Zhenya Zang

Zhenya Zang is a researcher specializing in deep learning applications for biomedical optics and hardware-accelerated signal processing, with recent focus on diffuse correlation spectroscopy for medical diagnostics.

Education

• PhD completed January 2025 with thesis: "Towards highly efficient algorithms and hardware architecture design for single-photon signal processing"

Research Focus

Zang's work bridges computer science and biomedical engineering through:

• Development of back-propagation-free neural network algorithms
• Hardware-embedded data processors for real-time imaging
• Optimization of deep learning architectures for optical diagnostics
• Extreme learning machine implementations in medical hardware

Publication Trends

2025 research demonstrates a clear trajectory toward deployable medical AI systems, emphasizing hardware-software co-design to solve latency challenges in blood flow monitoring. Key innovations include convolutional neural network adaptations for diode array sensors and accuracy-focused detection frameworks.

Scientific Awards

No awards documented in available records.

Grants & Collaboration

• Researcher on "Smart Hardware-embedded Data Processors for Rapid 3D Ranging & Imaging" (2019-2022), a studentship project led by Principal Investigator D. Li

Current work shows no student supervision activity.

Research Infrastructure

Publications indicate work within embedded hardware development environments for medical imaging, though specific laboratory affiliations remain undocumented.