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[2021/12]: This webpage is only in maintenance mode. Please check up-to-date information from our lab website, including his new personnal webpage at the website.

Education

• 2001.9 ~ 2007.7 Ph.D. in Computer Software and Theory, Institute of Computing Technology, University of the Chinese Academy of Sciences. Dissertation: "A Domain Oriented and Business User Friendly Service Model".

• 1997.9 ~ 2001.7 B.S. in Computer Science and Technology. Tianjin University

Employment

• 2021.7 ~ Present Associate Professor at the Department of Information Systems, University of Maryland, Baltimore County Baltimore, MD, U.S.A.

• 2021.5 ~ Present Affiliated Faculty at the Center for Real-time Distributed Sensing and Autonomy (CARDS), University of Maryland, Baltimore County Baltimore, MD, U.S.A.

• 2018.8 ~ Present Affiliated Faculty at the Joint Center for Earth Systems Technology (JCET) , University of Maryland, Baltimore County Baltimore, MD, U.S.A.

• 2018.8 ~ Present Affiliated Faculty at the NSF IUCRC Center for Accelerated Real Time Analytics (CARTA), University of Maryland, Baltimore County Baltimore, MD, U.S.A.

• 2015.8 ~ 2021.6 Assistant Professor at the Department of Information Systems, University of Maryland, Baltimore County Baltimore, MD, U.S.A.

Awards

• CAREER Award, National Science Foundation (NSF), 2020.

• Early-Career Faculty Excellence Award, UMBC, 2019.

Grants

• NSF Institute: Harnessing Data and Model Revolution in the Polar Regions (iHARP), NSF, Co-PI.

• REU Site: Online Interdisciplinary Big Data Analytics in Science and Engineering, NSF, PI.

• CAREER: Big Data Climate Causality Analytics, NSF, PI.

• Developing Passive Satellite Cloud Remote Sensing Algorithms using Collocated Observations, Numerical Simulation and Deep Learning, NASA, PI.

• Efficient and Flexible Aggregation and Distribution of MODIS Atmospheric Products based on Climate Analytics-as-a-Service Framework, NASA, PI.

• Low-Code Workflow Software for Life Sciences, Maryland Industrial Partnerships (MIPS) Program, PI.

• CrossTraining of Researchers in Computing, Applied Mathematics and Atmospheric Sciences using Advanced Cyberinfrastructure Resources, NSF, PI.

• MRI: Acquisition of Cutting-Edge GPU and Phi Nodes for the Interdisciplinary UMBC High Performance Computing Facility, NSF, Co-PI.

• Large-Scale Climate Analytics based on Satellite Data, Microsoft, PI.

• Addressing Fundamental Sensing and Data Processing Problems in Sustainable Farms, UMBC, Co-PI.

• The Smart Manufacturing Leadership Coalition (SMLC), DOE.

• Scientific Workflow Scheduling on Cloud, Amazon (2010.3-2013.2).

News

• UMBC to lead climate-focused NSF data science institute through $13M award

• Congratulations to, Sahara Ali, our PhD student, who will be an ESIP Community Fellow and help bridge the gap between informatics and Earth science.

• UMBC offers new Research Experiences for Undergraduates in smart computing, big data

• NASA awards UMBC team $1.4M to develop AI that improves how computers process climate data from satellites

• UMBC's Jianwu Wang receives NSF CAREER Award to help climate scientists make discoveries from massive, complex data sets

• UMBC receives NSF grant to launch first-of-its-kind big data and high-performance computing training for researchers across disciplines

Students

• Current PhD Students

• Arjun Pandya, Spring 2018-.

• Xin Wang, Fall 2018-.

• Xin Huang, Spring 2020-.

• Sahara Ali, Spring 2020-.

• Oluwatobiloba (Tobi) Odunsi, Spring 2021-.

• Xingyan Li, Fall 2021-.

• Seraj Mostafa, Fall 2021-.

• Graduated Students

• Pei Guo, Spring 2017 - Spring 2021. Ph.D. '21, Doctoral Thesis: Scalable Multivariate Causality Discovery From Large-scale Global Spatiotemporal Climate Data. Position after graduation: Data Scientist, Wyze Labs.

• Wenbin Zhang, Fall 2016-Fall 2020. Ph.D. '20, Doctoral Thesis: Learning Fairness and Graph Deep Generation in Dynamic Environments. Position after graduation: Post-doc, Machine Learning Department at Carnegie Mellon University.

• Rishi Sankineni, M.S. '17, Master Thesis: Parallel Feature Selection of Multiple Class Datasets using Apache Spark. Position after graduation: Data Scientist, Kaiser Permanente.

• Sarthak Bhatt, M.S. '17, Position after graduation: Full Stack Developer, Sparksoft Corporation.

• Savio Kay, M.S. '19, Master Thesis: A Big Data Study on Scientific Dataset Subsampling for Faster Data Aggregation Using Xarray And Dask. Position after graduation: Associate Programmer, Emmes.

• Deepak Prakash, M.S. '19. Master Thesis: Benchmarking of Parallel Climate Data Aggregation in a Distributed Environment. Position after graduation: Data Analyst and Business Intelligence Analyst at PNC Financial Services.

Teaching

• IS 651 - Distributed Systems, IS Department, UMBC: Fall 2015, Spring 2016, Spring 2017, Fall 2017, Spring 2018, Spring 2019, Fall 2020,

• IS 410 - Introduction to Database Design, IS Department, UMBC: Fall 2019, Spring 2020

• IS698/MATH700/PHYS650: Special topics on Big Data + High-Performance Computing + Atmospheric Sciences, UMBC: Spring 2018, Spring 2019, Spring 2020

• IS 789 - Big Data Fundamentals and Techniques, IS Department, UMBC, Fall 2019

• CMSC106 - Introduction to C Programming, CS Department, UMD, Fall 2014

• CSE21 - Mathematics for Algorithms and Systems Analysis, CSE Department, UCSD, Summer Session II, 2013

Selected Professional Services (Full List)

• Journal Editor

• Associate Editor at Frontiers in Big Data

• Guest Editor on Special Issue on Benchmarking, Performance Tuning and Optimization for Big Data Analytics at Big Data Research, Elsevier, 2020.

• Guest Editor on Special Issue on Big Data in Ubiquitous Computing at IEEE Transactions on Big Data, IEEE, 2017.

• Editorial Board Member of Future Generation Computer Systems (FGCS), Elsevier Press, 2016-2019

• Editorial Board Member of Services Transactions on Internet of Things (STIOT), 2015-2017

• Associate Editor of International Journal of Computers and Their Applications (IJCA), 2013-2016

• Editorial Board Member of Cluster Computing, Springer Press, 2012-2015

• Guest Editor on Special Issue on Service and Cloud Based Data Integration at Journal of Grid Computing, Springer Press, Published June 2014.

• Workshop Co-Chair

• The International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications: 2017-present at IEEE Big Data Conference (IEEE BigData) .

• The Third International Workshop on Advances in the Kepler Scientific Workflow System and Its Applications (Kepler 2016)

• The International Workshop on Service and Cloud Based Data Integration (SCDI): 2012 and 2014

• The Second International Workshop on Advances in Data and Information Management: Recent Advances of Cloud Computing in Data and Information Management (ADIM 2011)

• Conference Organization Committee

• Publication Chair, 23rd International Conference on Distributed Computing and Networking (ICDCN 2022)

• Workshop Chair, 2021 IEEE International Conference on Big Data (IEEE BigData 2021)

• Poster Chair, 2020 IEEE International Conference on Big Data (IEEE BigData 2020)

• Student Travel Award Chair, 2019 IEEE International Conference on Big Data (IEEE BigData 2019)

• Poster Chair, 2019 IEEE 15th International eScience Conference (IEEE eScience 2019)

• Student Travel Award Chair, 2017 IEEE International Conference on Big Data (IEEE BigData 2017)

• Short Paper Track Chair, The 6th IEEE International Congress on Big Data (BigDataCongress 2017)

• Area Chair, Scientific Workflows, The 13th IEEE International Conference on Services Computing (SCC 2016)

• Track Chair, Internet of Things (IoT) and Collaboration, The 13th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2017)

• Poster Chair, 2016 IEEE International Conference on Big Data (IEEE BigData 2016)

• Journal Special Issue Chair, The 14th IEEE International Conference on Ubiquitous Intelligence and Computing (IEEE UIC 2017)

• Journal Reviewer (Selected)

• Journal of Grid Computing, Springer Press

• IEEE Transactions on Services Computing

• IEEE Transactions on Automation Science and Engineering

• IEEE Transactions on Emerging Topics in Computing

• IEEE Transactions on Cloud Computing

• IEEE/ACM Transactions on Computational Biology and Bioinformatics

• Information Systems Frontiers, Springer Press

• Book Editorial Advisory Board Member

• Service-Oriented Methodology and Technologies for Cloud Computing, IGI Global Press

• Service-driven Approaches to Architecture and Enterprise Integration, IGI Global Press

• Program Committee Member (Selected)

• 41st IEEE International Conference on Distributed Computing Systems (ICDCS 2021)

• 2020 IEEE International Conference on Big Data (IEEE BigData 2020)

• The 18th International Conference on Service Oriented Computing (ICSOC 2020)

• The 15th IEEE International Conference on eScience (IEEE eScience 2019)

• The 48th International Conference on Parallel Processing (ICPP 2019)

• IEEE International Congress on Big Data (IEEE BigDataCongress 2019)

• The International Conference on Computational Science (ICCS 2019)

• IEEE International Conference on Data Engineering, Applications Track (ICDE 2017)

Publications

• 2021:

[117]. Eliot Kim, Peter Kruse, Skylar Lama, Jamal Bourne, Michael Hu, Sahara Ali, Yiyi Huang, Jianwu Wang. Multi-Task Deep Learning Based Spatiotemporal Arctic Sea Ice Forecasting. Accepted by the 2021 IEEE International Conference on Big Data (BigData 2021), IEEE.

[116]. James R. Clavin, Yue Huang, Xin Wang, Pradeep M. Prakash, Sisi Duan, Jianwu Wang, Sean Peisert. Accepted by the 27th IEEE International Conference on Parallel and Distributed Systems (ICPADS 2021).

[115]. 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.

[114]. 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. https://www.climatechange.ai/papers/icml2021/50.

[113]. 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.

[112]. 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).

[111]. 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.

[110]. Jonathan N. Basalyga, Carlos A. Barajas, Matthias K. Gobbert, 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.

[109]. Jangho Lee, Yingxi R. Shi, Changjie Cai, Pubu Ciren, Jianwu Wang, Aryya Gangopadhyay, Zhibo Zhang. Machine Learning Based Algorithms for Global Dust Aerosol Detection from Satellite Images: Inter-Comparisons and Evaluation. Remote Sensing, vol. 13, no. 3: 456, 2021. https://doi.org/10.3390/rs13030456.

[108]. Weilong Ding, Zhe Wang, Jun Chen, Yanqing Xia, Jianwu Wang, Zhuofeng Zhao, Potential Trend Discovery for Highway Drivers on Spatio-temporal Data. Wireless Networks, Feb, pages 1-16, Springer, 2021. https://doi.org/10.1007/s11276-020-02536-4

[107]. Jianwu Wang, Matthias K. Gobbert, Zhibo Zhang, Aryya Gangopadhyay. Team-Based Online Multidisciplinary Education on Big Data + High-Performance Computing + Atmospheric Sciences. In: Arabnia H.R., Deligiannidis L., Tinetti F.G., Tran QN. (eds) Advances in Software Engineering, Education, and e-Learning. Transactions on Computational Science and Computational Intelligence. pages 43-54, Springer, Cham, 2021. DOI: 10.1007/978-3-030-70873-3_4

[106]. Carlos A. Barajas, Matthias K. Gobbert, Jianwu Wang. Tornado Storm Data Synthesization using Deep Convolutional Generative Adversarial Network. In: Stahlbock R., Weiss G.M., Abou-Nasr M., Yang CY., Arabnia H.R., Deligiannidis L. (eds) Advances in Data Science and Information Engineering. Transactions on Computational Science and Computational Intelligence. pages 383-388, Springer, Cham, 2020. DOI: 10.1007/978-3-030-71704-9_25.

• 2020:

[105]. Xin Huang, Sahara Ali, Chenxi Wang, Zeyu Ning, Sanjay Purushotham, Jianwu Wang, Zhibo Zhang. Deep Domain Adaptation based Cloud Type Detection using Active and Passive Satellite Data. In Proceedings of the 2020 IEEE International Conference on Big Data (BigData 2020), pages 1330-1337, IEEE, 2020.

[104]. Manzhu Yu, Julie Bessac, Ling Xu, Aryya Gangopadhyay, Yingxi Shi, Jianwu Wang. Image Segmentation for Dust Detection using Semi-supervised Machine Learning. In Proceedings of the 2020 IEEE International Conference on Big Data (BigData 2020), pages 1745-1754, IEEE, 2020.

[103]. Arjun Pandya, Oluwatobiloba Odunsi, Chen Liu, Alfredo Cuzzocrea, Jianwu Wang. Adaptive and Efficient Streaming Time Series Forecasting with Lambda Architecture and Spark. In Proceedings of the 2020 IEEE International Conference on Big Data (BigData 2020), pages 5182-5190, IEEE, 2020.

[102]. Wenbin Zhang, Mingli Zhang, Ji Zhang, Zhen Liu, Zhiyuan Chen, Jianwu Wang, Edward Raff, Enza Messina. Flexible and Adaptive Fairness-aware Learning in Non-stationary Data Streams. In Proceedings of the 32nd International Conference on Tools with Artificial Intelligence (ICTAI 2020), pages 399-406, IEEE, 2020.

[101]. Wanghu Chen, Bo Yang, Jing Li, Jianwu Wang. An Approach to Detecting Diabetic Retinopathy based on Integrated Shallow Convolutional Neural Networks. IEEE ACCESS, 8, pages 178552-178562 IEEE, 2020.

[100]. Jianwu Wang, Xin Huang, Jianyu Zheng, Chamara Rajapakshe, Savio Kay, Lakshmi Kandoor, Thomas Maxwell, Zhibo Zhang. Scalable Aggregation Service for Satellite Remote Sensing Data. In Proceedings of the 20th International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP 2020), pages 184-199, Springer, 2020. DOI: 10.1007/978-3-030-60239-0_13.

[99]. Pei Guo, Achuna Ofonedu, Jianwu Wang. Scalable and Hybrid Ensemble-Based Causality Discovery. In Proceedings of the 2020 IEEE International Conference on Smart Data Services (SMDS 2020), pages 72-80, IEEE, 2020. DOI: 10.1109/SMDS49396.2020.00016 Best Student Paper Award!

[98]. Weilong Ding, Zhe Wang, Jianwu Wang, Yanbo Han. Trends Drift Discovery for Individual Highway Drivers through Ensemble Learning. In Proceedings of the 9th SIGKDD International Workshop on Urban Computing (UrbComp 2020).

[97]. 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) .

[96]. Weilong Ding, Zhuofeng Zhao, Jianwu Wang, Han Li. Task Allocation in Hybrid Big Data Analytics for Urban IoT Applications. ACM/IMS Transactions on Data Science, 1(3), pages 1-22, 2020.

[95]. 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. 2020 IEEE International Conference on Smart Computing (SMARTCOMP), pages 196-201, 2020. DOI: 10.1109/SMARTCOMP50058.2020.00045.

• 2019:

[94]. Zhong Liu, Jianwu Wang, Shimei Pan, David Meyer. Improving Reproducibility in Earth Science Research. Eos, 100, https://doi.org/10.1029/2019EO136216, 2019.

[93]. Wenbin Zhang, Xuejiao Tang, Jianwu Wang. On Fairness-Aware Learning for Non-discriminative Decision-Making. In Proceedings of the 2019 International Conference on Data Mining Workshops (ICDMW), Beijing, China, pages 1072-1079, 2019.

[92]. Wanghu Chen, Chao Wang, Jing Li, Bo Yang, Yang Liu, Jianwu Wang. Benchmarking Discretisation Level of Continuous Attributes: Theoretical and Experimental Approaches. In Proceedings of the Third IEEE International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD 2019), IEEE, 2019.

[91]. Carlos Barajas, Matthias Gobbert, Jianwu Wang. Performance Benchmarking of Data Augmentation and Deep Learning for Tornado Prediction. Accepted by the Third IEEE International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD 2019).

[90]. Wanghu Chen, Jing Li, Xintian Li, Lizhi Zhang, Jianwu Wang. Training Back Propagation Neural Networks in MapReduce on High-dimensional Big Datasets with Global Evolution. In IEEE Access, IEEE, 2019. Digital Object Identifier: 10.1109/ACCESS.2019.2951189,[Preprint].

[89]. 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.

[88]. Yan Tang, Jianwu Wang, Mai Nguyen, Ilkay Altintas. PEnBayes: A Multi-Layered Ensemble Approach for Learning Bayesian Network Structure from Big Data. Volume 19, Issue 20, Article 4400. Sensors, MDPI, 2019.

[87]. Hua Song, Jing Tian, Jingfeng Huang, Pei Guo, Zhibo Zhang, Jianwu Wang. Hybrid Causality Analysis of ENSO's Global Impacts on Climate Variables based on Data-driven Analytics and Climate Model Simulation. Volume 7, Article 233. Interdisciplinary Climate Studies Section, Frontiers in Earth Science, Frontiers, doi: 10.3389/feart.2019.00233, 2019.

[86]. 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 eScience (eScience2019), pages 39-46, IEEE, 2019.

[85]. Shouli Zhang, Chen Liu, Jianwu Wang, Zhongguo Yang, Yanbo Han. Latency-Aware Deployment of IoT Services in a Cloud-Edge Environment. In Proceedings of the 17th International Conference on Service Oriented Computing (ICSOC2019), pages 231-236, Springer, 2019.

[84]. Pei Guo, Raymond Peterson, Paul Paukstelis, Jianwu Wang. Cloud-based Life Sciences Manufacturing System: Integrated Experiment Management and Data Analytics via Amazon Web Services, In Proceedings of the 2019 INFORMS Conference on Service Science (INFORMS-CSS2019), pages 149-159, Springer, 2019.

[83]. Hailun Lin, Yong Liu, Peng Zhang, and Jianwu Wang. Representation Learning of Taxonomies for Taxonomy Matching, In Proceedings of the 2019 International Conference on Computational Science (ICCS 2019), pages 383-397, Springer, 2019.

[82]. 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, https://doi.org/10.5194/acp-19-1077-2019, 2019.

• 2018:

[81]. Jianwu Wang, Qiang Duan. Big Data Helps SDN to Manage Traffic. In J. Taheri (eds), Big Data and Software Defined Networks. ISBN: 978-1-78561-304-3, pages 376-388, The Institution of Engineering and Technology, 2018.

[80]. Jianwu Wang, Chen Liu, Meiling Zhu, Pei Guo, Yapeng Hu. Sensor Data based System-level Anomaly Prediction for Smart Manufacturing. In Proceedings of the 2018 IEEE 8th International Congress on Big Data (BigData Congress 2018), pages 158-165, IEEE, 2018.

[79]. Wanghu Chen, Xiaoyan Liang, Jing Li, Hongwu Qin, Yuxiang Mu, Jianwu Wang. Blockchain based Provenance Sharing of Scientific Workflows. In Proceedings of the Second International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD 2018) at IEEE Big Data Conference (IEEE BigData 2018), pages 3814-3820. IEEE, 2018.

[78]. Hua Song, Jianwu Wang, Jing Tian, Jingfeng Huang, Zhibo Zhang. Spatio-temporal climate data causality analytics - an analysis of ENSO's global impacts, In Proceedings of the 8th International Workshop on Climate Informatics, pages 45-48, 2018.

[77]. 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, IEEE, 2018.

[76]. Wenbin Zhang, Jianwu Wang. Content-bootstrapped Collaborative Filtering for Medical Article Recommendations. In Proceedings of the 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2018), pages 1184-1188, IEEE, 2018.

[75]. Prakashan Korambath, Hari S. Ganesh, Jianwu Wang, Michael Baldea, and Jim Davis. Use of On-Demand Cloud Services to Model the Optimization of an Austenitization Furnace. Smart and Sustainable Manufacturing Systems, Vol. 2, No. 1, pages 165-179, https://doi.org/10.1520/ SSMS20180024. ISSN 2520-6478, 2018.

[74]. Arjun Pandya, Chaitanya Kulkarni, Kunal Mali, Jianwu Wang. An Open Source Cloud-based NoSQL and NewSQL Database Benchmarking Platform for IoT Data. Accepted by 2018 BenchCouncil International Symposium on Benchmarking, Measuring and Optimizing (Bench 18), 2018.

[73]. Peng Zhang, Yan Li, Hailun Lin, Jianwu Wang, Chuang Zhang, A Periodic Task-Oriented Scheduling Architecture in Cloud Computing, In Proceedings of the 16th IEEE International Symposium on Parallel and Distributed Processing with Applications (IEEE ISPA 2018), pages 788-794, 2018.

[72]. 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.

• 2017:

[71]. Shouli Zhang, Xiaohong Li, Jianwu Wang, Shen Su. Curve-Registration-Based Feature Extraction for Predictive Maintenance of Industrial Equipment, In Proceedings of the International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2017), pages 253-263, Springer, 2017.

[70]. Pei Guo, Jianwu Wang, Zhiyuan Chen. A Comparison of Big Data Application Programming Approaches: A Travel Companion Case Study, In Proceedings of the First International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD 2017) at IEEE Big Data Conference (IEEE BigData 2017), pages 2787-2796, 2017 [Preprint]

[69]. Wanghu Chen, Xintian Li, Jing Li, Jianwu Wang. Enhancing the MapReduce Training of BP Neural Networks Based on Local Weight Matrix Evolution, In Proceedings of the First International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD 2017) at IEEE Big Data Conference (IEEE BigData 2017).

[68]. Jianwu Wang, Matthias Gobbert, Zhibo Zhang, Aryya Gangopadhyay and Glenn Page. Multidisciplinary Education on Big Data + HPC + Atmospheric Sciences, In Proceedings of the Workshop on Education for High-Performance Computing (EduHPC-17) at SC'2017.

[67]. Meiling Zhu, Chen Liu, Jianwu Wang, Shen Su, Yanbo Han. An Approach to Modeling and Discovering Event Correlations for Service Collaboration, Accepted by International Conference on Service-Oriented Computing (ICSOC 2017) (Accepatance rate: 18.4%).

[66]. Meiling Zhu, Chen Liu, Jianwu Wang, Shen Su, Yanbo Han. Service Hyperlink: Modeling And Reusing Partial Process Knowledge By Mining Event Dependencies Among Sensor Data Services, In Proceedings of the 24th IEEE International Conference on Web Services (IEEE ICWS 2017), pages 902-905, IEEE, 2017.

[65]. Wenbin Zhang, Jianwu Wang. A Hybrid Learning Framework for Imbalanced Stream Classification, In Proceedings of the 2017 IEEE 6th International Congress on Big Data (BigData Congress 2017), pages 480-487 [Preprint].

[64]. Sai C. Pallaprolu, Rishi Sankineni, Muthukumar Thevar, George Karabatis, Jianwu Wang. Zero-day Attack Identification in Streaming data using Semantics and Spark. In Proceedings of the IEEE 6th International Congress on Big Data (BigData Congress 2017), pages 121-128, [Preprint].

[63]. Lina Zhou, Shimei Pan, Jianwu Wang, Athanasios V. Vasilakos. Machine Learning on Big Data: Opportunities and Challenges, Vol. 237, pages 350-361, Neurocomputing, Elsevier Press, 2017.

• 2016:

[62]. Jianwu Wang, Zhichuan Huang, Wenbin Zhang, Ankita Patil, Ketan Patil, Ting Zhu, Eric J Shiroma, Mitchell A Schepps, and Tamara B Harris. Wearable Sensor based Human Posture Recognition, In Proceedings of the 3rd Annual Workshop on Big Data Analytic Technology for Bioinformatics and Health Informatics (KDDBHI 2016) at 2016 IEEE International Conference on Big Data (IEEE BigData 2016), pages 3432-3438.

[61]. Zhichuan Huang, Tiantian Xie, Ting Zhu, Jianwu Wang, and Qingquan Zhang. Application-Driven Sensing Data Reconstruction and Selection Based on Correlation Mining and Dynamic Feedback, In Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), pages 1322-1327.

[60]. Jianwu Wang, Moustafa AbdelBaky, Javier Diaz-Montes, Shweta Purawat, Manish Parashar, and Ilkay Altintas. Kepler + CometCloud: Dynamic Scientific Workflow Execution on Federated Cloud Resources, In Proceedings of the International Conference on Computational Science 2016 (ICCS 2016), pages 700-711.

[59]. George Karabatis, Jianwu Wang, Ahmed AlEroud. Towards Adaptive Big Data Cyber-attack Detection via Semantic Link Networks. Accepted by the first Workshop of Mission-Critical Big Data Analytics workshop (MCBDA 2016).

[58].Prakashan Korambath, Jianwu Wang, Ankur Kumar, Jim Davis, Robert Graybill, Brian Schott, and Michael Baldea. A Smart Manufacturing Use Case: Furnace Temperature Balancing in Steam Methane Reforming Process via Kepler Workflows . In Proceedings of International Conference on Computational Science 2016 (ICCS 2016), pages 680-689.

[57]. Meiling Zhu, Chen Liu, Jianwu Wang, Xiongbin Wang, Yanbo Han. A Service-Friendly Approach to Discover Traveling Companions based on ANPR Data Stream, In Proceedings of IEEE the 13th 2016 IEEE International Conference on Services Computing (SCC 2016), pages 171-178.

• 2015:

[56]. Jianwu Wang, Daniel Crawl, Shweta Purawat, Mai Nguyen, Ilkay Altintas. Big Data Provenance: Challenges, State of the Art and Opportunities, In Proceedings of 2015 IEEE Conference on Big Data Conference, 2015. [PDF]

[55].Zhuofeng Zhao, Weilong Ding, Jianwu Wang, Yanbo Han. A Hybrid Processing System for Large-Scale Traffic Sensor Data, in IEEE Access, Vol. 3, pages 2341-2351, 2015.

[54]. Meiling Zhu, Chen Liu, Jianwu Wang, Xiongbin Wang, Yanbo Han. Instant Discovery of Moment Companion Vehicles from Big Streaming Traffic Data, In Proceedings of the 2015 International Conference on Cloud Computing and Big Data (CCBD 2015), pages 73-80, 2015.

[53]. Chen Liu, Jianwu Wang, Yanbo Han. Discovery of Service HyperLinks with User Feedbacks for Situational Data Mashup. International Journal of Database Theory and Application. 8(4), pages 71-80, 2015. http://dx.doi.org/10.14257/ijdta.2015.8.4.08

[52]. Yu Qian, Hyunsoo Kim, Shweta Purawat, Jianwu Wang, Rick Stanton, Weijia Xu, Ilkay Altintas, Robert Sinkovits, Alexandra Lee, Richard H. Scheuermann. FlowGate: Towards Extensible and Scalable Web-Based Flow Cytometry Data Analysis. In Proceedings of the 2015 XSEDE Conference: Scientific Advancements Enabled by Enhanced Cyberinfrastructure (XSEDE 2015), ACM, New York, NY, USA, Article No. 5.

[51]. Jim Davis, Thomas Edgar, Robert Graybill, Prakashan Korambath, Brian Schott, Denise Swink, Jianwu Wang, Jim Wetzel. Smart Manufacturing Technology. Annual Review of Chemical and Biomolecular Engineering. Vol. 6, pages 141-160, 2015

• 2014:

[50]. Jianwu Wang, Yan Tang, Mai Nguyen, Ilkay Altintas. A Scalable Data Science Workflow Approach for Big Data Bayesian Network Learning. In Proceedings of the International Symposium on Big Data Computing (BDC 2014), 2014. Acceptance rate: 22%. [PDF]

[49]. Jianwu Wang, Daniel Crawl, Ilkay Altintas, Weizhong Li. Big Data Applications using Workflows for Data Parallel Computing. Computing in Science & Engineering, 16(4), pages 11-21, July-Aug. 2014, IEEE. [PDF]

[48]. Jianwu Wang, Prakashan Korambath, Ilkay Altintas, Jim Davis, Daniel Crawl. Workflow as a Service in the Cloud: Architecture and Scheduling Algorithms. In Proceedings of International Conference on Computational Science (ICCS 2014), pages 546-556. DOI: 10.1016/j.procs.2014.05.049

[47]. Zhuohui Gan, Jianwu Wang, Nathan Salomonis, Jennifer C. Stowe, Gabriel G. Haddad, Andrew D. McCulloch, Ilkay Altintas and Alexander C. Zambon. MAAMD: A Workflow to Standardize Meta-Analyses and Comparison of Affymetrix Microarray Data , BMC Bioinformatics Journal, 15(1), 69, 2014.

[46]. Chen Liu, Jianwu Wang, Yanbo Han. Mashroom+: An Interactive Data Mashup Approach with Uncertainty Handling. Journal of Grid Computing, 12(2), June 2014, pages 221-244, Springer. DOI: 10.1007/s10723-013-9280-5.

[45]. Prakashan Korambath, Jianwu Wang, Ankur Kumar, Lorin Hochstein, Brian Schott, Robert Graybill, Michael Baldea, and Jim Davis. Deploying Kepler Workflows as Services on a Cloud Infrastructure for Smart Manufacturing. In Proceedings of the Second International Workshop on Advances in the Kepler Scientific Workflow System and Its Applications, at International Conference on Computational Science (ICCS 2014), pages 2254-2259.

[44]. Ruijuan Chen, Xiaohua Wan, Albert Lawrence, Jianwu Wang, Daniel Crawl, Sebastien Phan, Ilkay Altintas, Mark Ellisman. EPiK-a Workflow for Electron Tomography in Kepler. In Proceedings of the Second International Workshop on Advances in the Kepler Scientific Workflow System and Its Applications, at International Conference on Computational Science (ICCS 2014).

[43]. Wanghu Chen, Ilkay Altintas, Jianwu Wang and Jing Li. Enhancing Smart Re-run of Kepler Scientific Workflows based on Near Optimum Provenance Caching in Cloud, In Proceedings of IEEE 2014 Eighth International Symposium on Scientific Workflows and Big Data Science (SWF 2014) , at the 2014 Congress on Services (SERVICES 2014) , pages 2295-2305.

[42]. Zhuofeng Zhao, Weilong Ding, Jianwu Wang. A Spatio-temporal Parallel Processing Platform for Traffic Sensor Data Streams. In Proceedings of the 2014 Asia-Pacific Services Computing Conference (APSCC 2014).

[41]. Xiaoyu Yang, David Wallom, Simon Waddington, Jianwu Wang, Arif Shaon, Brian Matthews, Michael Wilson, Yike Guo, Li Guo, Jon Blower, Athanasios V. Vasilakos, Kecheng Liu, Philip Kershaw. Cloud Computing in e-Science: Research Challenges and Opportunities. Journal of Supercomputing, August 2014, Springer, DOI: 10.1007/s11227-014-1251-5.

[40]. Zhuofeng Zhao, Jun Fang, Weilong Ding, Jianwu Wang. An Integrated Processing Platform for Traffic Sensor Data and Its Applications in Intelligent Transportation Systems, In Proceedings of IEEE 2014 Second International Workshop on Service and Cloud Based Data Integration (SCDI 2014), at the 2014 Congress on Services (SERVICES 2014).

[39]. Pek U. Ieong, Jesper Sorensen, Prasantha L. Vemu, Celia W. Wong, Ozlem Demir, Nadya P. Williams, Jianwu Wang, Daniel Crawl, Robert V. Swift, Robert D. Malmstrom, Ilkay Altintas, Rommie E. Amaro. Progress towards automated Kepler scientific workflows for computer-aided drug discovery and molecular simulations. In Proceedings of the Second International Workshop on Advances in the Kepler Scientific Workflow System and Its Applications, at International Conference on Computational Science (ICCS 2014), pages 1745-1755.

• 2013:

[38]. Jianwu Wang, Daniel Crawl, Ilkay Altintas, Kostas Tzoumas, Volker Markl. Comparison of Distributed Data-Parallelization Patterns for Big Data Analysis: A Bioinformatics Case Study. In Proceedings of The Fourth International Workshop on Data Intensive Computing in the Clouds (DataCloud) 2013 at International Conference for High Performance Computing, Networking, Storage and Analysis, (SC'13).[PDF][Slides]

[37]. Marcin Plociennik, Tomasz Zok, Ilkay Altintas, Jianwu Wang, Daniel Crawl, David Abramson, Frederic Imbeaux, Bernard Guillerminet, Marcos Lopez-Caniego, Isabel Campos Plasencia, Wojciech Pych, Pawel Ciecielag, Bartek Palak, Michal Owsiak, Yann Frauel and ITM-TF contributors. Approaches to Distributed Execution of Scientific Workflows in Kepler. In Fundamenta Informaticae, 128(3), 2013, [PDF].

[36]. Chen Liu, Jianwu Wang, Yanbo Han. Situation-Aware Data Service Composition Based on Service Hyperlinks. In Proceedings of the Sixth International Workshop on Personalization in Cloud and Service Computing (PCS 2013) at The 14th International Conference on Web Information System Engineering (WISE 2013), pages 153-167.

• 2012:

[35]. Cheng Zhang, Xiaofang Zhao, Jianwu Wang. An Item-Targeted User Similarity Method for Data Service Recommendation. In Proceedings of the First International Workshop on Service and Cloud Based Data Integration (SCDI 2012) at IEEE International EDOC Conference.[PDF], pages 172-178.

[34]. Chen Liu, Jianwu Wang, Yan Wen, Yanbo Han. A Unified Data and Service Integration Approach for Dynamic Business Collaboration. In Proceedings of 2012 IEEE the First International Conference on Services Economics .[PDF], pages 54-61.

[33]. Jianwu Wang, Ilkay Altintas. Early Cloud Experiences with the Kepler Scientific Workflow System. In Proceedings of the First International Workshop on Advances in the Kepler Scientific Workflow System and Its Applications at ICCS 2012 Conference.[PDF][Slides], pages 1630-1634.

[32]. Jianwu Wang, Daniel Crawl, Ilkay Altintas. A Framework for Distributed Data-Parallel Execution in the Kepler Scientific Workflow System. In Proceedings of The First International Workshop on Advances in the Kepler Scientific Workflow System and Its Applications at ICCS 2012 Conference.[PDF][Slides], pages 1620-1629.

[31]. Ilkay Altintas, Jianwu Wang, Daniel Crawl, Weizhong Li. Challenges and Approaches for Distributed Workflow-Driven Analysis of Large-Scale Biological Data. In Proceedings of the Workshop on Data analytics in the Cloud (DanaC2012) at EDBT/ICDT 2012 Conference.[PDF], pages 73-78.

[30]. Zhuohui Gan, Jianwu Wang, Nathan Salomonis, Ilkay Altintas, Andrew D. McCulloch, Alex Zambon. MAAMD: A Workflow to Standardize Meta-Analyses of Affymetrix Microarray Data. In Proceedings of 2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology (HISB 2012), pages 120-120, doi: 10.1109/HISB.2012.45, 2012.

• 2011:

[29]. Daniel Crawl Jianwu Wang, Ilkay Altintas. Provenance for MapReduce-based Data-Intensive Workflows. In Proceedings of the Sixth Workshop on Workflows in Support of Large-Scale Science (WORKS11) at Supercomputing 2011 (SC2011) Conference. ACM 2011, pages 21-29.[PDF]

[28]. Jianwu Wang, Prakashan Korambath, Ilkay Altintas. A Physical and Virtual Compute Cluster Resource Load Balancing Approach to Data-Parallel Scientific Workflow Scheduling. In Proceedings of IEEE 2011 Fifth International Workshop on Scientific Workflows (SWF 2011), at 2011 Congress on Services (Services 2011), pages 212-215. [PDF]

[27]. Jianwu Wang, Prakashan Korambath, Seonah Kim, Scott Johnson, Kejian Jin, Daniel Crawl, Ilkay Altintas, Shava Smallen, Bill Labate, Kendall N. Houk. Facilitating E-Science Discovery Using Scientific Workflows on the Grid. In X. Yang, L.Wang, W. Jie (eds), Guide to e-Science: Next Generation Scientific Research and Discovery. ISBN: 978-0-85729-438-8, pages 353-382. Springer, 2011. [PDF]

• 2010:

[26]. Jianwu Wang, Prakashan Korambath, Seonah Kim, Scott Johnson, Kejian Jin, Daniel Crawl, Ilkay Altintas, Shava Smallen, Bill Labate, Kendall N. Houk. Theoretical Enzyme Design Using the Kepler Scientific Workflows on the Grid. In proceedings of the Fifth Workshop on Computational Chemistry and Its Applications (5th CCA) at International Conference on Computational Science (ICCS 2010). [PDF]

• 2009:

[25]. Jianwu Wang, Daniel Crawl, Ilkay Altintas. Kepler + Hadoop : A General Architecture Facilitating Data-Intensive Applications in Scientific Workflow Systems. In Proceedings of the Fourth Workshop on Workflows in Support of Large-Scale Science (WORKS09) at Supercomputing 2009 (SC2009) Conference. ACM 2009, ISBN 978-1-60558-717-2. [PDF][Slides]

[24]. Jianwu Wang, Ilkay Altintas, Parviez R. Hosseini, Derik Barseghian, Daniel Crawl, Chad Berkley, Matthew B. Jones. Accelerating Parameter Sweep Workflows by Utilizing Ad-hoc Network Computing Resources: an Ecological Example. In Proceedings of IEEE 2009 Third International Workshop on Scientific Workflows (SWF 2009), 2009 Congress on Services (Services 2009), pages 267-274. [PDF][Slides]

• 2008:

[23]. Jianwu Wang, Ilkay Altintas, Chad Berkley, Lucas Gilbert, Matt B. Jones. A High-Level Distributed Execution Framework for Scientific Workflows. In Proceedings of workshop SWBES08: Challenging Issues in Workflow Applications, at the Fourth IEEE International Conference on e-Science (e-Science 2008), pages 634-639.[PDF][Slides]

[22]. Jianwu Wang, Jian Yu, Paolo Falcarin, Yanbo Han, Maurizio Morisio. An Approach to Domain-Specific Reuse in Service-Oriented Environments. In Proceedings of the Tenth International Conference on Software Reuse (ICSR 2008), pages 221-232. [PDF]

[21]. Jianwu Wang, Wanghu Chen, Yanbo Han. Domain-oriented and Customizable Service Model. Journal of Computer Engineering, 34(4), 2008. (In Chinese)

[20]. Chen Liu, Yanbo Han, Wanghu Chen, Jianwu Wang. MINI: An Ontology Evolution Algorithm for Reducing Impact Ranges. Chinese Journal of Computers, 31(5), 2008, pages 711-720. (In Chinese)

[19]. Yanbo Han, Jianwu Wang, et al. Domain oriented Business Service Modeling and Service Virtualization. Communications of China Computer Federation. 4(4), 2008, pages 56-63. (In Chinese)

• 2007:

[18]. Jianwu Wang, Jian Yu. A Business-Level Service Model Supporting End User Customization. In Proceedings of the First International Workshop on Telecom Service Oriented Architectures (TSOA-07), at the Fifth International Conference on Service-Oriented Computing (ICSOC 2007).

[17]. Wanghu Chen, Yanbo Han, Jing Wang, Chen Liu, Jianwu Wang. Approach to Adaptive Service Matchmaking. Journal of Southeast University (English Edition). 23(3), 2007.

• 2006:

[16]. Jun Han, Yanbo Han, Yan Jin, Jianwu Wang, Jian Yu (alphabetical order). Personalized Active Service Spaces for End-User Service Composition. In Proceedings of the 2006 IEEE International Conference on Services Computing (SCC 2006) [PDF]

[15]. Yanbo Han, Hongcui Wang, Jianwu Wang, Shuying Yan, Cheng Zhang. An End-User-Oriented Approach to Exploratory Service Composition. Journal of Computer Research and Development, 43(11), 2006. (In Chinese)

[14]. He Huang, Zhongzhi Shi, Jianwu Wang and Rui Huang. DDL: Embracing Actions into Semantic Web. In Proceedings of IIP2006 (2006 IFIP International Conference on Intelligent Information Processing), 2006.

[13]. Wanghu Chen, Chen Liu, Houfu Li, Jianwu Wang. An Approach to Dynamically Forming Semantic Infrastructure for Virtual Organizations. Chinese Journal of Computers, 19(7), 2006. (In Chinese)

[12]. Jian Yu, Tan Phan Manh, Jun Han, Yan Jin, Yanbo Han, Jianwu Wang. Pattern Based Property Specification and Verification for Service Composition. In Proceedings of Seventh International Conference on Web Information Systems Engineering (WISE 2006).

[11]. Hailue Lin, Chen Liu, Jianwu Wang, Jun Fang, Houfu Li. A Business Domain Oriented Service Modeling Approach and its Supporting Framework, Information Technology Letter. 4(3), 2006, Pages:10-17. (In Chinese)

• 2005:

[10]. Jianwu Wang, Jian Yu, Yanbo Han. A Service Modeling Approach with Business-Level Reusability and Extensibility. In Proceedings of IEEE International Workshop on Service-Oriented System Engineering (SOSE 2005), October 20-21, 2005. Beijing.[PDF]

[9]. Jian Yu, Jianwu Wang, Yanbo Han et al. Developing End-User Programmable Service-Oriented Applications with VINCA. In Kurt Sandkuhl, Alexander Smirnov, and Herbert Weber (eds.), The Knowledge Gap in Enterprise Information Flow: Information Logistic concepts and technologies for improving information flow in networked organizations, Ljungby(Sweden), May 2005, ISBN 91-975604-2-1. [PDF]

[8]. Jian Yu, Jun Fang, Yanbo Han, Jianwu Wang, and Cheng Zhang. An Approach to Abstracting and Transforming Web Services for End-user-doable Construction of Service-Oriented Applications. In Proceedings of the Second International Conference on Grid Services Engineering and Management (GSEM'05). Lecture Notes in Informatics.

• 2004:

[7]. Jianwu Wang, Yanbo Han, Jing Wang and Gang Li. An Approach to Dynamically Reconfiguring Service-Oriented Applications from a Business Perspective, In Proceedings of Advanced Workshop on Content Computing (AWCC 2004) LNCS 3309, pages 357-368, 2004.[PDF]

[6]. Zhuofeng Zhao, Yanbo Han, Jianwu Wang, Kui Huang. A Reflective Approach to Keeping Business Characteristics in Business-End Service Composition. In Proceedings of Fifth International Conference on Web Information Systems Engineering (WISE 2004), pages 479-490. [PDF]

[5]. Donglai Li, Yanbo Han, Jianwu Wang, Jian Yu. Research on Service Availability and Its Related Exceptions within Service-Oriented Applications. Journal of Computer Research and Development, 2004, 41(12). (In Chinese)

[4]. Zhuofeng Zhao, Yanbo Han, Jian Yu, Jianwu Wang. A Service Virtualization Mechanism for Business User Programming. Journal of Computer Research and Development, 2004.41(12). (In Chinese)

• 2003:

[3]. Gang Li, Jianwu Wang, Jing Wang, Yanbo Han, Zhuofeng Zhao, Roland M. Wagner, Haitao Hu. MASON: A Model for Adapting Service-Oriented Grid Applications. In Proceedings of the Second International Workshop on Grid and Cooperative Computing (GCC 2003), LNCS 3032, pages 99-107, 2003.

[2]. Gang Li, Yanbo Han, Zhuofeng Zhao, Jianwu Wang, Roland M. Wagner. An Adaptable Service Connector Model. In Proceedings of the First International Workshop on Semantic Web and Databases (SWDB 2003), co-located with VLDB 2003, pages 79-90, 2003.

[1]. Yanbo Han, Zhuofeng Zhao, Gang Li, Dongshan Xing, Qingzhong Lu, Jianwu Wang, Jinhua Xiong, Hao Liu: CAFISE: An Approach to Enabling Adaptive Configuration of Service Grid Applications. Journal of Computer Science and Technology. 18(4), 2003. pages 484-494. [PDF]