| Ph.D Student Department of Information Systems University of Maryland, Baltimore County Baltimore, MD, U.S.A. Email: xinwang11_at_umbc.edu See me at: Google Scholar Citation Page, LinkedIn |
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Short Biography
Xin (Starly) Wang is a fourth-year Ph.D. student at the Department of Information Systems, University of Maryland, Baltimore County (UMBC). Xin started her Ph.D. study in Fall 2018 in Data Science, worked as a Research Assistant in the Distributed Systems and Security Lab until Fall 2020, and worked in the Big Data Analytics Lab as a Research Assistant. Her research interests include distributed computing (systems), blockchains, big data analytics, federated learning, and cloud reproducibility. She passed the Comprehensive Exam in Spring 2020, and became a Ph.D. candidate in Winter 2020 with the proposal title “Secure and Efficient Federated Learning”.
Research Interests
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- Distributed Computing
- Blockchains
- Big Data Analytics
- Cloud Reproducibility
- Federated Learning
Education
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- 2018 ~ Present: Ph.D. in Information Systems, University of Maryland, Baltimore County, U.S.A.
- 2013 ~ 2017: B.S. in Computer and Information Sciences, Anhui University of Finance and Economics, China.
Employment
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- 2021.8 ~ Present Research Assistant at Center for Real-time Distributed Sensing and Autonomy, University of Maryland, Baltimore County, Baltimore, MD, U.S.A.
- 2020.8 ~ Present Graduate Research Assistant at Big Data Analytics Lab, University of Maryland, Baltimore County, Baltimore, MD, U.S.A.
- 2019.8 ~ Present Treasurer at Chinese Student and Scholar Association (CSSA), University of Maryland, Baltimore County, Baltimore, MD, U.S.A.
- 2019.1 ~ 2021.1 Research Assistant and Program Developer at Softhread Inc., Baltimore, MD, U.S.A.
- 2018.8 ~ 2020.8 Graduate Research Assistant at Distributed Systems and Security Lab, University of Maryland, Baltimore County, Baltimore, MD, U.S.A.
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Awards
- Student Travel Award, 2021 IEEE International Conference on Big Data.
Services
- Program Committee, 2022 Artificial Intelligence To Security (AITS2022).