stevenberger.com
WHAT I AM is an advocate for the warfighter. To wage or not wage war is not my decision. Conflict between people is inevitable.
That said, Soldiers are performing clearing and containment operations and conducting
street-to-street fighting in Afghanistan and Iraq. Over the last decade, the military has connected nearly all its command posts and all
its vehicles into a kind of internet for battle. The Blue Force Tracker system has allowed them to, at the very least, see each battlespace
component's location and better coordinate attacks. Individual Soldiers, however, still remain largely off the grid. This is problematic
because counter-insurgency fights are almost wholly dependent on small groups of Soldiers — who need technological advancements to
keep them informed and aware.
WHAT I BELIEVE is identification of acoustic signals in noisy environments remains one of the most difficult of signal processing problems, and is a major obstacle to the high degrees of accuracy and speed needed to identify suspicious sounds in high-security, high-safety environments. It has been argued that the brain is an existence proof of a near-optimal "model-based" system for pattern recognition: through evolution, the brain has found the optimal feature models to guide the search over an almost infinite input space such that efficient pattern recognition can be achieved, even in the presence of noise. Information in the brain is coded in terms of variation in the sequence of all-or-none spike events, or temporal patterns, transmitted between nerve cells. Identifying the nonlinear input/output properties of neurons involved in forming memories for new patterns, and developing mathematical models of those nonlinear properties, can provide a revolutionary pathway to neural-based classification. More information on this research can be found at Theodore W. Berger Laboratories at USC, for which Safety Dynamics serves as commercialization arm.
WHAT I BELIEVE is identification of acoustic signals in noisy environments remains one of the most difficult of signal processing problems, and is a major obstacle to the high degrees of accuracy and speed needed to identify suspicious sounds in high-security, high-safety environments. It has been argued that the brain is an existence proof of a near-optimal "model-based" system for pattern recognition: through evolution, the brain has found the optimal feature models to guide the search over an almost infinite input space such that efficient pattern recognition can be achieved, even in the presence of noise. Information in the brain is coded in terms of variation in the sequence of all-or-none spike events, or temporal patterns, transmitted between nerve cells. Identifying the nonlinear input/output properties of neurons involved in forming memories for new patterns, and developing mathematical models of those nonlinear properties, can provide a revolutionary pathway to neural-based classification. More information on this research can be found at Theodore W. Berger Laboratories at USC, for which Safety Dynamics serves as commercialization arm.
WHAT I DO is partially-own and work at Safety Dynamics, Inc. for which I
manage Department of Defense-funded research for the development of smart sensors that can provide warfighters with information about the
battlespace that will create situational awareness — the sensing, understanding, and effectively responding to events
as they unfold in real-time, particularly in the context of safety in battle or en route to battle. Effective situational awareness
requires unambiguous identification of threats, and accurate localization of the source of those threats, so that optimal decisions can be
made with respect to evasive actions or aggressive engagement of the enemy — decisions that have life or death consequences.
WHAT I HOPE is to continue to foster the collaboration between the pure research performed at the Berger Labs of USC and the implementation of prototypes that are biologically-based by Safety Dynamics; which come together to complete a product development life cycle that can serve both military and homeland security markets. Above and beyond serving contracts with the Army Research Office; the Office of Naval Research; and the Department of Defense; there is a greater vision for the development of a library of sounds allowing customers to choose tailor-made acoustic recognition sound signatures with localization; and intelligent video analysis solutions. The idea is to make the sensors smarter; make the surveillance obvious or obfuscated; and make the warfighter safer, allowing Soldiers to come home to their families alive and well.
CONTACT:
sberger@safetydynamics.net
READING:
White Paper on Temporal Pattern Recognition [S. Berger, 2007]
WHAT I HOPE is to continue to foster the collaboration between the pure research performed at the Berger Labs of USC and the implementation of prototypes that are biologically-based by Safety Dynamics; which come together to complete a product development life cycle that can serve both military and homeland security markets. Above and beyond serving contracts with the Army Research Office; the Office of Naval Research; and the Department of Defense; there is a greater vision for the development of a library of sounds allowing customers to choose tailor-made acoustic recognition sound signatures with localization; and intelligent video analysis solutions. The idea is to make the sensors smarter; make the surveillance obvious or obfuscated; and make the warfighter safer, allowing Soldiers to come home to their families alive and well.
CONTACT:
sberger@safetydynamics.net
READING:
White Paper on Temporal Pattern Recognition [S. Berger, 2007]