| Background |
Note: I have recently finished my postdoc at LBL and am now at Google, Inc.
From 2005 to 2007 I was a postdoctoral researcher in the Visualization
Group at Lawrence Berkeley National Laboratory, where I applied
statistical learning algorithms to the analysis of scientific
data. Projects included recognizing supernovae from photometric
and geometric futures using Support Vector Machines, classifying
time-varying spectra from observed and synthetic supernovae via
component analyses, and finding statistical dependencies between
hurricane occurrences and spatiotemporal variables in climate
I spent a year as postdoctoral researcher in the Imaging and Informatics Group
applying vision and learning methods to miscroscopy imagery used by
radiation biologists as a way to quantify the presence in cell nuclei
of proteins crucial to DNA repair.
I earned my Ph.D. in EECS from MIT in May 2002 in the
Computer Vision Group
at the Artificial Intelligence Laboratory, now
| Current Projects |
Recognition of Supernovae using Support Vector Machines |
Classification of Supernova Spectra via Non-negative Matrix Factorization
Modeling Protein Expression Features from Fluorescence Microscopy
using Independent Component Analysis
Projective Minimal Analysis of Camera Geometry
Monitoring from Multiple Views
Real-Time Face Verification
| Talks |
Recognition Using Support Vector Machines,
Neyman Seminar, Department of Statistics, UC Berkeley, September 20, 2006|
and Anomalies in Scientific Data,
Tapia Diversity in
Computing Conference, October 22, 2005
Statistical Analysis of
Subcellular Proteins in Microscopy Imagery,
Bay Area Scientific Computing Day,
March 5, 2005
Projective Geometry for Computer Vision,
LBL Scientific Computing Seminar,
May 12, 2004
| Publications |
Supernova Recognition using
Support Vector Machines., R. Romano, C. Aragon, and Chris
Ding. Proceedings of the 5th International Conference of Machine
Learning Applications. December 14-16, 2006. Best
Application Paper Award |
Projective Minimal Analysis of
Camera Geometry. Raquel A. Romano. Ph.D. Thesis.
May 2002. (ps.gz)
from Multiple Video Streams: Establishing a Common
Coordinate Frame. L. Lee, R. Romano, and G. Stein.
IEEE Transactions on Pattern Recognition and Machine
Intelligence, Special Section on Video Surveillance and
Monitoring. Vol. 22, No. 8, August 2000.
Using Adaptive Tracking to
Classify and Monitor Activities in a Site.
W.E.L. Grimson, L. Lee, R. Romano, and C. Stauffer.
Proceedings of Computer Vision and Pattern Recognition (CVPR),
1998, pp.22-31. ps.gz)
Face Verification for Real-time
Applications. R. Romano, D. Beymer, and T.
Poggio. Proceedings of Image Understanding Workshop.
Vol. 1, Palm Springs, CA, February 1996, pp. 747-756.
| Links |
LBL Imaging and
Artificial Intelligence Laboratory Vision Group
INRIA Robotvis Group (now Odyssee)
| Outreach |
Education 198: Strategies for Sucess at
Cal for Science, Engineering and Mathematics Transfer
Students, UC Berkeley, Spring 2005 |
LBL Latino and Native American Association