Stan Williams 75th Birthday Symposium

Timothy D. Brown

Oklahoma State University

To be announced

Yong Chen

University of California, Los Angeles

Synstor Circuits to Reboot AI Systems

Miao Hu

TetraMem Inc.

A Systematic Approach to Overcoming Analog Loss in Memristor-Based In-Memory Computing

Duygu Kuzum

University of California, San Diego

8-Layer Vertical Filament-Free Bulk RRAM for 3D Multilevel Compute-in-Memory

Matthew Marinella

Arizona State University

Memristors for Energy Efficient Spaceborne AI Computing

Gilberto Medeiros-Ribeiro

Universidade Federal de Minas Gerais

Direct Visualization of Filament Nucleation, Growth, and Recession in an Electrically Driven VO₂ Insulator–Metal Transition, and a Test of Ridley's Minimum-Entropy-Production Principle

Aishwarya Natarajan

Hewlett Packard Enterprise

Next-Generation Hardware Accelerators: Analog and Neuromorphic In-Memory Computing

John Paul Strachan

Forschungszentrum Jülich / RWTH Aachen University

Adapting in-memory computing for today’s AI models and beyond

Dmitri B. Strukov

University of California, Santa Barbara

From Memristors to Neuromorphic Computing: A Personal Research Journey

A. Alec Talin

Sandia National Laboratories

Introduction talk

Rainer Waser

RWTH Aachen University / Forschungszentrum Jülich

Interdisciplinarity in the Research on Memristive Switching and Artificial Intelligence

R. Stanley Williams

Texas A&M University

Edge of Chaos and Entropy Production Minimization as Keys to Neuromorphic Computing

Qiangfei Xia

University of Massachusetts Amherst

Memristive Devices and Systems for Emerging AI Hardware: From Research to Innovation

J. Joshua Yang

University of Southern California

Taming Ions and Electrons for Memory in Extreme Environments

Wei Yi

Applied Materials

Nonlinear dynamics and stability analysis of locally active Mott memristors using a physics-based compact model