Investigations in nano and micro structures from data coming from national laboratories instruments, and simulations, including collaboration with industry and academia to discover motifs that enable image understanding and decision making At the Lawrence Berkeley National Laboratory, she is the Deputy Group Leader of the Analytics/Visualization, Staff Scientist at the Computational Research Division of LBNL. She is also one of the 2015 DOE Early Career Awarded scientists, a co-PI in Image Analysis/Machine Vision for the Center for Advanced Mathematics for Energy Related Applications (CAMERA).
At the University of California, Berkeley, she is one of the selected BIDS Data Scientists fellows since 2014. Her work focuses on image analysis and pattern recognition applied to diverse scientific domains - images range from biomedical micrographies to geological materials and composites, e.g. micro-tomography of materials with applications to carbon sequestration. She has acted as Principal/Co- Investigator of several projects related to image analysis, machine learning, pattern recognition, content-based image retrieval and high performance computing. Interests include computer vision, quantitative microscopy, and data sciences. [Previous work]
Scientific Image Analysis - hover on these pictures for details:
Synchrotron-based X-ray micro-tomography for analysis of composites with applications to jet engine construction.
Micro-CT of glass beads in biogenic mixture, using microbe S.pasteurii for calcite precipitation in research about efficient carbon sequestration.
Identication of palladium faces and platinum core from electron tomography for precise control of catalytic reactions during material design.
Quantitative Structure Activity Relationship (QSAR) models for nanoparticles: quantification of chemical composites.
Segmentation of cervical cells as part of the Pap-smear analysis automation process: this work was awarded 1st place in ISBI'2014 Cervical Cell Recognition Challenge.
Team from LBL/UCSF/Oblong developed a gesture-based interface with network diagrams that show traffic patterns, combined with maps of brain structure.
Using time series of 3D confocal imagery to measure cell movement patterns and speed during mitosis of human mammary epithelial cells (in vivo).
Using high-resolution imagery from Auer's lab to search for sub-cellular structures, such as microtubules within human mammary epithelial cells.
FAPESP science foundation, Sao Paulo, Brazil. Her PhD is from the University of Sao Paulo (USP) in Computational Physics (2004), where she developed a prototype for computer-aided leukemia diagnosis in collaboration with the Clinic Hospital FMRP-USP, and feature selection tools for general purpose data applications. As part of her PhD, she was also as a Visiting Researcher in the Electrical and Computer Engineering Department at UC Santa Barbara (2004).