Siyuan Liu

Color portrait of Siyuan Liu

Assistant Professor

Department Supply Chain & Information Systems
Office Address 423 Business Building
Phone Number 814-865-5944
Email Address siyuan@psu.edu

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Siyuan Liu is with Smeal College of Business, Pennsylvania State University. He received his Ph.D. degree from Department of Computer Science and Engineering at Hong Kong University of Science and Technology, and another Ph.D. degree from University of Chinese Academy of Sciences.

Expertise

Big data for business intelligence, new technology for digital economy, data mining, behavior models.

Education

Ph D, University of Chinese Academy of Sciences, 2014

Ph D, Hong Kong University of Science and Technology, 2011

Courses Taught

BA 841 – BUS INTELLIGENCE (3)
Business intelligence encompasses the IT tools for exploring, analyzing, integrating, and reporting business data for fact-based, intelligent decision making. This course primarily investigates methods and tools for exploring and analyzing large amounts of business data, also called "Big Data". Learning methods emphasize active learning in the application of methods and tools to real data and the presentation of the results. Students will be exposed to a variety of methods for analyzing both structured and unstructured data and they will work with business data sets to understand the value that can be extracted from large data sets.They will also learn how to classify and associate data to discover business rules that can be used to support decision making. The course will also cover methods to analyze social media information and tools that can facilitate such analysis and discovery. Students will work with data from real social networks to gain an appreciation of how value can be obtained from such networks. Finally, they will learn about techniques for visualizing, presenting, and communicating information in a useful way, e.g. through dashboards and with other technologies on various platforms. Upon successful completion of this course, students will have:- acquired the tools and techniques of data cleaning and preparation, data mining, and data visualization- become competent in analyzing both structured and unstructured data- developed an understanding of, and an appreciation for, the complexities of mining unstructured data such as text data includingdocuments, web pages, emails, etc.- developed an understanding of social networks as well as mobile and location-based analytics

MIS 441 – Bus Intelligence (3)
Application of Information Technology based methods and tools to analyze business data and support decision making. MIS 441 Business Intelligence for Decision Making (3) Business intelligence encompasses the IT tools for exploring, analyzing, integrating, and reporting business data for fact-based, intelligent decision making. This course primarily investigates methods and tools for exploring and analyzing large amounts of business data also called "Big Data." Learning methods emphasize active learning in the application of methods and tools to real data and the presentation of the results. Students will be exposed to a variety of methods for analyzing both structured and unstructured data and they will work with business data sets to understand the value that can be extracted from large data sets. They will also learn how to classify and associate data to discover business rules that can be used to support decision making. The course will also cover methods to analyze social media information and about tools that can facilitate such analysis and discovery. Again they will get a chance to work with data from real social networks to gain an appreciation of how value can be obtained from such networks. Finally, they will learn about techniques for visualizing, presenting and communicating information in a useful way, e.g. through dashboards and with other technologies on various platforms.

MIS 301 – Business Analytics (3)
MIS 301 investigates use of databases, basic data mining tools, social networking software, and advanced level of spreadsheet management for analysis of large amounts of data. Learning methods emphasize active learning in the application of methods and tools to real data and the presentation of the results. Topics may include methods for analyzing not only structured data, but also unstructured data from the web, emails, blogs, social networks, click streams, etc. Finally, techniques for visualizing, presenting and communicating information in a useful way will be presented.

MIS 494H – Research Project (Variable)
Supervised student activities on research projects identified on an individual or small-group basis.

Selected Publications

Ho I., Liu S., Wang L., "Fun Shopping - A Randomized Field Experiment on Gamification." Information Systems Research, 2022
Xu X., Zhou F., Zhang K., Liu S., Trajcevski G., "CasFlow: Exploring Hierarchical Structures and Propagation Uncertainty for Cascade Prediction." IEEE Transactions on Knowledge and Data Engineering, 2022
Guo H., Zhang D., Liu S., Wang L., Ding, "Bitcoin Price Forecasting: A Perspective of Underlying Blockchain Transactions." Decision Support Systems, 2021
Huang K., Han Y., Chen K., Pan H., Zhao G., Yi W., Li X., Liu S., Wei P., Wang L., "A hierarchical 3D-motion learning framework for animal spontaneous behavior mapping." Nature Communications, 2021
Tang S., Liu S., Han X., Qiao Y., "Towards Robust Monitoring of Malicious Outbreak." INFORMS Journal on Computing, 2021
Liu S., Tang S., Zheng J., Ni L., "Unsupervised Learning for Human Mobility Behaviors." INFORMS Journal on Computing, 2021
Liu S., Li J., Zhang K., Tang S., "Responsible IS by Design: A Psychology-Informed Social Connection Recommender System for Mental Health." 2021 INFORMS Workshop on Data Science, Best Paper Award, 2021
Zhao B., Xu C., Liu S., Zhao J., Li L., "Dynamic Traffic Bottlenecks Identification Based on Congestion Diffusion Model by Influence Maximization in Metrocity Scales." Concurrency and Computation: Practice and Experience, 2021
Cheng P., Lian X., Chen L., Liu S., "Maximizing the Utility in Location-Based Mobile Advertising." IEEE Transactions on Knowledge and Data Engineering, 2020
Yue X., Shu X., Zhu X., Du X., Yu Z., Papadopoulos D., Liu S., "BitExTract: Interactive Visualization for Extracting Bitcoin Exchange Intelligence." IEEE transactions on visualization and computer graphics, 2019
Ghose A., Li B., Liu S., "Mobile Advertising Using Customer Trajectory Patterns." Management Science, 2019
Cheng P., Lian X., Chen L., Liu S., "Maximizing the Utility in Location-Based Mobile Advertising." 2019 IEEE 35th International Conference on Data Engineering (ICDE), 2019
Zhao B., Xu C., Liu S., Zhao J., Li L., "A Congestion Diffusion Model with Influence Maximization for Traffic Bottleneck Identification in Metrocity Scales." 2019 IEEE International Conference on Big Data, 2019
Liu S., Qu Q., Wang S., "Heterogeneous anomaly detection in social diffusion with discriminative feature discovery." Information Sciences, 2018
He B., Chen X., Zhang D., Liu S., Han D., Ni L., "PBE: Driver Behavior Assessment Beyond Trajectory Profiling." 2018 Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2018
He B., Zhang D., Liu S., Liu H., Han D., Ni L., "Profiling Driver Behavior for Personalized Insurance Pricing and Maximal Profit." 2018 IEEE International Conference on Big Data, 2018
Liu S., Zhang J., "Big Data, Big Marketing." (China Development Press), 2017
Le T. V., Oentaryo R., Liu S., Lau H. C., "Local Gaussian Processes for Efficient Fine-Grained Traffic Speed Prediction." IEEE Transactions on Big Data, vol. 3, no. 2, 2017, pp. 194–207
Zhao J., Qu Q., Zhang F., Xu C., Liu S., "Spatio-Temporal Analysis of Passenger Travel Patterns in Massive Smart Card Data." IEEE Transactions on Intelligent Transportation Systems, 2017
Liu S., Wang S., "Trajectory Community Discovery and Recommendation by Multi-Source Diffusion Modeling." IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 4, 2017, pp. 898–911
Le T. V., Liu S., Lau H. C., "Reinforcement learning framework for modeling spatial sequential decisions under uncertainty." Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016, pp. 1449–1450
Qu Q., Liu S., Zhu F., Jensen C. S., "Efficient Online Summarization of Large-Scale Dynamic Networks." IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 12, 2016, pp. 3231–3245
Liu S., Qu Q., "Dynamic collective routing using crowdsourcing data." Transportation Research Part B: Methodological, vol. 93, 2016, pp. 450–469
Zhao K., Tarkoma S., Liu S., Vo H., "Urban human mobility data mining: An overview." 2016 IEEE International Conference on Big Data (Big Data), 2016, pp. 1911–1920
Wu T., Zhang C. J., Chen L., Hui P., Liu S., "Object identification with Pay-As-You-Go crowdsourcing." 2016 IEEE International Conference on Big Data (Big Data), 2016, pp. 578–585
Hua Y., Wang S., Liu S., Cai A., Huang Q., "Cross-modal correlation learning by adaptive hierarchical semantic aggregation." IEEE Transactions on Multimedia, vol. 18, no. 6, 2016, pp. 1201–1216
Liu S., Wang S., Zhu F., "Structured Learning from Heterogeneous Behavior for Social Identity Linkage." IEEE Transactions on Knowledge and Data Engineering, 2015
Liu S., Wang S., Liu C., Krishnan R., "Understanding taxi drivers’ routing choices from spatial and social traces." Frontiers of Computer Science, 2015, pp. 1–10
Liu S., Qu Q., Chen L., Ni L. M., "SMC: A practical schema for privacy-preserved data sharing over distributed data streams." IEEE Transactions on Big Data, vol. 1, no. 2, 2015, pp. 68–81
Liu S., Qu Q., Wang S., "Rationality analytics from trajectories." ACM Transactions on Knowledge Discovery from Data (TKDD), vol. 10, no. 1, 2015, pp. 10
Liu S., Yue Y., Krishnan R., "Non-Myopic Adaptive Route Planning in Uncertain Congestion Environments." IEEE Transactions on Knowledge and Data Engineering, 2015
Ghose A., Li B., Liu S., "Trajectory-based Mobile Advertising." Proceedings of the International Conference on Information Systems (ICIS), 2015
Le T. V., Liu S., Lau H. C., Krishnan R., "Predicting bundles of spatial locations from learning revealed preference data." Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, 2015, pp. 1121–1129
Xie W., Zhu F., Liu S., Wang K., "Modelling cascades over time in microblogs." 2015 IEEE International Conference on Big Data (Big Data), 2015, pp. 677–686
Zhang Y., Li B., Krishnan R., Liu S., "Learning from the Offline Trace: A Case Study of the Taxi Industry." Thirty Sixth International Conference on Information Systems, 2015
Pu J., Liu S., Xu P., Qu H., Ni L. M., "MViewer: mobile phone spatiotemporal data viewer." Frontiers of Computer Science, vol. 8, no. 2, 2014, pp. 298–315
Zheng J., Liu S., Ni L. M., "Effective mobile context pattern discovery via adapted hierarchical dirichlet processes." 2014 IEEE 15th International Conference on Mobile Data Management (MDM), vol. 1, 2014, pp. 146–155
Liu S., Kang L., Chen L., Ni L. M., "How to Conduct Distributed IncompletePattern Matching." IEEE Transactions on Parallel and Distributed Systems, vol. 25, no. 4, 2014, pp. 982–992
Liu S., Ni L. M., Krishnan R., "Fraud detection from taxis’ driving behaviors." IEEE Transactions on Vehicular Technology, vol. 63, no. 1, 2014, pp. 464–472
Liu S., Chen L., Ni L. M., "Anomaly detection from incomplete data." ACM Transactions on Knowledge Discovery from Data (TKDD), vol. 9, no. 2, 2014, pp. 11
Lu L., Cao N., Liu S., Ni L., Yuan X., Qu H., "Visual analysis of uncertainty in trajectories." Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2014, pp. 509–520
Zheng J., Liu S., Ni L. M., "User characterization from geographic topic analysis in online social media." 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2014, pp. 464–471
Hua Y. T., Wang S., Liu S., Huang Q., Cai A., "TINA: Cross-modal Correlation Learning by Adaptive Hierarchical Semantic Aggregation." 2014 IEEE International Conference on Data Mining (ICDM), 2014
Zheng J., Liu S., Ni L. M., "Robust Bayesian Inverse Reinforcement Learning with Sparse Behavior Noise.." AAAI'14: Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014, pp. 2198–2205
Liu S., Wang S., Krishnan R., "Persistent community detection in dynamic social networks." Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2014, pp. 78–89
Qu Q., Liu S., Jensen C. S., Zhu F., Faloutsos C., "Interestingness-driven diffusion process summarization in dynamic networks." Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2014, pp. 597–613
Qu Q., Liu S., Yang B., Jensen C. S., "Integrating non-spatial preferences into spatial location queries." Proceedings of the 26th International Conference on Scientific and Statistical Database Management, 2014, pp. 8
Liu S., Wang S., Zhu F., Zhang J., Krishnan R., "Hydra: Large-scale social identity linkage via heterogeneous behavior modeling." Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, 2014, pp. 51–62
Qu Q., Liu S., Yang B., Jensen C. S., "Efficient top-k spatial locality search for co-located spatial web objects." 2014 IEEE 15th International Conference on Mobile Data Management (MDM), vol. 1, 2014, pp. 269–278
Chu L., Wang S., Liu S., Huang Q., Pei J., "ALID: Scalable Dominant Cluster Detection." VLDB 2015, 2014
Guo X., Chan E. C., Liu C., Wu K., Liu S., Ni L. M., "Shopprofiler: Profiling shops with crowdsourcing data." 2014 Proceedings IEEE INFOCOM, 2014, pp. 1240–1248
Liu S., Wang S., Jayarajah K., Misra A., Krishnan R., "TODMIS: Mining communities from trajectories." Proceedings of the 22nd ACM International Conference on Information & Knowledge Management (CIKM), 2013, pp. 2109–2118
Liu S., Pu J., Luo Q., Qu H., Ni L. M., Krishnan R., "Vait: A visual analytics system for metropolitan transportation." IEEE Transactions on Intelligent Transportation Systems, vol. 14, no. 4, 2013, pp. 1586–1596
Liu S., Liu Y., Ni L., Li M., Fan J., "Detecting crowdedness spot in city transportation." IEEE Transactions on Vehicular Technology, vol. 62, no. 4, 2013, pp. 1527–1539
Liu S., Araujo M., Brunskill E., Rossetti R., Barros J., Krishnan R., "Understanding sequential decisions via inverse reinforcement learning." 2013 IEEE 14th International Conference on Mobile Data Management (MDM), vol. 1, 2013, pp. 177–186
Pu J., Liu S., Ding Y., Qu H., Ni L., "T-watcher: A new visual analytic system for effective traffic surveillance." 2013 IEEE 14th International Conference on Mobile Data Management (MDM), vol. 1, 2013, pp. 127–136
Liu S., Krishnan R., Brunskill E., Ni L. M., "Modeling Social Information Learning among Taxi Drivers." Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2013, pp. 73–84
Ding Y., Liu S., Pu J., Ni L. M., "Hunts: A trajectory recommendation system for effective and efficient hunting of taxi passengers." 2013 IEEE 14th International Conference on Mobile Data Management (MDM), vol. 1, 2013, pp. 107–116
Liu S., Li L., Krishnan R., "Hibernating Process: Modelling Mobile Calls at Multiple Scales." 2013 IEEE 13th International Conference on Data Mining (ICDM), 2013, pp. 1139–1144
Zheng J., Liu S., Ni L., "Effective routine behavior pattern discovery from sparse mobile phone data via collaborative filtering." Proceedings of the 9th Annual International Conference on International Computing Education Research, 2013
Liu S., Yue Y., Krishnan R., "Adaptive collective routing using gaussian process dynamic congestion models." Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, 2013, pp. 704–712
Liu S., Liu C., Luo Q., Ni L. M., Krishnan R., "Calibrating large scale vehicle trajectory data." 2012 IEEE 13th International Conference on Mobile Data Management (MDM), 2012, pp. 222–231
Liu S., Kang L., Chen L., Ni L., "Distributed Incomplete Pattern Matching via a Novel Weighted Bloom Filter." 2012 IEEE 32nd International Conference on Distributed Computing Systems (ICDCS), 2012, pp. 122–131
Liu C., Liu S., Hamdi M., "GeRA: Generic rate adaptation for vehicular networks." 2012 IEEE International Conference on Communications (ICC), 2012, pp. 5311–5315
Pu J., Liu S., Qu H., Ni L. M., "Visual Fingerprinting: A New Visual Mining Approach for Large-Scale Spatio-temporal Evolving Data." Event8th International Conference on Advanced Data Mining and Applications (ADMA 2012), 2012, pp. 502–515
Gao Y., Xu P., Lu L., Liu H., Liu S., Qu H., "Visualization of taxi drivers’ income and mobility intelligence." Advances in Visual Computing, 2012, pp. 275–284
Liu S., Liu C., Luo Q., Ni L. M., Qu H., "A visual analytics system for metropolitan transportation." Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2011, pp. 477–480
Liu S., Chen L., Ni L. M., Fan J., "Cim: categorical influence maximization." Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication, 2011, pp. 124
Pu J., Xu P., Qu H., Cui W., Liu S., Ni L., "Visual analysis of people’s mobility pattern from mobile phone data." Proceedings of the 2011 Visual Information Communication-International Symposium, 2011, pp. 13
Zhang D., Yang Y., Cheng D., Liu S., Ni L. M., "COCKTAIL: An RF-based hybrid approach for indoor localization." 2010 IEEE International Conference on Communications (ICC), 2010, pp. 1–5
Liu S., Liu Y., Ni L. M., Fan J., Li M., "Towards mobility-based clustering." Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010, pp. 919–928
Liu S., Wen G., Fan J., "A 3d geosciences modeling system for large-scale water-diversion projects." Computing in science & engineering, vol. 12, no. 1, 2010, pp. 28–35

Research Impact and Media Mentions

"New type of mobile tracking link shoppers' physical movements, buying choices", Science Daily, Internet, www.sciencedaily.com/releases/2019/03/190325080448.htm
"Anticipating Customers’ Next Steps", Insights from MSI, Journal or Magazine