Amjad Alkilani

Ph.D. Candidate & Research Assistant

Tennessee State University
Department of Mechanical and Manufacturing Engineering
Center of Excellence for Battlefield Sensor Fusion
Email: aalkilan@my.tnstate.edu
Tel: 615-963-5081

 Amjad

Education:

•  Master’s in Software Engineering, California State University, USA (August 2008)
•  Bachelor in Computer Science, Mutah University, Jordan (August 2003)

Professional Experience:

  • Research Assistant, Tennessee State University, Nashville, Tennessee (Jan 2011 – Present)
  • Project Manager, CBM Integrated Software Inc., Corona, CA (Dec 2008 – Jan 2011)
  • Software Engineer, Los Angeles County, Norwalk, CA (Jan 2007 – Dec 2008)
  • System Analyst, A&Z Software, Inc. , Irvine, CA (Sep 2005 – Jan 2007)
  • Software Programmer, CMS Software Solutions, UAE, Dubai ( Sep 2003 – June 2005)

Project Scope:   

Acoustic surveillance and human behavior analysis are some of the ongoing research topics in signal processing. Automatic recognition of human activities is an ambitious yet challenging process in achievement of a Persistent Surveillance System (PSS) for Department of Defense (DoD) and Department of Homeland Security (DHS). A typical PSS encompasses a number of human activities and the recognition of these activities is a challenging problem. The complexity of the problem is involved with low-level signal and image processing, data alignment from different sources (e.g., audio and video), fusion of Soft Data (SD) (e.g., HUMINT) and Hard Data (HD) (physical sensors), and annotating sensory information in the form of semantic messages understandable by human analysts. SD is based on human observations and it represents the ambiguity in human thinking with real life uncertainty. HD is the information computed from physical sensors (radar, video, acoustic) and it usually provides straightforward solution to analyze.To maximize reliability and effectiveness of a PSS, robust soft and hard data (audio and video) fusion techniques are in high demand to identify cohesive patterns of activities representing potential threats. Identification of such activities (e.g., Human-Vehicle Interactions (HVI), Human-Object Interactions (HOI), and Human-Human Interactions (HHI)) based on acoustics can significantly improve situational awareness in PSS.

Research Applications:                                                                                                                   

Develop robust techniques for automated human activities discovery, tracking, and recognition for Homeland Security and civilian applications.

Publications:

  • Alkilani, A., Shirkhodaie, A., "A survey on acoustic signature recognition and classification techniques for persistent surveillance systems," SPIE Defense and Security Conference, April 2012.
  • Alkilani, A., Shirkhodaie, A., "Acoustic Recognition of Human-Object Interactions in Persistent Surveillance Systems," SPIE Defense and Security Conference, April 2013.
  • Amir Shirkhodaie, Vinayak Elangovan, Mohammad S. Habibi, Amjad Alkilani “ A decision support A decision support system for fusion of soft- and hard-sensor information based on latent semantic analysis technique” SPIE Defense and Security Conference, April 2013.
  • Elangovan, V, Alkilani, A., Shirkhodaie, A., " A Multi-Modality Attributes Representation Scheme for Group Activity Characterization and Data Fusion," IEEE Conference, August 2013.


Research Advisor:
Dr. Amir Shirkhodaie
Director, Center of Excellence for Battlefield Sensor Fusion
Tennessee State University
Dept. of Mechanical and Manufacturing Engineering
3500 John A. Merritt Blvd., Nashville, TN 37209
Tel: 615-963-5396





webpage contact:
ITMRL