I finished my PhD in 1999, under Neil Gershenfeld.
The title of my dissertation is Electric Field
Imaging, "seeing" with electric fields.
Electric Field Imaging
is a new channel for machine perception that has been overlooked,
perhaps because humans do not sense electric fields.
I developed signal processing techniques, hardware, and inference
algorithms to let machines
acquire useful geometrical information from electric field measurements.
The School of Fish, developed for Electric Field Imaging, is a
network of intelligent electrodes, each with its own analog hardware
and on-board computing, on a shared communication
channel. It is an unusual form of Sensor Network, because
the electrodes are not actually capable of sensing individually.
Sensing only occurs
via pairwise interactions between electrodes, which makes
sensing a property of the network itself, not of individual units.
Elesys (formerly NEC Automative Electronics) has released a product
based directly on work I did in the course of my thesis.
The product is a car seat with
embedded electric field sensors
to determine the size and body configuration of the occupant in order to
make more intelligent firing decisions.
The Occupant Position
Detection System
now ships in all Honda cars with side airbags, and
an even more sophisticated Electric Field Imaging system from Elesys will be in GM vehicles
beginning
in Model Year 2004. Here is a
televised
demonstration of the Occupant Position Detection System.
Motorola has also launched an Electric Field Imaging IC,
the MC33794 Electric Field Imaging Device.
The fact that Electric Field Imaging has so successfully addressed the
important problem of automotive passenger sensing
is, in my view, proof that alternative sensing mechanisms can enable
better machine perceptual systems.
While still working on Electric Field Imaging, I realized that the
weak signal detection
techniques I was using could be applied in
a very different setting,
digital watermarking
or data hiding. My paper Modulation and
Information Hiding in Images was one of the first to
propose a quantitative model of digital watermarking, and to frame
digital watermarking in terms of communications concepts such
as signal, noise, bandwidth and jamming margin. Here is a link to
citations.
After finishing my PhD, I became
Director of Escher
Labs, which developed
sensing,
signal processing, and security technologies
for pervasive information processing, with an emphasis on
adding intelligence to paper documents.
We developed a technology called FiberFingerprint that takes the
next step beyond digital watermarking, enabling copy protection for
physical media. Here is link to The
Document That Can't be Forged, a New York Times article about FiberFingerprint (here is
a local copy in case you have trouble logging in).
Every square
centimeter of paper has a unique pattern of hills and valleys.
With the proper sensing and signal processing, we
can make use of those characteristics for identification and
authentication. FiberFingerprint also makes use of the
weak signal detection principles used in
Electric Field Imaging and data hiding.
Next I joined
Tiax
(formerly Arthur D. Little's Technology and
Innovation Practice).
I am now a principal investigator at Intel Research Seattle.