15.3 A 65nm 3T Dynamic Analog RAM-Based Computing-in-Memory Macro and CNN Accelerator with Retention Enhancement, Adaptive Analog Sparsity and 44TOPS/W System Energy Efficiency. - Zhengyu Chen 002; Xi Chen 099; Jie Gu 001 (ISSCC, 2021)

A 65nm Implantable Gesture Classification SoC for Rehabilitation with Enhanced Data Compression and Encoding for Robust Neural Network Operation Under Wireless Power Condition. - Yijie Wei; Xi Chen 099; Jie Gu 001 (CICC, 2022)

A 65nm Fully-integrated Fast-switching Buck Converter with Resonant Gate Drive and Automatic Tracking. - Xi Chen 099; Aly Shoukry; Tianyu Jia; Xin Zhang 025; Raveesh Magod; Nachiket V. Desai; Jie Gu 001 (CICC, 2023)

Development of Tropical Algebraic Accelerator with Energy Efficient Time-Domain Computing for Combinatorial Optimization and Machine Learning. - Qiankai Cao; Xi Chen 099; Jie Gu 001 (ISLPED, 2023)

Proactive Power Regulation with Real-time Prediction and Fast Response Guardband for Fine-grained Dynamic Voltage Droop Mitigation on Digital SoCs. - Xi Chen 099; Jiaxiang Feng; Aly Shoukry; Xin Zhang 025; Raveesh Magod; Nachiket V. Desai; Jie Gu 001 (VLSI Technology and Circuits, 2023)

A General-Purpose Compute-in-Memory Processor Combining CPU and Deep Learning with Elevated CPU Efficiency and Enhanced Data Locality. - Yuhao Ju; Yijie Wei; Xi Chen 099; Jie Gu 001 (VLSI Technology and Circuits, 2023)

Human Activity Recognition SoC for AR/VR with Integrated Neural Sensing, AI Classifier and Chained Infrared Communication for Multi-chip Collaboration. - Yijie Wei; Xi Chen 099; Jie Gu 001 (VLSI Technology and Circuits, 2023)

LLM-MARK: A Computing Framework on Efficient Watermarking of Large Language Models for Authentic Use of Generative AI at Local Devices. - Shiyu Guo; Yuhao Ju; Xi Chen 099; Jie Gu 001 (DAC, 2024)

Mobile-PBR: A 28-nm Energy-Efficient Rendering Processor for Photorealistic Augmented Reality With Inverse Rendering and Background Clustering. - Shiyu Guo; Yuhao Ju; Xi Chen 099; Sachin S. Sapatnekar; Jie Gu 001 (IEEE J. Solid State Circuits, 2025)

A 65-nm Proactive Power Management Technique With Real-Time Machine Learning Engine for Droop Prediction and Mitigation on Microprocessors. - Xi Chen 099; Jiaxiang Feng; Aly Shoukry; Xin Zhang 025; Raveesh Magod; Nachiket V. Desai; Jie Gu 001 (IEEE J. Solid State Circuits, 2025)