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Developing data-specific analytical tools through blending machine learning algorithms and statistical modelling techniques is my main research interest. I have been involved in various research and industrial projects to extract descriptive and predictive insight from rainfall, electric discharge, telecom network, social network, call details record (CDR) and Passenger Name Record (PNR) data. In the most recent project with Ericsson Ireland, I developed a streaming technique based on statistical data reduction technique, the algorithm was implemented in Storm paradigm. I also lead a project on building real-time pattern model prediction technique based on large scale machine learning paradigm. I have developed my skills on the `Big Data' techniques to process the massive data streams.

Most Recent Publications:

• F. Zaman, S. Robitzsch, Z. Wu, J. Keeney, S. van der Meer, G. Muntean: A heuristic correlation algorithm for data reduction through noise detection in stream-based communication management systems, NOMS 2014 - Data Centric Cloud and Network Management.
• F. Zaman, G. Hogan, S. van der Meer, J. Keeney, S. Robitzsch, G. Muntean: A Recommender System Architecture for Predictive Telecom Network Management, accepted in IEEE Communications Magazine, 2015.
• F.Zaman, S. Robitzsch, Z. Qu, J. Keeney, S. van der Meer, G. Muntean: i-MagNet : A Real-time Intelligent Framework for Finding Specific Needles From Needle Stacks, accepted in IFIP/IEEE International Symposium on Integrated Network Management, 2015.
• S. Robitzsch, F.Zaman, Z. Qu, J. Keeney, S. van der Meer, G. Muntean: E-Stream: Towards Pattern Centric Network Incident Discovery and Corrective Action Recommendation in Telecommunication Networks, accepted in IFIP/IEEE International Symposium on Integrated Network Management, 2015

Key Skill Set:

• 5 years of experience in
  • Leading teams and supervise students in solving analytical problems
  • Reporting analytical insights of complex datasets
  • Developing data-specific statistical analytical tools and predictive models
  • Interactive analytical presentation
•  2 years of experience in
  • Leading teams in influencing business models through building data-analytics systems
  • Generate analytical reports for industrial partners

Research Expertise:

1. Develop ‘big data’ analytics to extract meaningful insight from large-scale data
2. Statistical data modelling
3. Parallel and scalable machine learning and data mining algorithm development and deployment
4. Predictive model development and refinement

Technical Expertise:

• Statistical programming and visualization with R
• Clinical trial analysis with SAS
• Scientific programming with MATLAB
• Understanding of Hadoop-MapReduce (algorithm design), Storm, Spark (basic)
• Scripting with Python (basic)
• Database exploration with SQL (basic)