CV
Education
- Ph.D in Machine Learning, Georgia Institute of Technology, 2028 (expected)
- M.S. in Electrical and Computer Engineering, Georgia Institute of Technology, 2023
- B.S. in Applied Mathematics, University of California Los Angeles, 2020
- B.S. in Material Science and Engineering (Electronics), University of California Los Angeles, 2020
Skills
- Machine Learning (I guess?)
Publications
A selection of my publications is listed below. Please note that some the previous publications I am in are not pertinent to my current field. For a complete list, please see my Google Scholar profile.
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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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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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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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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.
Teaching