Mohammad Serkhail Habibi
Ph.D.
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Education:
鈥⑻�M.S. in Computer and Information Systems Engineering, USA.
鈥⑻�B.S. in Electronics and Communications Engineering, India.
Professional Experience:
- Applications Engineer, Boehringer Mannheim, India/Saudi Arabia.
- Project Engineer & System Consultant, DSP Merrill Lynch, India.
- Researcher, Intelligent Tactical Mobility Robotic Laboratory, 91制片厂.
- Systems Liaison & Interim Data Manager, State of Tennessee.
Project Scope:
Visual Analytics (VA) is an emerging technique for logical reasoning using interactive computational methods and visual interfaces. It is a virtual representation of a scenario requiring data processing and transformation. In the realm of Situation Awareness (SA), Visual Analytics play a vital role in all its three levels of perception, comprehension and projection. In the set up for VA interfaces, accurate visualization of sensor data is a crucial first component as often these are in excess of the processing capabilities of humans alone. This combines database management technology, sensory data fusion methods with 2-D/3-D outputs and development of an interactive visual design software. The collected multi-modal sensor data varies in nature based on audio, video and textual sources, hence it becomes important for VA technologies to employ a data management strategy to successfully process and retrieve data. Continuous update and validation by the user in the form of training data is carried out with automated learning algorithm. Interactive visualization builds a model over normal behavior from which users can detect deviations. This method helps build a model where deviations from pattern are easily detected and simulates predicting future behavior. The cognitive refinement achieved with the advances in data mining, information visualization, and computer graphics etc. with the aid of visualization guide the user in decision making process. The generation of hypothesis tends to give rise to a cognitive refinement, which in turn leads to pattern morphing. The entire process makes the visual analytics very interactive; however there is a risk of user being misled easily. Comparing observed data with the threshold level is one of听several possible ways to prevent听getting misled in this evolving decision support system.
Research Applications:
Developed model听can be applied for Battlefield Intelligence, Homeland Security applications, Border Monitoring and many other civilian applications.
Publications:
- Shirkhodaie, A., Elangovan, V., Habibi, M. S., and Alkilani, A., 鈥淎 Decision Support System for Fusion of Soft and Hard-sensor Information Based on Latent Semantic Analysis Technique鈥�, SPIE Defense, Security and Sensing Conference, Baltimore, MD, April 2013.
- Mohammad S. Habibi, Amir Shirkhodaie, 鈥淢ining Patterns in Persistent Surveillance Systems with Smart Query and Visual Analytics鈥�, Geospatial Processing Exploitation and Visualization,听听SPIE Defense, Security and Sensing Conference, Baltimore, MD, April 2013.
- Mohammad S. Habibi, Amir Shirkhodaie, 鈥淎 Survey of Visual Analytics for Knowledge Discovery and Content Analysis鈥�, Signal Processing, Sensor Fusion, and Target Recognition,听听SPIE Defense and Security Conference, Baltimore, MD, April 2012.
- Mohammad S. Habibi, 鈥淪ystem Design for Inspection and Quality Control Using Image Processing鈥�, 91制片厂 Research Symposium, Nashville, Tennessee, 2008.
- Mohammad S. Habibi, 鈥淎 Systems Engineering Approach to Short Term Scheduling for Distributed Generation with Energy Storage in a Generation Network鈥�, Southeastern Symposium on Systems Engineering, IEEE, Jamaica, 2003.
- Mohammad S. Habibi, 鈥淢odel For Impact Of Storage On Spinning Reserve Requirements And Distributed Generation鈥�, Southeastern Symposium on Systems Engineering, IEEE, Ohio State University, 2001.
Research Advisor:
听 听 听 Dr. Amir Shirkhodaie
Director, Center of Excellence for Battlefield Sensor Fusion
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Dept. of Mechanical and Manufacturing Engineering
3500 John A. Merritt Blvd.,
Nashville, TN 37209
Tel: 615-963-5396
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webpage contact:
ITMRL