Liping Wang
Ph.D. QualifyingMar 30, 2026, 3:00 pm - 5:00 pm
ECE conference room (C101B Engineering)
N/A - qualifying exam
Abstract: qualifying exam
Adviser: Haonan Chen
Co-Adviser: N/A
Non-ECE Member: Christine Chiu, Atmospheric Science
Member 3: Chandrasekaran Venkatachalam, Electrical and Computer Engineering
Addional Members: Jesse Wilson, Electrical and Computer Engineering
Co-Adviser: N/A
Non-ECE Member: Christine Chiu, Atmospheric Science
Member 3: Chandrasekaran Venkatachalam, Electrical and Computer Engineering
Addional Members: Jesse Wilson, Electrical and Computer Engineering
Publications:
Publications & Conference Presentations:
Schmude, J., Roy, S., & Wang, L. PDE foundation models are skillful AI weather emulators for the Martian atmosphere. Submitted to International Conference on Machine Learning (ICML), 2026.
Wang, L., & Chen, H. Precipitation-to-precipitation translation via deep learning for improving satellite precipitation products. To appear in Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2026.
Wang, L., & Chen, H. A transformer-based deep learning model for precipitation retrievals using ATMS observations aboard the NOAA/JPSS satellites. To appear in Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2026.
Wang, L., & Chen, H. Deep learning approach with transformers for passive microwave-based precipitation retrievals using ATMS observations aboard the Joint Polar Satellite System. Presented at the 106th Annual AMS Meeting, Houston, TX, USA, Jan. 2026.
Wang, L., & Chen, H. A novel transformer-based deep learning architecture for satellite precipitation enhancement. Presented at the 106th Annual AMS Meeting, Houston, TX, USA, Jan. 2026.
Wang, L., & Chen, H. A novel transformer-based deep learning model for satellite precipitation enhancement. In Proc. 2026 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM). IEEE, Jan. 2026.
Wang, L., Chen, H., & Li, Z. Multi-scale performance of global blended satellite precipitation products over Taiwan. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024.
Wang, L., Chen, H., Chen, Y., Xie, P., Chen, C. R., & Stewart, J. Q. Bias correction of global blended satellite precipitation products over Taiwan with deep learning. In Proc. 104th Annual AMS Meeting, Baltimore, MD, USA, Jan. 2024.
Wang, L., Chen, H., Li, Z., Chen, Y. L., & Chen, C. R. Multi-scale evaluation of global blended satellite precipitation products over Taiwan. In AGU Fall Meeting Abstracts, Dec. 2023.
Wang, L., Chen, Y. L., Chen, H., Chen, C. R., & Liao, W. W. T. Uncertainty quantification of multi-satellite precipitation products with deep learning: A case study over Taiwan. In Proc. 2023 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM), pp. 218–219. IEEE, Jan. 2023.
Wang, L., & Pasricha, S. A framework for CSI-based indoor localization with ID convolutional neural networks. In Proc. 2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN), pp. 1–8. IEEE, Sep. 2022.
Wang, L., Chen, H., & Liao, W. T. Ensemble learning for improving satellite retrievals of orographic precipitation. In Proc. IGARSS 2022 – IEEE International Geoscience and Remote Sensing Symposium, pp. 4658–4661. IEEE, Jul. 2022.
Wang, L., Tiku, S., & Pasricha, S. CHISEL: Compression-aware high-accuracy embedded indoor localization with deep learning. IEEE Embedded Systems Letters, vol. 14, no. 1, pp. 23–26, 2021.
Book Chapters:
Tiku, S., Wang, L., & Pasricha, S. Machine learning model compression for efficient indoor localization on embedded platforms. In Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing: Software Optimizations and Hardware/Software Codesign, pp. 3–13. Cham, Switzerland: Springer Nature, 2023.
Tiku, S., Wang, L., & Pasricha, S. Exploring model compression for deep machine learning–based indoor localization. In Machine Learning for Indoor Localization and Navigation, pp. 461–471. Cham, Switzerland: Springer International Publishing, 2023.
Publications to be Reviewed:
GPROF-NN: a neural-network-based implementation of the Goddard Profiling Algorithm
Prithvi WxC: Foundation Model for Weather and Climate
Publications & Conference Presentations:
Schmude, J., Roy, S., & Wang, L. PDE foundation models are skillful AI weather emulators for the Martian atmosphere. Submitted to International Conference on Machine Learning (ICML), 2026.
Wang, L., & Chen, H. Precipitation-to-precipitation translation via deep learning for improving satellite precipitation products. To appear in Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2026.
Wang, L., & Chen, H. A transformer-based deep learning model for precipitation retrievals using ATMS observations aboard the NOAA/JPSS satellites. To appear in Proc. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2026.
Wang, L., & Chen, H. Deep learning approach with transformers for passive microwave-based precipitation retrievals using ATMS observations aboard the Joint Polar Satellite System. Presented at the 106th Annual AMS Meeting, Houston, TX, USA, Jan. 2026.
Wang, L., & Chen, H. A novel transformer-based deep learning architecture for satellite precipitation enhancement. Presented at the 106th Annual AMS Meeting, Houston, TX, USA, Jan. 2026.
Wang, L., & Chen, H. A novel transformer-based deep learning model for satellite precipitation enhancement. In Proc. 2026 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM). IEEE, Jan. 2026.
Wang, L., Chen, H., & Li, Z. Multi-scale performance of global blended satellite precipitation products over Taiwan. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024.
Wang, L., Chen, H., Chen, Y., Xie, P., Chen, C. R., & Stewart, J. Q. Bias correction of global blended satellite precipitation products over Taiwan with deep learning. In Proc. 104th Annual AMS Meeting, Baltimore, MD, USA, Jan. 2024.
Wang, L., Chen, H., Li, Z., Chen, Y. L., & Chen, C. R. Multi-scale evaluation of global blended satellite precipitation products over Taiwan. In AGU Fall Meeting Abstracts, Dec. 2023.
Wang, L., Chen, Y. L., Chen, H., Chen, C. R., & Liao, W. W. T. Uncertainty quantification of multi-satellite precipitation products with deep learning: A case study over Taiwan. In Proc. 2023 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM), pp. 218–219. IEEE, Jan. 2023.
Wang, L., & Pasricha, S. A framework for CSI-based indoor localization with ID convolutional neural networks. In Proc. 2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN), pp. 1–8. IEEE, Sep. 2022.
Wang, L., Chen, H., & Liao, W. T. Ensemble learning for improving satellite retrievals of orographic precipitation. In Proc. IGARSS 2022 – IEEE International Geoscience and Remote Sensing Symposium, pp. 4658–4661. IEEE, Jul. 2022.
Wang, L., Tiku, S., & Pasricha, S. CHISEL: Compression-aware high-accuracy embedded indoor localization with deep learning. IEEE Embedded Systems Letters, vol. 14, no. 1, pp. 23–26, 2021.
Book Chapters:
Tiku, S., Wang, L., & Pasricha, S. Machine learning model compression for efficient indoor localization on embedded platforms. In Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing: Software Optimizations and Hardware/Software Codesign, pp. 3–13. Cham, Switzerland: Springer Nature, 2023.
Tiku, S., Wang, L., & Pasricha, S. Exploring model compression for deep machine learning–based indoor localization. In Machine Learning for Indoor Localization and Navigation, pp. 461–471. Cham, Switzerland: Springer International Publishing, 2023.
Publications to be Reviewed:
GPROF-NN: a neural-network-based implementation of the Goddard Profiling Algorithm
Prithvi WxC: Foundation Model for Weather and Climate
Program of Study:
ATS 693 Responsible Research
ECE 513 Digital Image Processing
ATS 652 Atmospheric Remote Sensing
ECE 578 Satellite Data Analysis
ECE 699 Thesis
ECE 799 Dissertation
GSTR 600 Credits From Masters
N/A
ATS 693 Responsible Research
ECE 513 Digital Image Processing
ATS 652 Atmospheric Remote Sensing
ECE 578 Satellite Data Analysis
ECE 699 Thesis
ECE 799 Dissertation
GSTR 600 Credits From Masters
N/A