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third author | ResSKNet-SSDP: Effective and Light End-To-End Architecture for Speaker Recognition

Published in Sensors, 2023

Proposed a lightweight speaker recognition network based on ResNet.

✧ first author | Seismic First Break Picking Through Swin Transformer Feature Extraction

Published in IEEE Geoscience and Remote Sensing Letters, 2023

High precision first break picking achieved using MSA based Swin Transformer.

third author | FSegNet: A Semantic Segmentation Network for High-Resolution Remote Sensing Images That Balances Efficiency and Performance

Published in IEEE Geoscience and Remote Sensing Letters, 2024

A remote sensing image segmentation network with both performance and efficiency.

third author | Semi-Airborne Transient Electromagnetic Denoising Through Variation Diffusion Model

Published in IEEE Transactions on Geoscience and Remote Sensing, 2024

Using Diffusion Model for denoising Semi-Aerial Electromagnetic signals.

third author | EEGDiR: Electroencephalogram denoising network for temporal information storage and global modeling

Published in Computers in Biology and Medicine, 2024

Deep learning-based EEG denoising techniques leverage the Retentive Network (Retnet) from large-scale language models.

✧ co-first author | Three-Dimensional Magnetotelluric Forward Modeling Through Deep Learning

Published in IEEE Transactions on Geoscience and Remote Sensing, 2024

Implementing 3-D magnetotelluric(MT) forward modeling with certain generalization through deep learning network.

✧ first author | 3-D Seismic First Break Picking Based on Two Channel Mask Strategy

Published in IEEE Transactions on Geoscience and Remote Sensing, 2024

Propose a two channel mask strategy to improve the accuracy and generalization of first break picking.

third author | SeisFusion: Constrained Diffusion Model With Input Guidance for 3-D Seismic Data Interpolation and Reconstruction

Published in IEEE Transactions on Geoscience and Remote Sensing, 2024

3-D seismic data interpolation and reconstruction using Diffusion Model.

✧ first author | 3-D Magnetotelluric Deep Learning Inversion Guided by Pseudo-Physical Information

Published in arXiv, Submit to IEEE TGRS, 2024

A new deep learning method for 3-D magnetotelluric inversion.

GEM 2024 Shenzhen: International Workshop on Gravity, Electrical, and Magnetic Methods and Their Applications

Published: May 19, 2024

Poster speech titled “Fast Forward Modeling of 3-D Magnetotellurics via Neural Networks”

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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