Publications
[33]. Carlos A. Barajas, Gerson C. Kroiz, Matthias K. Gobbert, and Jerimy C. Polf. Using Deep Learning to Enhance Compton Camera Based Prompt Gamma Image Reconstruction Data for Proton Radiotherapy. In: Proceedings in Applied Mathematics and Mechanics (PAMM), vol. 21, no. 1, 2 pages, 2021.
[32]. Reetam Majumder, Matthias K. Gobbert, and Nagaraj K. Neerchal. A Modified Minibatch Sampling Method for Parameter Estimation in Hidden Markov Models using Stochastic Variational Bayes. In: Proceedings in Applied Mathematics and Mechanics (PAMM), vol. 21, no. 1, 2 pages, 2021.
[31]. Matthias K. Gobbert, Jianwu Wang. Lessons from an Online Multidisciplinary Undergraduate Summer Research Program. Accepted by the 17th International Conference on Frontiers in Education: Computer Science and Computer Engineering (FECS 2021).
[30]. Gerson C. Kroiz, Carlos A. Barajas, Matthias K. Gobbert, and Jerimy C. Polf. Exploring Deep Learning to Improve Compton Camera Based Prompt Gamma Image Reconstruction for Proton Radiotherapy. In: The 17th International Conference on Data Science (ICDATA'21), 2021.
[29]. Sahara Ali, Yiyi Huang, Xin Huang, Jianwu Wang. Sea Ice Forecasting using Attention-based Ensemble LSTM. Tackling Climate Change with Machine Learning workshop at International Conference on Machine Learning (ICML), 2021.
[28]. Xin Wang, Pei Guo, Jianwu Wang. Large-Scale Causality Discovery Analytics
as a Service. In Proceedings of the Fifth IEEE International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD 2021) at 2021 IEEE Big Data Conference (Big Data 2021), IEEE, 2021.
[27]. Jianyu Zheng, Xin Huang, Supriya Sangondimath, Jianwu Wang, Zhibo Zhang. Efficient and Flexible Aggregation and Distribution of MODIS Atmospheric Products Based on Climate Analytics as a Service Framework. Remote Sensing 13, no. 17: 3541. https://doi.org/10.3390/rs13173541, 2021.
[26]. Pei Guo, Yiyi Huang, Jianwu Wang. Scalable and Flexible Two-Phase Ensemble Algorithms for Causality Discovery. Accepted by Big Data Research, 2021. doi:10.1016/j.bdr.2021.100252.
[25]. Yiyi Huang, Matthäus Kleindessner, Alexey Munishkin, Debvrat Varshney, Pei Guo, Jianwu Wang. Benchmarking of Data-Driven Causality Discovery Approaches in the Interactions of Arctic Sea Ice and Atmosphere. Accepted by Data-driven Climate Sciences Section, Frontiers in Big Data, Frontiers, 2021. doi:10.3389/fdata.2021.642182.
[24]. Zhi Li, Yixin Wen, Mathias Schreier, Ali Behrangi, Yang Hong, Bjorn Lambrigtsen. Advancing satellite precipitation retrievals with data driven approaches: Is black box model explainable? Earth and Space Science, 8, e2020EA001423, 2021. https://doi.org/10.1029/2020EA001423.
[23]. Gerson C. Kroiz, Reetam Majumder, Matthias K.Gobbert, Nagaraj K. Neerchal, Kel Markert, and Amita Mehta. Daily Precipitation Generation using a Hidden Markov Model with Correlated Emissions for the Potomac River Basin. Proceedings in Applied Mathematics and Mechanics (PAMM), vol. 20, no. 1, 2 pages, 2021.
[22]. Jonathan N. Basalyga, Carlos A. Barajas, Matthias K. Gobbert, Paul Maggi, and Jerimy Polf. Deep Learning for Classification of Compton Camera Data in the Reconstruction of Proton Beams in Cancer Treatment. Proceedings in Applied Mathematics and Mechanics (PAMM), vol. 20, no. 1, 2 pages, 2021.
[21]. Brice Coffer, Michaela Kubacki, Yixin Wen, Ting Zhang, Carlos A. Barajas, Matthias K. Gobbert. Machine Learning with Feature Importance Analysis for Tornado Prediction from Environmental Sounding Data, PAMM, 10.1002/pamm.202000112, 20, 1, 2021. https://doi.org/10.1002/pamm.202000112.
[20]. Jonathan N. Basalyga, Carlos A. Barajas, Matthias K. Gobbert, and Jianwu Wang. Performance Benchmarking of Parallel Hyperparameter Tuning for Deep Learning based Tornado Predictions. Big Data Research, vol. 25, no. 100212, 2021. https://doi.org/10.1016/j.bdr.2021.100212.
[19]. Jangho Lee, Yingxi R. Shi, Changjie Cai, Pubu Ciren, Jianwu Wang, Aryya Gangopadhyay, Zhibo Zhang. 2021. "Machine Learning Based Algorithms for Global Dust Aerosol Detection from Satellite Images: Inter-Comparisons and Evaluation" Remote Sens. 13, no. 3: 456. https://doi.org/10.3390/rs13030456.
[18]. Chamara Rajapakshe, Zhibo Zhang. Using polarimetric observations to detect and quantify the three-dimensional radiative transfer effects in passive satellite cloud property retrievals: Theoretical framework and feasibility study, Journal of Quantitative Spectroscopy and Radiative Transfer, Volume 246, 2020, 106920, ISSN 0022-4073, https://doi.org/10.1016/j.jqsrt.2020.106920.
[17]. Xin Huang, Sahara Ali, Chenxi Wang, Zeyu Ning, Sanjay Purushotham, Jianwu Wang, and Zhibo Zhang. Deep Domain Adaptation based Cloud Type Detection using Active and Passive Satellite Data. Accepted by the 2020 IEEE International Conference on Big Data (BigData 2020), IEEE, 2020.
[16]. Manzhu Yu, Julie Bessac, Ling Xu, Aryya Gangopadhyay, Yingxi Shi, Jianwu Wang. Image Segmentation for Dust Detection using Semi-supervised Machine Learning. Accepted by the 2020 IEEE International Conference on Big Data (BigData 2020), IEEE, 2020.
[15]. Pei Guo, Achuna Ofonedu, Jianwu Wang. Scalable and Hybrid Ensemble-Based Causality Discovery. Accepted by the 2020 IEEE International Conference on Smart Data Services (SMDS 2020), IEEE, 2020.
Best Student Paper Award!
[14]. Xin Huang, Sahara Ali, Sanjay Purushotham, Jianwu Wang, Chenxi Wang and Zhibo Zhang. Deep Multi-Sensor Domain Adaptation on Active and Passive Satellite Remote Sensing Data. In Proceedings of the 1st KDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems (DeepSpatial 2020), 2020.
[13]. Jianwu Wang, Xin Huang, Jianyu Zheng, Chamara Rajapakshe, Savio Kay, Lakshmi Kandoor, Thomas Maxwell, and Zhibo Zhang. Scalable Aggregation Service for Satellite Remote Sensing Data. Accepted by the 20th International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP 2020), Springer, 2020.
[12]. Jianwu Wang, Matthias Gobbert, Zhibo Zhang, Aryya Gangopadhyay. Team-Based Online Multidisciplinary Education on Big Data + High-Performance Computing + Atmospheric Sciences. Accepted by the 16th International Conference on Frontiers in Education: Computer Science and Computer Engineering (FECS 2020), Springer, 2020.
[11]. Carlos A. Barajas, Matthias K. Gobbert, Jianwu Wang. Tornado Storm Data Synthesization using Deep Convolutional Generative Adversarial Network. Accepted by the 16th International Conference on Data Science (ICDATA 2020), Springer, 2020.
[10]. Ping Hou, Peng Wu, Pei Guo, Jianwu Wang, Aryya Gangopadhyay, Zhibo Zhang, A Deep Learning Model for Detecting Dust in Earth’s Atmosphere from Satellite Remote Sensing Data, accepted by the Sixth IEEE International Conference on Smart Computing (SMARTCOMP 2020).
[9]. Pei Guo, Chen Liu, Yan Tang, Jianwu Wang. Parallel Gradient Boosting based Granger Causality Learning. In Proceedings of the 2019 IEEE International Conference on Big Data (BigData 2019), pages: 2845 - 2854, IEEE, 2019.
[8]. Carlos A. Barajas, Matthias K. Gobbert, and Jianwu Wang. Performance Benchmarking of Data Argumentation and Deep Learning for Tornado Prediction. In Proceedings of The Third IEEE International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD 2019) at the IEEE Big Data Conference, 2019, [
pdf].
[6]. Peichang Shi, Qianqian Song, Janita Patwardhan, Zhibo Zhang, Jianwu Wang,
Aryya Gangopadhyay. A hybrid algorithm for mineral dust detection using satellite data. In
Proceedings of the 15th IEEE International Conference on e-Science (e-Science2019), IEEE,
2019.
[5]. Zhibo Zhang, Hua Song, Po-Lun Ma, Vincent E. Larson, Minghuai Wang, Xiquan Dong, Jianwu Wang. Subgrid Variations of the Cloud Water and Droplet Number Concentration over the Tropical Ocean: Satellite Observations and Implications for Warm Rain Simulations in Climate Models, Atmospheric Chemistry and Physics, 19(2), pages 1077-1096, 2019. https://doi.org/10.5194/acp-19-1077-2019, 2019.
[4]. Hua Song, Jianwu Wang, Jing Tian, Jingfeng Huang, Zhibo Zhang, Spatio-temporal climate data
causality analytics – an analysis of ENSOS’s global impacts, In Proceedings from the 8th
International Workshop on Climate Informatics, 2018.
[3]. Wenbin Zhang, Jianwu Wang, Daeho Jin, Lazaros Oreopoulos, Zhibo Zhang, A Deterministic
Self-Organizing Map Approach and its Application on Satellite Data based Cloud Type
Classification, In Proceedings of the 2018 IEEE International Conference on Big Data
(BigData 2018), pages 2026-2033, 2018.
[2]. Carlos Barajas, Pei Guo, Lipi Mukherjee, Susan Hoban, Jianwu Wang, Daeho Jin, Aryya
Gangopadhyay, Matthias K. Gobbert. Benchmarking Parallel Implementations of K-Means Cloud
Type Clustering from Satellite Data. Accepted by 2018 BenchCouncil International Symposium
on Benchmarking, Measuring and Optimizing (Bench 18), 2018.
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[18]. Gerson C. Kroiz, Jonathan N. Basalyga, Uchendu Uchendu, Reetam Majumder, Carlos A. Barajas, Matthias K. Gobbert, Kel Markert, Amita Mehta, and Nagaraj K. Neerchal. Stochastic Precipitation Generation for the Potomac River Basin using Hidden Markov Models. Technical Report HPCF-2020-11, UMBC High Performance Computing Facility, University of Maryland, Baltimore County, 2020. (HPCF machines used: taki), [
pdf].
[17]. Christine Abraham, Olivia Norman, Erick Shepherd, Jianyu Zheng, and Zhibo Zhang. Studying Anomalous Discrepancies between MODIS and CALIOP Cloud Observations. Technical Report HPCF-2020-12, UMBC High Performance Computing Facility, University of Maryland, Baltimore County, 2020. (HPCF machines used: taki), [
pdf].
[16]. Sahara Ali, Xin Huang, Achala Wickramasuriya Denagamage, Neranga Prasadi, Jianyu Zheng, Pei Guo, and Jianwu Wang. Evaluation of Tropical Cloud Simulations between CMIP6 Models and Satellite Observations. Technical Report HPCF-2019-13, UMBC High Performance Computing Facility, University of Maryland, Baltimore County, 2020. (HPCF machines used: taki), [
pdf].
[15]. Jonathan N. Basalyga, Gerson C. Kroiz, Carlos A. Barajas, Matthias K. Gobbert, Paul Maggi, and Jerimy Polf. Use of Deep Learning to Classify Compton Camera Based Prompt Gamma Imaging for Proton Radiotherapy. Technical Report HPCF-2020-14, UMBC High Performance Computing Facility, University of Maryland, Baltimore County, 2020. (HPCF machines used: taki), [
pdf].
[14]. Kallista Angeloff, Kirana Bergstrom, Tianhao Le, Chengtao Xu, Jianyu Zheng, and Zhibo Zhang. Machine Learning for Retrieving Cloud Optical Thickness from Observed Reflectance: 3D effects. Technical Report HPCF-2020-15, UMBC High Performance Computing Facility, University of Maryland, Baltimore County, 2020. (HPCF machines used: taki), [
pdf].
[13]. Yiyi Huang, Matthäus Kleindessner, Alexey Munishkin, Debvrat Varshney, Pei Guo, and Jianwu Wang. Benchmarking of Data-driven Causality Discovery Approaches in the Interactions of Arctic Sea Ice and Atmosphere. Technical Report HPCF-2020-16, UMBC High Performance Computing Facility, University of Maryland, Baltimore County, 2020. (HPCF machines used: taki), [
pdf].
[12]. Julie Bessac, Ling Xu, Manzhu Yu, Pei Guo, and Aryya Gangopadhyay. Image Segmentation for Dust Detection using Unsupervised Machine Learning. Technical Report HPCF-2020-17, UMBC High Performance Computing Facility, University of Maryland, Baltimore County, 2020. (HPCF machines used: taki), [
pdf].
[11]. Brice Coffer, Michaela J. Kubacki, Yixin Wen, Ting Zhang, Carlos Barajas, and Matthias K. Gobbert. Using Machine Learning Techniques for Supercell Tornado Prediction with Environmental Sounding Data. Technical Report HPCF-2020-18, UMBC High Performance Computing Facility, University of Maryland, Baltimore County, 2020. (HPCF machines used: taki), [
pdf ]
[10]. Reetam Majumder, Redwan Walid, Jianyu Zheng, Carlos Barajas, Pei Guo, Chamara Rajapakshe, Aryya Gangopadhyay, Matthias K. Gobbert, Jianwu Wang, Zhibo Zhang, Kel Markert, Amita Mehta, and Nagaraj K. Neerchal. Assessing Water Budget Sensitivity to Precipitation Forcing Errors in Potomac River Basin Using the VIC Hydrologic Model. Technical Report HPCF-2019-11, UMBC High Performance Computing Facility, University of Maryland, Baltimore County, 2019. (HPCF machines used: taki.). [
pdf].
[9]. Steven Randal Hussung, Mengxi Wu, Akila Sampath, Suhail Mahmud, Pei Guo, and Jianwu Wang. Evaluation of Data-Driven Causality Discovery Approaches among Dominant Climate Modes. Technical Report HPCF-2019-12, UMBC High Performance Computing Facility, University of Maryland, Baltimore County, 2019. (HPCF machines used: taki), [
pdf].
[8]. Charlie Becker, Will D. Mayfield, Sarah Y. Murphy, Bin Wang, Carlos Barajas, and Matthias K. Gobbert. An approach to tuning hyperparameters in parallel: A performance study using climate data. Technical Report HPCF-2019-13, UMBC High Performance Computing Facility, University of Maryland, Baltimore County, 2019. (HPCF machines used: taki), [
pdf].
[7]. Ping Hou, Peng Wu, Pei Guo, and Aryya Gangopadhyay. Deep Learning Based Mineral Dust Detection and Feature Selection. Technical Report HPCF-2019-14, UMBC High Performance Computing Facility, University of Maryland, Baltimore County, 2019. (HPCF machines used: taki), [
pdf].
[6]. Changjie Cai, Jangho Lee, Yingxi Rona Shi, Camille Zerfas, Pei Guo, and Zhibo Zhang. Dust Detection in Satellite Data using Convolutional Neural Networks. Technical Report HPCF-2019-15, UMBC High Performance Computing Facility, University of Maryland, Baltimore County, 2019. (HPCF machines used: taki), [
pdf].
[5]. Noah Sienkiewicz, Arjun Pandya, Tim Brown, Carlos Barajas, and Matthias K. Gobbert, Numerical
Methods for Parallel Simulation of Diffusive Pollutant Transport from a Point Source, Technical
Report HPCF-2018-11, UMBC High Performance Computing Facility, University of Maryland, Baltimore
County, 2018. (HPCF machines used: maya), [
pdf].
[4]. Carlos Barajas, Lipi Mukherjee, Pei Guo, Susan Hoban, Daeho Jin, Aryya Gangopadhyay, and Jianwu
Wang. Benchmarking parallel implementations of cloud type clustering from satellite data,
Technical Report HPCF-2018-12, UMBC High Performance Computing Facility, University of Maryland,
Baltimore County, 2018. (HPCF machines used: maya), [
pdf].
[3]. Peichang Shi, Qianqian Song, Janita Patwardhan, Zhibo Zhang, and Jianwu Wang, Mineral Dust
Detection Using Satellite Data, Technical Report HPCF-2018-13, UMBC High Performance Computing
Facility, University of Maryland, Baltimore County, 2018. (HPCF machines used: maya), [
pdf].
[2]. Hua Song, Jing Tian, Jingfeng Huang, Jianwu Wang, and Zhibo Zhang, Causality Analysis of ENSO’s
Global Impacts on Climate Variables based on Data-driven Analytics and Climate Model Simulation,
Technical Report HPCF-2018-14, UMBC High Performance Computing Facility, University of Maryland,
Baltimore County, 2018. (HPCF machines used: maya), [
pdf].
[1]. Yunwei Cui, Meng Gao, Scott Hottovy, Chamara Rajapakshe, and Zhibo Zhang, The impacts of 3D
radiative transfer effects on cloud radiative property simulations and retrievals, Technical
Report HPCF-2018-15, UMBC High Performance Computing Facility, University of Maryland, Baltimore
County, 2018. (HPCF machines used: maya), [
pdf].
[3]. Deepak Prakash. Benchmarking of Parallel Climate Data Aggregation in a Distributed Environment. M.S. Thesis, Department of Information Systems, University of Maryland, Baltimore County, 2019. (HPCF machines used: taki).
[2]. Carlos Alexander Barajas. An Approach to Tuning Hyperparameters in Parallel: A Performance Study Using Climate Data. M.S. Thesis, Department of Mathematics and Statistics, University of Maryland, Baltimore County, 2019. (HPCF machines used: taki).
[1]. Savio Sebastian Kay. Efficient Scientific Big Data Aggregation through Parallelization and Subsampling. M.S. Thesis, Department of Information Systems, University of Maryland, Baltimore County, 2019. (HPCF machines used: taki).
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