), 2021.
  
• B. Weinger, J. Kim, A. Sim, M. Nakashima, N. Moustafa, K. Wu, "Enhancing IoT Anomaly Detection Performance for Federated Learning", Digital Communications and Networks, Special Issue on Edge Computation and Intelligence, 2021.
• A. Syal, A. Lazar, J. Kim, A. Sim, K. Wu, "Network Traffic Performance Analysis and Anomaly Detection using Supervised Machine Learning", International Journal of Big Data Intelligence, Special Issue on Systems and Network Telemetry and Analytics, 2021.
• E. Copps, H. Zhang, A. Sim, K. Wu, I. Monga, C. Guok, F. Wurthwein, D. Davila, E. Fajardo, "Analyzing scientific data sharing patterns with in-network data caching", ACM International Workshop on System and Network Telemetry and Analysis (SNTA) 2021. doi:10.1145/3452411.3464441. http://arxiv.org/abs/2105.00964.
• Y. Wang, K. Wu, A. Sim, S. Yoo, S. Misawa, "Access Patterns of Disk Cache for Large Scientific Archive", ACM International Workshop on System and Network Telemetry and Analysis (SNTA) 2021. doi:10.1145/3452411.3464444.
• Y. Ma, F. Ruso, A. Sim, K. Wu, "Adaptive Stochastic Gradient Descent for Deep Learning on Heterogeneous CPU+GPU Architectures", Heterogeneity in Computing Workshop (HCW 2021), in conjunction with the 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2021. doi:10.1109/IPDPSW52791.2021.00012
• M. Nakashima, A. Sim, Y. Kim, J. Kim, J. Kim, "Automated Variable Selection for Network Anomaly Detection", ACM Transactions on Management Information Systems (TMIS), 2021. doi:10.1145/3446636.
  
  
• B. Cho, T. Dayrit, Y. Gao, Z. Wang, T. Hong, A. Sim, K. Wu,"Effective Missing Value Imputation Methods for Building Monitoring Data", The 2nd International Workshop on Big Data Tools, Methods, and Use Cases for Innovative Scientific Discovery (BTSD 2020) in conjunction with IEEE International Conference on Big Data (IEEE BigData 2020), 2020. doi:10.1109/BigData50022.2020.9378230
• J. Kim, A. Sim, J. Kim, K. Wu, "Botnets Detection Using Recurrent Variational Autoencoder", IEEE Global Communications Conference (Globecom 2020), 2020.
• B. Weinger, J. Kim, A. Sim, M. Nakashima, N. Moustafa, K. Wu, "Enhancing IoT Anomaly Detection Performance for Federated Learning", The 16th International Conference on Mobility, Sensing and Networking (MSN2020), 2020. doi:10.1109/MSN50589.2020.00045
• Brett Weinger, "Enhancing IoT Anomaly Detection Performance for Federated Learning"
  Poster (in PDF), Summary (in PDF)
  International Conference for High Performance Computing, Networking, Storage and Analysis (SC'20), ACM Student Research Competition (SRC), 2020
• J. Kim, A. Sim, J. Kim, K. Wu, J. Hahm, "Transfer Learning Approach for Botnet Detection based on Recurrent Variational Autoencoder", ACM International Workshop on System and Network Telemetry and Analysis (SNTA) 2020, 2020.
• M. Nakashima, A. Sim, J. Kim, "Evaluation of Deep Learning Models for Network PerformancePrediction for Scientific Facilities", ACM International Workshop on System and Network Telemetry and Analysis (SNTA) 2020
• J. Bang, C. Kim, K. Wu, A. Sim, S. Byna, S. Kim, H. Eom, "HPC Workload Characterization using Feature Selection and Clustering", ACM International Workshop on System and Network Telemetry and Analysis (SNTA) 2020
• S. Bhandari, A. K. Kukreja, A. Lazar, A. Sim, K. Wu, "Feature Selection and Tree-based Classification for Wireless Intrusion Detection", ACM International Workshop on System and Network Telemetry and Analysis (SNTA) 2020
• Q. Kang, A. Sim, P. Nugent, S. Lee, W.K. Liao, A, Agrawal, A. Choudhary, K. Wu, "Predicting Resource Requirement in Intermediate Palomar Transient Factory Workflow", the 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2020), 2020
• H. Sung, J. Bang, C. Kim, H. Kim, A. Sim, G. K. Lockwood, H. Eom, "BBOS: Efficient HPC Storage Management via Burst Buffer Over-Subscription", the 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2020), 2020
• G. R. Ghosal, D. Ghosal, A. Sim, A. V. Thakur, K. Wu, "A Deep Deterministic Policy Gradient Based Network Scheduler For Deadline-Driven Data Transfers", International Federation for Information Processing (IFIP) Networking Conference (NETWORKING 2020), 2020.
  
  
• Q. Kang, A. Agrawal, A. Choudhary, A. Sim, K. Wu, R. Kettimuthu, P. Beckman, Z. Liu, W-K Liao, "Spatiotemporal Real-Time Anomaly Detection for Supercomputing Systems", Workshop on Big Data Predictive Maintenance using Artificial Intelligence, in conjunction with IEEE International Conference on Big Data (Big Data), 2019
• Alexandra Ballow, "Handling Missing Values in Joint Sequence Analysis", ACM Richard Tapia Celebration of Diversity in Computing (TAPIA 2019), 2019. ACM Student Research Competition (SRC), First place winner, 2019. Abstract
  
  
• S. Shukla, D. Ghosal, K. Wu, A. Sim, M. Farrens, "Co-optimizing Latency and Energy for IoT services using HMP servers in Fog Clusters", IEEE International Conference on Fog and Mobile Edge Computing (FMEC2019), 2019. PDF
  
  
• S. Kim, A. Sim, K. Wu, S. Byna, T. Wang, Y. Son, H. Eom, "DCA-IO: A Dynamic I/O Control Scheme for Parallel and Distributed File System", 19th Annual IEEE/ACM International Symposium in Cluster, Cloud, and Grid Computing (CCGrid 2019), 2019. PDF
  
  
• H. Sung, J. Bang, A. Sim, K. Wu, H. Eom, "Understanding Parallel I/O Performance Trends Under Various HPC Configurations", the 2nd International Workshop on Systems and Network Telemetry and Analytics (SNTA 2019), 2019. PDF
  
  
• M. Jin, Y. Homma, A. Sim, W. Kroeger, K. Wu, "Performance Prediction for Data Transfers in LCLS Workflow", the 2nd International Workshop on Systems and Network Telemetry and Analytics (SNTA 2019), 2019. PDF
  
  
• O. Del Guercio, R. Orozco, A. Sim, K. Wu, "Similarity-based Compression with Multidimensional Pattern Matching", the 2nd International Workshop on Systems and Network Telemetry and Analytics (SNTA 2019), 2019. PDF
  
  
• A. Syal, A. Lazar, J. Kim, K. Wu, A. Sim, "Automatic Detection of Network Traffic Anomalies and Changes", the 2nd International Workshop on Systems and Network Telemetry and Analytics (SNTA 2019), in conjunction with ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC 2019), 2019. PDF
  
  
• Olivia Del Guercio, Rafael Orozco, Alex Sim, Kesheng Wu, "Multidimensional Compression and Pattern Matching", Data Compression Conference (DCC 2019), 2019. Poster (in PDF), Summary
  
  
• Alexandra Ballow, Alina Lazar, Alex Sim, Kesheng Wu, "Joint Sequence Analysis Challenges: How to Handle Missing Values and Mixed Variable Types", SIAM Conference on Computational Science and Engineering (CSE19), 2019. Poster (in PDF), Abstract
  
  
• Tyler Leibengood, Alina Lazar, Alex Sim, Kesheng Wu, "Network Traffic Performance Prediction with Multivariate Clusters in Time Windows", SIAM Conference on Computational Science and Engineering (CSE19), 2019. Poster (in PDF), Abstract
  
  
• Tal Shachaf, Alexander Sim, Kesheng Wu, Wilko Kroeger, "Detecting Anomalies in the LCLS Workflow", 3rd workshop on Open Science in Big Data (OSBD 2018), in conjunction with IEEE International Conference on Big Data (Big Data 2018), 2018. PDF
  
  
• Kade Gibson, Dongeun Lee, Jaesik Choi, Alex Sim, "Dynamic Online Performance Optimization in Streaming Data Compression", IEEE International Conference on Big Data (Big Data 2018), 2018. PDF
  
  
• Karen Tu, "Identification of Network Data Transfer Bottlenecks in HPC Systems"
  Poster (in PDF), Summary (in PDF)
  International Conference for High Performance Computing, Networking, Storage and Analysis (SC'18), ACM Student Research Competition (SRC), 2018
  
  
• J. Wang, K. Wu, A. Sim, S. Hwangbo, "Feature Engineering and Classification Models for Partial Discharge in Power Transformers", Joint Workshop on Deep Learning for Safety-Critical in Engineering Systems (DISE1), in conjunction with ICML, AAMAS, IJCAI, and ECAI 2018, 2018. PDF
  
  
• Weijie Zhao, Florin Rusu, Bin Dong, Kesheng Wu, Anna Ho, and Peter Nugent, "Distributed Caching for Processing Raw Arrays", SSDBM, 2018
  
  
• J. Kim, J. Choi, A. Sim, "Spatio-temporal Analysis of HPC I/O and Connection Data", International Workshop on Scalable Network Traffic Analytics (SNTA 2018), 2018, in conjunction with the 38th IEEE International Conference on Distributed Computing Systems (ICDCS 2018), 2018. doi: 10.1109/ICDCS.2018.00176
  
  
• C. Dao, X. Liu, J. Jiang, A. Sim, C. E. Tull, K. Wu, "Modeling Data Transfers: Change Point and Anomaly Detection", International Workshop on Scalable Network Traffic Analytics (SNTA 2018), 2018, in conjunction with the 38th IEEE International Conference on Distributed Computing Systems (ICDCS 2018), 2018. doi: 10.1109/ICDCS.2018.00177
  
  
• M. Yang, X. Liu, W. Kroeger, A. Sim, K. Wu, "Identifying Anomalous File Transfer Events in LCLS Workflow", Workshop in Autonomous Infrastructure for Science (AI-Science 2018), 2018, in conjunction with the 27th International Symposium on High-Performance Parallel and Distributed Computing (ACM HPDC 2018), 2018, doi: 10.1145/3217197.3217203
  
  
• H. Zhan, G. Gomes, X. S. Li, K. Madduri, A. Sim, K. Wu, "Consensus Ensemble System for Traffic Flow Prediction", IEEE Transactions on Intelligent Transportation Systems, 2018. doi: 10.1109/TITS.2018.2791505
  
  
• T. Kim, J. Choi, D. Lee, A. Sim, C. A. Spurlock, A. Todd, K. Wu, "Predicting Baseline for Analysis of Electricity Pricing", International Journal of Big Data Intelligence, Special Issue on Data to Decision, 2018, 5:3-20, doi: 10.1504/IJBDI.2018.10008133, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2773991.
  
  
• J. Wang, A. Sim, K. Wu, S. Hwangbo, "Accurate Signal Timing from High Frequency Streaming Data", 2017 IEEE International Conference on Big Data (Big Data 2017). Summary, Poster
  
  
• J. Wang, K. Wu, A. Sim, S. Hwangbo, "Feature Engineering and Classification Models for Partial Discharge Events in Power Transformers", 10th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2017), 2017. Summary, Poster
  
  
• Peter Harrington, "Diagnosing Parallel I/O Bottlenecks in HPC Applications"
  Poster (in PDF) , Summary (in PDF) , Presentation slides (in PDF)
  International Conference for High Performance Computing, Networking, Storage and Analysis (SC'17), ACM Student Research Competition (SRC), First place winner, 2017
  
  
• Matt Bae, "Discovering Energy Resource Usage Patterns on Scientific Clusters"
  Poster (in PDF) , Summary (in PDF) , Presentation slides (in PDF)
  International Conference for High Performance Computing, Networking, Storage and Analysis (SC'16), ACM Student Research Competition (SRC), Third place winner, 2016
  
  
• Matt Bryson, "The Search for Missing Parallel IO Performance on the Cori Supercomputer"
  Poster (in PDF) , Summary (in PDF) , Presentation slides (in PDF)
  
  
• Jonathan Wang, "Analysis of Variable Selection Methods on Scientific Cluster Measurement Data"
  Poster (in PDF) , Summary (in PDF) , Presentation slides (in PDF)
  International Conference for High Performance Computing, Networking, Storage and Analysis (SC'16), ACM Student Research Competition (SRC), Second place winner, 2016
  
  
• J. Wang, W. Yoo, A. Sim, P. Nugent, K. Wu, "Parallel Variable Selection for Effective Performance Prediction", the 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid2017), 2017.
  
  
• Ling Jin, Doris Lee, Alex Sim, Sam Borgeson, John Wu, Anna Spurlock, Annika Todd, "Comparison of Clustering Techniques for Residential Energy Behavior using Smart Meter Data", 2nd International Workshop on Artificial Intelligence for Smart Grids and Smart Buildings, In conjunction with AAAI 2017, 2017
  
  
• Michelle Koo, "I/O Performance Analysis Framework on Measurement Data from Scientific Clusters"
  Poster (in PDF) , Summary (in PDF) , Additional slides (in PDF)
  International Conference for High Performance Computing, Networking, Storage and Analysis (SC'15), ACM Student Research Competition (SRC), 2015
  
  
• W. Yoo, M. Koo, Y. Cao, A. Sim, P. Nugent, K. Wu, "Performance Analysis Tool for HPC and Big Data Applications on Scientific Clusters", Conquering Big Data with High Performance Computing, edited by R. Arora, (Springer International: 2016) Pages: 139-161 doi: 10.1007/978-3-319-33742-5.
  
  
• T. Kim, D. Lee, J. Choi, A. Spurlock, A. Sim, A. Todd, K. Wu, "Extracting Baseline Electricity Usage Using Gradient Tree Boosting", International Conference on Big Data Intelligence and Computing (DataCom 2015), Best Paper Award, 2015.
  
  
• K. Hu, J. Choi, A. Sim, J. Jiang, "Best Predictive Generalized Linear Mixed Model with Predictive Lasso for High-Speed Network Data Analysis", International Journal of Statistics and Probability, 2015, http://www.ccsenet.org/journal/index.php/ijsp/article/view/48070
  
  
• Lingfei Wu, Kesheng Wu, Alex Sim, Michael Churchill, Jong Choi, Andreas Stathopoulos, Choong-Seock Chang, Scott Klasky, "Towards Real-Time Detection and Tracking of Spatio-Temporal Features: Blob-Filaments in Fusion Plasma", IEEE Transactions on Big Data (TBD), Vol. 2, Issue 3, pp. 262-275, Sep. 2016, doi:10.1109/TBDATA.2016.2599929.
  
  
• David H. Bailey, Stephanie Ger, Marcos Lopez De Prado, Alexander Sim, Kesheng Wu, "Statistical Overfitting and Backtest Performance", book chapter, "Risk-Based and Factor Investing", edited by Emmanuel Jurczenko, ISTE Press Ltd, Elsevier Ltd, UK, pp. 449-461, ISBN 978-1-78548-008-9, 2015.
  D. H. Bailey, S. Ger, M. L. de Prado, A. Sim, K. Wu, "Statistical Overfitting and Backtest Performance", Social Science Research Network, 7 Oct 2014. http://ssrn.com/abstract=2507040
  
  
• L. Wu, K. Wu, A. Sim, M. Churchill, J. Y. Choi, A. Stathopoulos, CS Chang, S. Klasky, "High-Performance Outlier Detection Algorithm for Finding Blob-Filaments in Plasma", 5th International Workshop on Big Data Analytics: Challenges, and Opportunities (BDAC'14), 2014
  
  
• Lingfei Wu, "Real-Time Outlier Detection Algorithm for Finding Blob-Filaments in Plasma", ACM Student Research Poster Competition, Super Computing 2014, 2014.
  
  
• Benson Ma, Arie Shoshani, Alex Sim, Kesheng Wu, Yong-Ik Byun, Jaegyoon Hahm and Min-Su Shin, "Efficient Attribute-based Data Access in Astronomy Analysis", The 2nd International Workshop on Network-Aware Data Management Workshop (NDM2012), Nov. 2012
  
  
• D. Hasenkamp, A. Sim, M. Wehner, K. Wu, "Finding Tropical Cyclones on a Cloud Computing Cluster: Using Parallel Virtualization for Large-Scale Climate Simulation Analysis", Proceedings of the 2nd IEEE International Conference on Cloud Computing Technology and Science (CloudCom2010), 2010.
  
  
• D. Hasenkamp, "Finding Tropical Cyclones on Clouds", International Conference for High Performance Computing, Networking, Storage and Analysis (SC'10), ACM Student Research Competition (SRC), Third place winner, 2010.