Shamal Dohuki

Ph.D. Candidate @ Kent State University

My name is Shamal AL-Dohuki. I am from Kurdistan Region of Iraq. I am a Ph.D. candidate in the Department of Computer Science at Kent State University, Ohio, USA. I joined KSU-CS in 2013-2014 Academic Year. I have been working on image processing for 5 years. My current research interest includes implementing visual analytics of big urban data, urban data management and visualization, visual query of trajectory data, and semantic data query and analytics.

Work Experience:



Awards:



Contact:

    Shamal Dohuki
    Computer Science Department
    Kent State University
    Math & Comp. Sci. Building
    Office: Room 140
    Email: saldohuk(at)kent.edu


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2013-2019 (expected)

Ph.D. in Computer Science
Kent State University (U.S.A)
Advisor: Dr. Ye Zhao

2006-2008

MSc in Computer Science
University of Duhok (KRG - Iraq)
Advisor: Dr. Ahmed AK. Tahir
M.Sc Thesis: Improving Spatial Resolution Of Satellite Images Through Image Fusion Techniques.

2001-2005

BSc in Computer Science
University of Duhok (KRG - Iraq)
Advisor: Majid M. Nori
B.Sc Thesis: Minimal Perfect Hash Function.



SemanticTraj: A New Approach to Interacting with Massive Taxi Trajectories, Shamal AL-Dohuki, Farah Kamw, Ye Zhao, Chao Ma, Yingyu Wu, Jing Yang, Xinyue Ye, Fei Wang, Xin Li, and Wei Chen, IEEE Transactions on Visualization and Computer Graphics (VAST'16), To appear, Oct, 2016.
Paper    Web    Video


TrajAnalytics: A Web-Based Visual Analytics Software of Urban Trajectory Data, Ye Zhao, Shamal AL-Dohuki, Thomas Eynon, Farah Kamw, David Sheets, Chao Ma, Yueqi Hu, Xinyue Ye, Jing Yang, IEEE Workshop on Visualization in Practice: Open Source Visualization and Visual Analytics Software, IEEE Visualization Conference 2016.
Web   PDF    Poster    Video


Image Fusion for Resolution Improvement of Multispectral Satellite Images, Ahmed AK. Tahir, Shamal AL-Dohuki, The XVII International Conference - Multidisciplinary, vol. 31/2017, ISSN 2067-7138, held in 2-3 June, 2017, Sebes, Romania.
Web


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Advanced technologies in sensing and computing have created a variety of urban datasets of cities and their citizens. Understanding and analyzing the large-scale, complex data reflecting city dynamics is of great importance to enhance both human lives and urban environments. Exploratory visualization is a powerful tool to understand the data and to reveal knowledge intuitively, for both real-time monitoring and historical data analytics. Shamal AL-Dohuki, a PhD candidate in the Department of Computer Science at Kent State University, is working with Dr. Ye Zhao with research interests in implementing visual analytics of big urban data.
Web   YouTube Channel   Facebook Group






NeighborVis is a visual analytics system that allows users to study social media data in a community neighborhood. It is developed to answer the simple questions about an urban community: what is happening at this location, is it good or bad, and can outcomes be improved? It may be a police department considering a blighted street, a planning department considering urban renewal and the "greening" of spaces, a community group wanting to add neighborhood gardens, or a hospital mining its child injury data.
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