 |
Dr. Kam
Sanmugalingam
e-mail: kam (at)
shan.me
|
 |
|
I am a mathematician
and computer scientist and have worked in the areas of theoretical
diffractive optics for a pre-startup, indoor ultrasonic reflections for sentient computing research, object-based
middleware over variable mobile networks for an SME, database design for BT and even VRML (a
very long time ago) for a UK charity organisation. I love all areas of maths (I took pure
and applied classes) but my work has always been applied (comp-sci, numerical
analysis, optimisation, stats). I'm interested in computing at all
levels too (from enterprise-class clusters down to low-power mobiles).
I graduated in
Mathematics and Computer Science (Management) from King's College, London.
I got an MSc in Data Comms, Networks and Distributed Systems from UCL, and then did my PhD
in ultrasound location estimation at the University of Cambridge in the Laboratory
for Communications Engineering (LCE)
of the Engineering Department (CUED), which is now the
Digital Technology Group
(DTG) of the
Computer Laboratory (CL).
Research
One of the main areas for improvement in location sensor systems (such
as Active Bat or GPS) is the less than expected accuracy in real-world
deployments. This is due to an incorrect mapping in the relationship
between receivers and transmitters, from incorrect (e.g. incomplete)
models of the sensors, environment or physical geometry.
The lab's QoSDReAM2/SPIRIT event-driven middleware defines spatial data
models, spatial predictates and spatial relations in a quadtree spatial
index to efficiently generate sensor-agnostic region overlap events.
My research developed a mathematical framework that received low-level
Active Bat ranges. It extended QoSDReAM2/SPIRIT, to reduce location
errors during extreme conditions in harsh environments, with:
- improved physical models (ultrasound propagation, physical
geometry, human motion)
- stochastic estimation (multipath mitigation, Kalman filtering)
- statistical prediction from spatio-temporal datasets (e.g.
predicting a user's track from their history during sensor dropouts)
- and multi-sensor data fusion algorithms (conflict resolution)
My 1st year project was on improving the realism of simulated location
data. These events could then be sent to the middleware, and look just
like a real location tag had generated them. To generate the simulated
location events, for generic vehicles/people, we merged event-driven
simulation, queuing models, velocity/vehicle models, cellular/hybrid
automata, et.c.
This work (paper)
was discussed with colleagues from other universities and with British
Airways' Terminal 5 engineers for their research into crowd control and
efficient Ground Service Equipment (anything that can't fly, e.g.
baggage trucks) deployment.
I was a member of the QoSDREAM group, and my professors were Andy
Hopper and George Coulouris. I was also a member of Girton College.
Publications
- K. Sanmugalingam, Ultrasound Location Estimation for Sentient Computing. PhD thesis, University of Cambridge Department of Engineering.
- Kam Sanmugalingam, George Coulouris, A Generic Location Event
Simulator. Fourth International Conference on Ubiquitous
Computing (UbiComp 2002), Series LNCS, Volume 2498, Pages 308-315,
Springer-Verlag, September 2002.
- ... Master's thesis, University of London.
- ... under construction, sorry ...