Directory at the HPC²
Email
lalitha@cavs.msstate.edu
Office
CAVS 2123
Phone
(662) 325-5580
Alt. Phone
(662) 694-9499
Mailstop 9627
200 Research Blvd
Mississippi State, MS 39762
lalitha@cavs.msstate.edu
Office
CAVS 2123
Phone
(662) 325-5580
Alt. Phone
(662) 694-9499
Mailstop 9627
200 Research Blvd
Mississippi State, MS 39762
Email
lalitha@cavs.msstate.edu
Office
CAVS 2123
Phone
(662) 325-5580
Alt. Phone
(662) 694-9499
Mailstop 9627
200 Research Blvd
Mississippi State, MS 39762
lalitha@cavs.msstate.edu
Office
CAVS 2123
Phone
(662) 325-5580
Alt. Phone
(662) 694-9499
Mailstop 9627
200 Research Blvd
Mississippi State, MS 39762
Biography
Lalitha Dabbiru is an Assistant Research Professor in the Center for Advanced Vehicular Systems (CAVS) and adjunct faculty in the department of Electrical and Computer Engineering at Mississippi State University. Her research interests include remote sensing, radar and lidar image processing, and machine learning. Her research activities focused on levee anomaly detection, autonomous vehicles, small satellite engineering and knowledge management systems. Her past work experience include fabrication and integration of multi sensor chips. She received the Ph.D. degree in Electrical Engineering at Mississippi State University. She is a member of the IEEE.
Research Interest
Dr. Dabbiru's research focuses on remote sensing, radar and lidar image processing, and machine learning. Current research activities include image segmentation, object detection, and perception for the advancement of autonomous driving technology. Past research focused on levee anomaly detection, small satellite engineering and knowledge management systems.
Selected Publications
Total Publications: 43
Goodin, C., Sharma, S., Doude, M., Carruth, D. W., Dabbiru, L., & Hudson, C. R. (2019). Training of Neural Networks with Automated Labeling of Simulated Sensor Data. SAE Technical Paper 2019-01-0120. Detroit, MI. DOI:10.4271/2019-01-0120. [Abstract] [Document Site]
Dabbiru, L., Aanstoos, J.V., Ball, J. E., & Younan, N. H. (2017). Screening Mississippi River Levees Using Texture-based and Polarimetric-based Features from Synthetic Aperture Radar Data. Electronics. MDPI. 1, 20. [Abstract] [Document Site]
Dabbiru, L., Aanstoos, J.V., & Younan, N. H. (2015). Earthen Levee Slide Detection via Automated Analysis of Synthetic Aperture Radar Imagery. Journal of Landslides. Springer. 1612-5118, 10. DOI:10.1007/s10346-015-0599-9. [Abstract]
Sehat, S., Vahedifard, F., Aanstoos, J.V., Dabbiru, L., & Hasan, K. (2014). Using In situ Soil Measurements for Analysis of a Polarimetric SAR-based Classification of Levee Slump Slides in the Lower Mississippi River. Engineering Geology. Elsevier. 181, 157–168. DOI:10.1016/j.enggeo.2014.07.007. [Document Site]
Nobrega, R. A. A., Aanstoos, J.V., Gokaraju, B., Mahrooghy, M., Dabbiru, L., & O'Hara C. (2013). MAPPING WEAKNESSES IN THE MISSISSIPPI RIVER LEVEE SYSTEM USING MULTI-TEMPORAL UAVSAR DATA. Brazilian Journal of Cartography, Photogrammetry and Remote Sensing. State University of Rio de Janeiro, Rio de Janeiro, Brazil: Brazilian Society for Cartography. 65(4), 681-694. [Abstract]
Dabbiru, L., Aanstoos, J.V., Ball, J. E., & Younan, N. H. (2017). Screening Mississippi River Levees Using Texture-based and Polarimetric-based Features from Synthetic Aperture Radar Data. Electronics. MDPI. 1, 20. [Abstract] [Document Site]
Dabbiru, L., Aanstoos, J.V., & Younan, N. H. (2015). Earthen Levee Slide Detection via Automated Analysis of Synthetic Aperture Radar Imagery. Journal of Landslides. Springer. 1612-5118, 10. DOI:10.1007/s10346-015-0599-9. [Abstract]
Sehat, S., Vahedifard, F., Aanstoos, J.V., Dabbiru, L., & Hasan, K. (2014). Using In situ Soil Measurements for Analysis of a Polarimetric SAR-based Classification of Levee Slump Slides in the Lower Mississippi River. Engineering Geology. Elsevier. 181, 157–168. DOI:10.1016/j.enggeo.2014.07.007. [Document Site]
Nobrega, R. A. A., Aanstoos, J.V., Gokaraju, B., Mahrooghy, M., Dabbiru, L., & O'Hara C. (2013). MAPPING WEAKNESSES IN THE MISSISSIPPI RIVER LEVEE SYSTEM USING MULTI-TEMPORAL UAVSAR DATA. Brazilian Journal of Cartography, Photogrammetry and Remote Sensing. State University of Rio de Janeiro, Rio de Janeiro, Brazil: Brazilian Society for Cartography. 65(4), 681-694. [Abstract]
