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preprints
Radon Implicit Field Transform (RIFT): Learning Scenes from Radar Signals
Published in ArXiv preprint, submitted to Transactions on Machine Learning Research (TMLR), 2024
Recommended citation: *Daqian Bao*, A. Saad-Falcon, & J. Romberg. (2024). "Radon Implicit Field Transform (RIFT): Learning Scenes from Radar Signals." ArXiv[arXiv:2410.19801].
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Directional Encoding Based Implicit Neural Representation as Compressive Models for Radar Signal
Published in ArXiv preprint, submitted to IEEE Transaction on Antenna and Propagation, 2025
Recommended citation: *Daqian Bao* and Justin Romberg. (2025). "Directional Encoding Based Implicit Neural Representation as Compressive Models for Radar Signal" ArXiv[To Be Updated].
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publications
Metric learning: a new approach for defining similarity measures for nanophotonics
Published in Bulletin of the American Physical Society (APS March Meeting 2022), 2022
Recommended citation: M Zandehshahvar, Y Kiarashinejad, M Hadighejavani, M Zhu, *Daqian Bao*, A Adibi. (2022). "Metric learning: a new approach for defining similarity measures for nanophotonics." Bulletin of the American Physical Society, APS March Meeting 2022, Abstract A24.00003.
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Efficient artificial intelligence techniques for inverse design and knowledge discovery in metamaterials
Published in The Journal of the Acoustical Society of America, 2022
Recommended citation: Zandehshahvar, M., Kiarashinejad, Y., Hadighe Javani, M., Zhu, M., Brown, T., *Daqian Bao* & Adibi, A. (2022). "Efficient artificial intelligence techniques for inverse design and knowledge discovery in metamaterials." The Journal of the Acoustical Society of America 151, A254-A254.
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New paradigms in manifold learning for knowledge discovery and inverse design in nanophotonics
Published in SPIE OPTO, 2023
Recommended citation: Y. Kiarashinejad, M. Zandehshahvar, M. H. Javani, M. Zhu, *Daqian Bao*, R. Pourabolghasem, and A. Adibi. (2023). "New paradigms in manifold learning for knowledge discovery and inverse design in nanophotonics." Proc. SPIE 12430, Photonic and Phononic Properties of Engineered Nanostructures XIII.
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Metric Learning: Harnessing the Power of Machine Learning in Nanophotonics
Published in ACS Photonics, 2023
Recommended citation: Zandehshahvar, M., Kiarashi, Y., Zhu, M., *Daqian Bao*, Javani, M. H., Pourabolghasem, R. & Adibi, A. (2023). "Metric Learning: Harnessing the Power of Machine Learning in Nanophotonics." ACS Photonics 10, 900-909.
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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Graduate Teaching Assistant, Math Foundation for Machine Learning (ECE 7750)
Teaching, Georgia Institute of Technology, 2022
Graduate Teaching Assistant, Math Foundation for Machine Learning (ECE 7750)
Teaching, Georgia Institute of Technology, 2023
Graduate Teaching Assistant, Statistical Machine Learning (ECE 6254)
Teaching, Georgia Institute of Technology, 2024
Graduate Teaching Assistant, Adaptive Filtering (ECE 6271)
Teaching, Georgia Institute of Technology, 2024