Melba Crawford

Melba Crawford

Professor of Agronomy, Civil Engineering, and Electrical and Computer Engineering
Nancy Uridil and Francis Bossu Professor of Civil Engineering
765.496.9355
765.496.2926 (fax)

Area of Expertise

Methods in statistical pattern recognition for high dimensional data analysis, data fusion techniques for multisensor problems, multiresolution methods in image analysis, and knowledge transfer in data mining.

Curriculum Vitae

Professional Experience

2006 - Present

Professor of Civil Engineering, Electrical and Computer Engineering (courtesy), and Agronomy, Purdue University

2009 - 2019

Associate Dean of Engineering for Research, Purdue University

2006 - 2009

Assistant Dean for Interdisciplinary Research, College of Agriculture and College of Engineering, Purdue University

1991 - 2005

Associate Professor of Mechanical Engineering, The University of Texas at Austin

1986 - 1991

Associate Professor of Mechanical Engineering, The University of Texas at Austin

1980 - 1986

Assistant Professor of Mechanical Engineering, The University of Texas at Austin

1977 - 1980

Instructor, The University of Texas at Dallas

 

Publications

  1. Masjedi A, Carpenter NR, Crawford MM, Tuinstra M. Multi-Temporal Predictive Modelling of Sorghum Biomass Using UAV-Based Hyperspectral and LiDAR Data. Remote sensing. 2020; 12(21):3587. DOI: 10.3390/rs12213587
  2. Karami A, Crawford M, Delp E. Automatic Plant Counting and Location Based on a Few-Shot Learning Technique. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2020; 13:5872-5886. Available from: https://ieeexplore.ieee.org/document/9204369/ DOI: 1109/JSTARS.2020.3025790
  3. Ma L, Crawford M, Zhu L, Liu Y. Centroid and Covariance Alignment-Based Domain Adaptation for Unsupervised Classification of Remote Sensing Images. IEEE Transactions on Geoscience and Remote Sensing. 2019; 57(4):2305-2323. Available from: https://ieeexplore.ieee.org/document/8506613/ DOI: 10.1109/TGRS.2018.2872850
  4. Zhang Z, Pasolli E, Crawford M. An Adaptive Multiview Active Learning Approach for Spectral– Spatial Classification of Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing. 2020; 58(4):2557-2570. Available from: https://ieeexplore.ieee.org/document/8937036/ DOI: 10.1109/TGRS.2019.2952319
  1. Taskin G, Crawford M. An Out-of-Sample Extension to Manifold Learning via Meta-Modeling. IEEE Transactions on Image Processing. 2019; 29(10):5227. DOI: 10.1109/TIP.2019.2915162

 

Other Significant Products

  1. Masjedi A, Crawford MM, Carpenter NR, Tuinstra M. Prediction of Sorghum Biomass Using UAV Time Series Data and Recurrent Neural Networks. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops. 2019 June 17; :0. Available from: https://openaccess.thecvf.com/content_CVPRW_2019/html/CVPPP/Masjedi_Prediction_of_Sorghu
  2. Pasolli E, Yang HL., Crawford M. Active-metric Learning for Classification of Remotely Sensed Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing. 2017; 55(11):6594. DOI: 10.1109/TGRS.2015.2490482
  3. Pignotti G, Rathjens H, Cibin R, Chaubey I, Crawford M. Comparative Analysis of Spatial Resolution Effects on HRU and Grid-based SWAT Models. Water. 2017; 9(4):272. DOI: 3390/w9040272
  4. Yang H, Crawford M. Domain Adaptation with Preservation of Manifold Geometry for Hyperspectral Image Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2016; 9(2):543. DOI: 10.1109/JSTARS.2015.2449738
  5. Zhang Z, Pasolli E, Crawford M, Tilton J. An Active Learning Framework for Hyperspectral Image Classification Using Hierarchical Segmentation. IEEE journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2016; 9(2):640. DOI: 10.1109/JSTARS.2015.249388

 

SYNERGISTIC ACTIVITIES

  1. Director, Purdue Laboratory for Applications of Remote Sensing 2006 – present. Current focus on advancing multiscale high resolution sensing for plant science applications, including phenotyping studies and crop management initiatives.
  2. Co-Chair, Purdue Engineering Initiative (PEI) in Data in Engineering Applications (IDEA). Focused on developing the education and research strategy for the Purdue College of Engineering, 2019- 2022
  3. Reviewer and Panelist: NSF and NASA Research Proposals
  4. NSF IoT4Ag Engineering Research Center, U of Penn: Member of the Purdue team, Thrust on advances in data analytics/machine learning, including integration of machine learning-based approaches and biophysical crop models.
  5. Institute of Electrical and Electronic Engineers, Fellow; Women in Engineering Committee, member, Geoscience and Remote Sensing Society, past President, VP for Conferences; Associate Editor, IEEE Transactions on Geoscience and Remote Sensing.