Nanoelectronics Lab

In Stanford Magazine: AI, Technology, and Innovation, Issue 3, 2023- Professor H.-S. Philip Wong and Professor Kwabena Boahen proposed dentricentric computing for energy-efficient neuromorphic computing

In Stanford Magazine: AI, Technology, and Innovation, Issue 3, 2023- Professor H.-S. Philip Wong and Professor Kwabena Boahen proposed dentricentric computing for energy-efficient neuromorphic computing

Stanford engineers have developed a novel resistive random-access memory (RRAM) chip that does the AI processing within the memory itself, thereby eliminating the separation between the compute and memory units. Their compute-in-memory chip, called “NeuRRAM,” is about the size of a fingertip and does more work with limited battery power than what current chips can do.

Ph.D. student Weier Wan and Professor Wong present new chip that ramps up AI computing efficiency

Please visit website : https://roadtripnation.com/leader/rebecca-park?v=f1b8a857

Please visit website : https://roadtripnation.com/leader/rebecca-park?v=f1b8a857

Prof. Wong receives the 2023 IEEE Andrew S. Grove Award, for outstanding contributions to solid-state devices and technology.

PhD student Weier Wan created a more efficient and flexible AI chip, which could bring the power of AI into tiny edge devices.

Professor Wong's talk at SWITCH Conference: "Semiconductors in 2030 and Beyond"

Scaled-Down Carbon Nano Tube Transistors Inch Closer to Silicon Abilities at IEDM 2020

Voltage-Mode RRAM Compute-In-Memory Hardware Presented at VLSI 2020 (link to demo video)

Prof. Wong's online talk at HKU EEE & HKSTP - "N3XT: AI Chips with 1000x Improvement of Computing Energy Efficiency"

Experts Invent a New Way to Track Semiconductor Technology - IEEE Specturm