Sihan Shao (邵思涵)

I am a Ph.D. student at FAU ECLIPSE Lab, working with Prof. Philipp Pelz. My research focuses on computational imaging in X-ray and electron microscopy, particularly in tomography and ptychography.

In my free time, I enjoy running, swimming, and sauna.

Email  /  CV  /  GitHub  /  LinkedIn

Research

I'm interested in computational imaging, computer vision, machine learning, and optimization.

Rim-Integrated Bluetooth Antenna for Smart Watches with Full-Metallic Structure

This paper explores the design, manufacturing, and a prototype measurement of a Bluetooth antenna integrated into the metallic rim of a smartwatch.

Neural Dispersive Hologram for Computational Submillimeter-wave Imaging

Developed a multi-wavelength wave propagation simulation using PyTorch, co-optimized a sub-millimeter imaging system’s hardware and neural networks, introduced a surrogate gradient method for optimizing quantized holograms, and validated the system with real measurements.

Quantized THz Diffractive Optics Design via Automatic Differentiation

We explored the angular spectrum method (ASM) with automatic differentiation to optimize highly quantized diffractive optical elements (DOEs) for terahertz applications, facilitating precise control over radiation modulation while accounting for practical manufacturing limitations of 3D printer.

Harnessing Frequency Diversity for Improved Holographic Imaging Systems

The study examines how frequency diversity over time in a 340 GHz FMCW radar system with a dispersive hologram enhances target imaging and discrimination by capturing more detailed spatial information.

SAR Ship Detection from Complex Background Based on Dynamic Shrinkage Attention Mechanism

We developed a SAR ship detection method addressing challenges like speckle noise and complex backgrounds using a feature-level denoising approach called dynamic shrinkage attention.

Soft Thresholding Attention Network for Adaptive Feature Denoising in SAR Ship Detection

Proposed a feature-level denoising methodology for synthetic aperture radar ship detection, leveraging soft thresholding and attention mechanisms, which enhanced detection precision across several neural network models.

Lidar Sensor-Based Object Recognition Using Machine Learning

We developed a Lidar-based data collection system and applied filtering, clustering, PCA, and SVM techniques to improve the classification efficiency and accuracy of pedestrians and vehicles in point cloud data.

Projects

These include coursework, thesis projects and unpublished research work.

Image Deblurring with Neural Networks Using Fourier Optics

I simulated the optical blur caused by a camera lens with chromatic aberrations and depth-dependent point spread functions (PSFs), and created an image deblurring system by building a dataset and training a neural network.

Design of Vivaldi Array Antenna

With Guo Wei and Zhenhan Wang. Designed and manufactured a 4-Way Wilkinson Power Divider and Vivaldi array antenna with CST.

A 1.5 GHz Doppler Radar

With Yifan Yu. Designed and manufactured 1.5 GHz Doppler Radar with filters, mixer, oscillaor and amplifier.

Design and source code from Jon Barron's website