Jordan Milton Malof | Scholars@Duke

Jordan Milton Malof
Adjunct Assistant Professor in the Department of Electrical and Computer Engineering

I work with domain experts across different fields to solve challenging real-world problems through the application or development of advanced signal processing, computer vision, machine learning (especially deep learning) methods to real-world problems. Recently, my work has spanned topics such as remote sensing, energy systems, and materials science. My work has recently been featured in premiere machine learning conferences (e.g., NeurIps, ICLR) and computer vision conferences (e.g., WACV).

Current Research Interests

Application of advanced machine learning and computer vision techniques to real-world problems

Current Appointments & Affiliations

Adjunct Assistant Professor in the Department of Electrical and Computer Engineering, Electrical and Computer Engineering, Pratt School of Engineering 2022

Contact Information

jordan.malof@duke.edu

Background
Education, Training, & Certifications
- Ph.D., Duke University 2015
Previous Appointments & Affiliations
- Assistant Research Professor in the Department of Electrical and Computer Engineering, Electrical and Computer Engineering, Pratt School of Engineering 2016 - 2022
- Faculty Fellow in The Energy Initiative, Nicholas Institute-Energy Initiative, Initiatives 2018 - 2022
Recognition
Awards & Honors
- Bass Connections Award for Outstanding Leadership. Duke University. 2022
Research
Selected Grants
- Estimating regional non-electricity building energy consumption awarded by WattTime 2022 - 2023
- Deep Context-aware Discriminative Learning for Buried Threat Detection: single sensor processing and multi-sensor fusion awarded by Army Research Office 2017 - 2022
- Estimating solar PV locations and capacity in San Diego, CA awarded by Ernest Orlando Lawrence Berkeley National Laboratory 2019 - 2021
- RAISE: C-Accel Pilot - Track A1: Open Knowledge Network for the Global Energy Data Commons awarded by National Science Foundation 2019 - 2021
- Solar array identification in Adelaide, Australia awarded by Australia Energy Market Operator 2018
External Relationships
- Security Camera Maintenance Company
Publications & Artistic Works
Selected Publications
- Academic Articles
  - Calhoun, Z. D., S. Lahrichi, S. Ren, J. M. Malof, and K. Bradbury. “Self-Supervised Encoders Are Better Transfer Learners in Remote Sensing Applications.” Remote Sensing 14, no. 21 (November 1, 2022). https://doi.org/10.3390/rs14215500.
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  - Khatib, O., S. Ren, J. Malof, and W. J. Padilla. “Learning the Physics of All-Dielectric Metamaterials with Deep Lorentz Neural Networks.” Advanced Optical Materials 10, no. 13 (July 1, 2022). https://doi.org/10.1002/adom.202200097.
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  - Ren, S., J. Malof, R. Fetter, R. Beach, J. Rineer, and K. Bradbury. “Utilizing Geospatial Data for Assessing Energy Security: Mapping Small Solar Home Systems Using Unmanned Aerial Vehicles and Deep Learning.” Isprs International Journal of Geo Information 11, no. 4 (April 1, 2022). https://doi.org/10.3390/ijgi11040222.
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  - Ren, Simiao, Ashwin Mahendra, Omar Khatib, Yang Deng, Willie J. Padilla, and Jordan M. Malof. “Inverse deep learning methods and benchmarks for artificial electromagnetic material design.” Nanoscale 14, no. 10 (March 2022): 3958–69. https://doi.org/10.1039/d1nr08346e.
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  - Huang, B., J. Yang, A. Streltsov, K. Bradbury, L. M. Collins, and J. M. Malof. “GridTracer: Automatic Mapping of Power Grids Using Deep Learning and Overhead Imagery.” Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15 (January 1, 2022): 4956–70. https://doi.org/10.1109/JSTARS.2021.3124519.
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  - Xu, Y., B. Huang, X. Luo, K. Bradbury, and J. M. Malof. “SIMPL: Generating Synthetic Overhead Imagery to Address Custom Zero-Shot and Few-Shot Detection Problems.” Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15 (January 1, 2022): 4386–96. https://doi.org/10.1109/JSTARS.2022.3172243.
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  - Khatib, O., S. Ren, J. Malof, and W. J. Padilla. “Deep Learning the Electromagnetic Properties of Metamaterials—A Comprehensive Review.” Advanced Functional Materials 31, no. 31 (August 1, 2021). https://doi.org/10.1002/adfm.202101748.
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  - Deng, Yang, Simiao Ren, Kebin Fan, Jordan M. Malof, and Willie J. Padilla. “Neural-adjoint method for the inverse design of all-dielectric metasurfaces.” Optics Express 29, no. 5 (March 2021): 7526–34. https://doi.org/10.1364/oe.419138.
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  - Streltsov, A., J. M. Malof, B. Huang, and K. Bradbury. “Estimating residential building energy consumption using overhead imagery.” Applied Energy 280 (December 15, 2020). https://doi.org/10.1016/j.apenergy.2020.116018.
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  - Malof, J. M., D. Reichman, A. Karem, H. Frigui, K. C. Ho, J. N. Wilson, W. H. Lee, W. J. Cummings, and L. M. Collins. “A large-scale multi-institutional evaluation of advanced discrimination algorithms for buried threat detection in ground penetrating radar.” Ieee Transactions on Geoscience and Remote Sensing 57, no. 9 (September 1, 2019): 6929–45. https://doi.org/10.1109/TGRS.2019.2909665.
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  - Nadell, Christian C., Bohao Huang, Jordan M. Malof, and Willie J. Padilla. “Deep learning for accelerated all-dielectric metasurface design.” Optics Express 27, no. 20 (September 2019): 27523–35. https://doi.org/10.1364/oe.27.027523.
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  - Malof, J. M., K. Bradbury, L. M. Collins, and R. G. Newell. “Automatic detection of solar photovoltaic arrays in high resolution aerial imagery.” Applied Energy 183 (December 1, 2016): 229–40. https://doi.org/10.1016/j.apenergy.2016.08.191.
    Full Text Open Access Copy
  - Malof, J. M., K. D. Morton, L. M. Collins, and P. A. Torrione. “A Probabilistic Model for Designing Multimodality Landmine Detection Systems to Improve Rates of Advance.” Ieee Transactions on Geoscience and Remote Sensing 54, no. 9 (September 1, 2016): 5258–70. https://doi.org/10.1109/TGRS.2016.2559505.
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- Conference Papers
  - Kong, F., B. Huang, K. Bradbury, and J. M. Malof. “The synthinel-1 dataset: A collection of high resolution synthetic overhead imagery for building segmentation.” In Proceedings 2020 Ieee Winter Conference on Applications of Computer Vision, Wacv 2020, 1803–12, 2020. https://doi.org/10.1109/WACV45572.2020.9093339.
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  - Ren, S., W. J. Padilla, and J. Malof. “Benchmarking deep inverse models over time, and the neural-adjoint method.” In Advances in Neural Information Processing Systems, Vol. 2020-December, 2020.
  - Kong, F., C. Chen, B. Huang, L. M. Collins, K. Bradbury, and J. M. Malof. “Training a single multi-class convolutional segmentation network using multiple datasets with heterogeneous labels: Preliminary results.” In International Geoscience and Remote Sensing Symposium (Igarss), 3903–6, 2019. https://doi.org/10.1109/IGARSS.2019.8898617.
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  - Lin, K., B. Huang, L. M. Collins, K. Bradbury, and J. M. Malof. “A simple rotational equivariance loss for generic convolutional segmentation networks: Preliminary results.” In International Geoscience and Remote Sensing Symposium (Igarss), 3876–79, 2019. https://doi.org/10.1109/IGARSS.2019.8898722.
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  - Huang, B., K. Lu, N. Audebert, A. Khalel, Y. Tarabalka, J. Malof, A. Boulch, et al. “Large-scale semantic classification: Outcome of the first year of inria aerial image labeling benchmark.” In International Geoscience and Remote Sensing Symposium (Igarss), 2018-July:6947–50, 2018. https://doi.org/10.1109/IGARSS.2018.8518525.
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  - Reichman, D., L. M. Collins, and J. M. Malof. “Some good practices for applying convolutional neural networks to buried threat detection in Ground Penetrating Radar.” In 2017 9th International Workshop on Advanced Ground Penetrating Radar, Iwagpr 2017 Proceedings, 2017. https://doi.org/10.1109/IWAGPR.2017.7996100.
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  - Malof, J. M., K. D. Morton, L. M. Collins, and P. A. Torrione. “A queuing model for designing multi-modality buried target detection systems: Preliminary results.” In Proceedings of Spie the International Society for Optical Engineering, Vol. 9454, 2015. https://doi.org/10.1117/12.2176610.
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  - Malof, J. M., R. Hou, L. M. Collins, K. Bradbury, and R. Newell. “Automatic solar photovoltaic panel detection in satellite imagery.” In 2015 International Conference on Renewable Energy Research and Applications, Icrera 2015, 1428–31, 2015. https://doi.org/10.1109/ICRERA.2015.7418643.
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- Datasets
  - Deng, Yang, Mohammadreza Soltani, Simiao Ren, Willie Padilla, Omar Khatib, Vahid Tarokh, Juncheng Dong, and Jordan Malof. “Data from: Benchmarking deep learning architectures for artificial electromagnetic material problems,” August 25, 2021. https://doi.org/10.7924/r4jm2bv29.
    Data Access
- Preprints
  - Spell, Gregory P., Simiao Ren, Leslie M. Collins, and Jordan M. Malof. “Mixture Manifold Networks: A Computationally Efficient Baseline for Inverse Modeling,” November 25, 2022.
    Link to Item
  - Xu, Yang, Bohao Huang, Xiong Luo, Kyle Bradbury, and Jordan M. Malof. “SIMPL: Generating Synthetic Overhead Imagery to Address Zero-shot and Few-Shot Detection Problems,” June 29, 2021.
    Link to Item
  - Yaras, Can, Bohao Huang, Kyle Bradbury, and Jordan M. Malof. “Randomized Histogram Matching: A Simple Augmentation for Unsupervised Domain Adaptation in Overhead Imagery,” April 28, 2021.
    Link to Item
  - Kong, Fanjie, Bohao Huang, Kyle Bradbury, and Jordan M. Malof. “The Synthinel-1 dataset: a collection of high resolution synthetic overhead imagery for building segmentation,” January 14, 2020.
    Link to Item
  - Hu, Wei, Kyle Bradbury, Jordan M. Malof, Boning Li, Bohao Huang, Artem Streltsov, K Sydny Fujita, and Ben Hoen. “What you get is not always what you see: pitfalls in solar array assessment using overhead imagery,” February 28, 2019.
    Link to Item
  - Malof, Jordan M., Daniel Reichman, Andrew Karem, Hichem Frigui, Dominic K. C. Ho, Joseph N. Wilson, Wen-Hsiung Lee, William Cummings, and Leslie M. Collins. “A Large-Scale Multi-Institutional Evaluation of Advanced Discrimination Algorithms for Buried Threat Detection in Ground Penetrating Radar,” March 9, 2018.
    Link to Item
  - Camilo, Joseph, Rui Wang, Leslie M. Collins, Kyle Bradbury, and Jordan M. Malof. “Application of a semantic segmentation convolutional neural network for accurate automatic detection and mapping of solar photovoltaic arrays in aerial imagery,” January 11, 2018.
    Link to Item
  - Malof, Jordan M., Kyle Bradbury, Leslie M. Collins, and Richard G. Newell. “Automatic Detection of Solar Photovoltaic Arrays in High Resolution Aerial Imagery,” July 20, 2016.
    Link to Item
Teaching & Mentoring
Recent Courses
Scholarly, Clinical, & Service Activities
Outreach & Engaged Scholarship

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Education, Training, & Certifications

Previous Appointments & Affiliations

Awards & Honors

Selected Grants

External Relationships

Selected Publications

Academic Articles

Conference Papers

Datasets

Preprints

Recent Courses

Outreach & Engaged Scholarship