Projects per year
Personal profile
Research interests
Research Expertise:
Data Mining | Artificial Intelligence | Machine Learning | Pattern Recognition
My current research interests are: transfer learning, one-shot learning, computational creativity, spatiotemporal data mining, privacy issues in data mining, machine learning on network/graph data. My projects and investigations are both research-driven and application-driven. The application-driven investigations utilize real-world data such as mobile data from smartphones, crowdsourced sensor data collected using smartphone, factory sensor data, text data (from internet), audio data, image data, and satellite data.
Member of:
Association for Computing Machinery
Institute of Electrical and Electronics Engineers
Honors and Awards:
NASA Postdoctoral Fellowship, 2007-2009.
Recent Academic Projects:
2017 SURP projects: “Histogram-based Conformal Set Predictor with Application to Trajectory-based Object Similarity Search” and “A Knowledge Transfer Framework for Computational Creativity with Application to Music Generation”
Education/Academic qualification
Computer Science, doctorate, George Mason University
Computer Science, Master, George Mason University
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Projects
- 1 Active
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ATD: New Approaches for Anomaly Detection in Spatiotemporal Data
National Science Foundation (NSF)
9/1/18 → 1/31/22
Project: Other project
Research output
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Distributed machine learning for energy trading in electric distribution system of the future
Wang, N., Li, J., Ho, S. S. & Qiu, C., Jan 1 2021, In: Electricity Journal. 34, 1, 106883.Research output: Contribution to journal › Article › peer-review
4 Scopus citations -
Learning incentivization strategy for resource rebalancing in shared services with a budget constraint
Ho, S. S., Schofield, M. & Wang, N., Apr 2021, In: Journal of Applied and Numerical Optimization. 3, 1, p. 105-114 10 p.Research output: Contribution to journal › Article › peer-review
Open Access2 Scopus citations -
An Error-Correcting Output Code Framework for Lifelong Learning without a Teacher
Ho, S. S., Marchiano, M., Zockoll, S. & Nguyen, H., Nov 2020, Proceedings - IEEE 32nd International Conference on Tools with Artificial Intelligence, ICTAI 2020. Alamaniotis, M. & Pan, S. (eds.). IEEE Computer Society, p. 249-254 6 p. 9288216. (Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI; vol. 2020-November).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Assessing Accident Risk using Ordinal Regression and Multinomial Logistic Regression Data Generation
Alicioglu, G., Sun, B. & Ho, S. S., Jul 2020, 2020 International Joint Conference on Neural Networks, IJCNN 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 9207105. (Proceedings of the International Joint Conference on Neural Networks).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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A fractional differential equation model for bike share systems
Graef, J. R., Ho, S. S., Kong, L. & Wang, M., 2019, In: Journal of Nonlinear Functional Analysis. 2019, 23.Research output: Contribution to journal › Article › peer-review
5 Scopus citations