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Soon Chun

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Soon Ae Chun is a professor of Information Systems and Informatics Program, and a doctoral faculty member of Computer Science at the Graduate Center. She serves as the director of the Information Security Research and Education Lab (iSecure Lab). She received the Dolphin Award for Outstanding Scholarly Achievement. She serves as the President for the Digital Government Society. 

Her research area includes Data Science, Security and Privacy, Semantic Web, Social Media, Service and data sharing, focusing on applied areas in Digital Government and Public Health. She conducted research work on the cybersecurity ontology, the disaster and emergency management process and resource discovery, social media uses for public services, ontology-based public service workflow generation, public engagement and transparency of policy decision making, Geospatial data access control, crowd-based environmental planning and policy. She is an IEEE senior member, a member of ACM Computing Society, the Digital Government Society, and the Beta Gamma Sigma Honor Society.

Contact Information

Soon Chun, PhD


College of Staten Island
Email Soon Chun, PhD

Department: Marketing

  • School of Business
  • Information Systems and Informatics Program (Interdisciplinary degree program)
  • Computer Science, CUNY Graduate Center


Research Title

Big Data driven Megacity Insights Platform

Megacities provide many opportunities that stem from the density of the economic and social interactions between people, goods, and services, but also pose significant challenges for the city government and the city dwellers. The challenges and vulnerabilities range from the provision of a sustainable core infrastructure in transportation, health, education, public safety, and economic development to the innovative design of replicable and equitable social services to reduce socio-economic, cultural and political disparities and disharmony. The aim of this project is to build a Big Data driven Megacity Insights Platform (Mega-Insights) that can support researchers and policymakers to gain significant insights from emerging and frequent patterns, trends and predictions to proactively plan and respond to the important challenges of urban sustainability, through data pipelining and advanced analytics based on Artificial Intelligence and Machine Learning technologies. 

I did not use the HPC for these work but the projects are relevant.

Shengcheng Yuan, Soon Ae Chun, Bruno Spinelli, Yi Liu, Hui Zhang, Nabil R. Adam, Traffic Evacuation Simulation Based on Multi-level Driving Decision Model, Transportation Research Part C: Emerging Technologies, Volume 78, May 2017: pp 129-149

Xiang Ji, Soon Ae Chun, Paolo Cappellari and James Geller (2017) Linking and Using Social Media Data for Enhancing Public Health Analytics, Journal of Information Science, Volume 43, Issue 2, April 2017: pp. 221-245. 

Nhathai Phan, Soon Ae Chun, Manasi Bhole & James Geller, Enabling Real-Time Drug Abuse Detection in Tweet, Proceedings of ICDE, Workshop on Health Data Management and Mining (HDMM) , San Diego, April 30, 2017: 1510-1514. 

Xiang Ji, Soon Ae Chun and James Geller (2016) Predicting Comorbid Conditions and Trajectories using Social Health Records, IEEE Transactions on Nanobioscience Vol 15 Issue 4, June 2016:371-379.

Lorenzi, D., S. Chun, J. Vaidya, B. Shafiq, V. Atluri and N. Adam (2015) PEERS: Engaging Citizens to Crowdsource Emergency Response, International Journal of E-Planning Research, Vol4(3): 30-47. 

Xiang Ji, Soon Ae Chun, Zhi Wei, and James Geller (2015) Twitter Sentiment Classification for Measuring Public Health Concerns, Social Network Analysis and Mining, Vol 5 Issue 1, pp 5:13

Co-PI, I/UCRC: Center for Hybrid Multicore Productivity Research (CHMPR) - Rutgers Site, $299,961, NSF I/UCRC Program (PI Adam, Rutgers University) 8/1/2016-7/31/2021.

Co-PI: "Towards a Framework for Automatic Assessment and Awareness of Privacy Disclosure," PSC-CUNY Research Award #69339-00 47, PSC-CUNY Research Foundation $3443.48, 7/1/2016 - 6/30/2017.

Paolo Cappellari (CSI)

Huy Vo (CCNY)

Robert Haralick (Graduate Center)

Not yet but it has potentials to contribute on my research on:

- Data mining

- Deep learning

- Social Media text data analytics/visualization

- Data Science Education