A Framework for Graphical Visualization of Criminal Networks using Predictive Modelling and Analytics
Applications are invited for the post of Graduate research student for Flagship Research Grant Scheme “Data Analytics, Modelling and Visualisation” under Taylor’s University’s sponsored research project.
Project Duration: 3 Years
Project Code: TUFR/2017/004/06
Project Title: A Framework for Graphical Visualization of Criminal Networks using Predictive Modeling and Analytics.
Brief of Project:
Visualization has always been a potential aid while decision making in every discipline. It is a super structure of some data sets based on some sound analytical techniques. Exploring the bulk of data for digging out relevant information is really a challenging job since novel approaches are being introduced in the smart applications. Technology always brings challenges with it, same is the case with Information visualization. Visual analysis of huge crime data is a major challenge faced by law enforcing agencies. It lets the user develops hypothesis in his research area without having to get into cumbersome process of manipulating data. Much research is being carried on in this field. This research proposes a framework which focuses over distinct features of criminal network visualization. Optimization of some existing visualization techniques by way of merging or grouping their specific features is proposed. It will be done with a motive of incorporating drag and drop facilities to the experts in the field of criminal network analysis and visualization. We will also explore the research areas related to crime directionality to provide cognitive support to investigative analysts in effective decision making. A case study, based on some available data sets, with the purpose of validating the framework, is also proposed. An empirical study is also proposed to gather real-life criminal data. Finally, validation and dissemination of our results is proposed.
PhD Student – 1
Master’s by research student – 1
Specific Qualifications/ Requirements:
We are interested in a variety of hot topics in the area of graphical visualization, such as graphical algorithms, social and mobile networks and predictive analytics. In our group we try to apply and unite the approaches and techniques of algorithmic theory and systems implementation. Some members of our group focus on algorithms and theory, some on graphical systems design and building. Knowledge of R/Python would be highly advantageous as well of visualization tools.
Stipend and Benefits:
Students are encouraged to apply for PhD scholarship (applicable for PhD students with 100% tuition fee waiver and stipend) or Research scholarship (applicable for both Master’s and PhD students with 75% tuition fee waiver and stipend). Refer to ‘Postgraduate Funding’ for eligibility, application and selection details for the scholarships. Successful candidates who do not qualify for the above-mentioned scholarships will be funded through a Graduate Student Assistant Scheme with a monthly stipend of RM 1900-2500 (depending on the project budget). Students will be enrolled in PhD (Computer Science) and MSc (Computer Science) under the School of Computing and IT.
We are looking for a new member with a strong algorithmic background, and a Master’s degree in Computer Science or Mathematics or a related field. A candidate should be attracted by and proficient in areas such as approximation algorithms, complexity theory, distributed algorithms, graph theory, online computation, computational geometry, probabilistic algorithms, learning theory, combinatorics or optimization. The new group member can choose and shape the project according to his or her interests and talents within the first months of employment. Successful candidates are expected to work towards a doctoral degree, and participate in the publication and teaching activities of the group.
Master’s by Research Candidate
We are looking for a new member who would be interested to work on graph analytics including the application of machine learning to social networking and predictive data mining. The new group member can choose and shape the project according to his or her interests and talents within the first months of employment. Successful candidates are expected to work towards a master’s degree, and participate in the publication and teaching activities of the group.
Interested candidates can directly contact Dr. Azween Abdullah with their CV and research proposal via e-mail (email@example.com), School of Computing and IT, Faculty of Faculty of Built Environment, Engineering, Technology & Design, Taylor’s University.