activity
20242026
most citedSparseC-AFM: a deep learning method for fast and accurate characterization of MoS with C-AFM

1 citations · 1 across the 10 of their papers we have counts for

collaborators

10 papers

physics.optics2026

OptiClear: Differentiable Curvilinear Design Rule Legalization for Inverse-Designed Photonic Devices

Hongjian Zhou, Haoyu Yang, Nicholas Gangi +3

Photonic inverse design enables ultra-compact, high-performance devices with highly curvilinear and non-intuitive geometries, but the resulting layouts often violate fabrication de…

physics.optics2026

End-to-End Physical Design Automation Flow for Yield-Optimized Inverse-Designed Large-Scale Electronic-Photonic Integrated Circuits

Hongjian Zhou, Haoyu Yang, Haoxing Ren +2

As AI systems scale to multi-chiplet and wafer-level architectures, the demand for ultra-high bandwidth and system scalability has outpaced the capabilities of electrical interconn…

physics.optics2026

Harnessing Photonics for Machine Intelligence

Hanqing Zhu, Shupeng Ning, Hongjian Zhou +4

The exponential growth of machine-intelligence workloads is colliding with the power, memory, and interconnect limits of the post-Moore era, motivating compute substrates that scal…

physics.optics2025

Democratizing Electronic-Photonic AI Systems: An Open-Source AI-Infused Cross-Layer Co-Design and Design Automation Toolflow

Hongjian Zhou, Ziang Yin, Jiaqi Gu

Photonics is becoming a cornerstone technology for high-performance AI systems and scientific computing, offering unparalleled speed, parallelism, and energy efficiency. Despite th…

physics.optics2025

Toward Large-Scale Photonics-Empowered AI Systems: From Physical Design Automation to System-Algorithm Co-Exploration

Ziang Yin, Hongjian Zhou, Nicholas Gangi +4

In this work, we identify three considerations that are essential for realizing practical photonic AI systems at scale: (1) dynamic tensor operation support for modern models rathe…

physics.optics2025

Photonics-Aware Planning-Guided Automated Electrical Routing for Large-Scale Active Photonic Integrated Circuits

Hongjian Zhou, Haoyu Yang, Nicholas Gangi +6

The rising demand for AI training and inference, as well as scientific computing, combined with stringent latency and energy budgets, is driving the adoption of integrated photonic…

cs.ET2025

Toward Intelligent Electronic-Photonic Design Automation for Large-Scale Photonic Integrated Circuits: from Device Inverse Design to Physical Layout Generation

Hongjian Zhou, Pingchuan Ma, Jiaqi Gu

Photonic Integrated Circuits (PICs) offer tremendous advantages in bandwidth, parallelism, and energy efficiency, making them essential for emerging applications in artificial inte…

cs.CV2025★ 1 cited

SparseC-AFM: a deep learning method for fast and accurate characterization of MoS with C-AFM

Levi Harris, Md Jayed Hossain, Mufan Qiu +6

The increasing use of two-dimensional (2D) materials in nanoelectronics demands robust metrology techniques for electrical characterization, especially for large-scale production.…

cs.ET2025

Apollo: Automated Routing-Informed Placement for Large-Scale Photonic Integrated Circuits

Hongjian Zhou, Haoyu Yang, Nicholas Gangi +3

As technology advances, photonic integrated circuits (PICs) are rapidly scaling in size and complexity, with modern designs integrating thousands of components. However, the analog…

cs.ET2024

Automated Curvy Waveguide Routing for Large-Scale Photonic Integrated Circuits

Hongjian Zhou, Keren Zhu, Jiaqi Gu

As photonic integrated circuit (PIC) designs advance and grow in complexity, largely driven by innovations in photonic computing and interconnects, traditional manual physical desi…