NSF Neocortex Researcher Seminar Series

Dear all, 

It is my privilege to announce and cordially invite you to the NSF Neocortex Seminar Series, a monthly virtual space to highlight and learn from colleagues advancing impactful research powered by the Cerebras WSE (Wafer Scale Engine), the AI accelerator featured in the NSF Neocortex AI supercomputer.

We are inaugurating the virtual series on March 5th at 2 pm ET (today) with a talk from Dr. Matthew Moreno (University of Michigan) titled Sampling- and Estimation-based Strategies for Data Collection in Wafer-Scale Evolution Simulations. Dr. Moreno will be sharing how the powerful WSE has impacted his research in evolutionary biology and allowed him to advance digital experiments exploring cross-scale biological phenomena.

If you haven't registered and have the availability, you, your friends and colleagues are all welcome to join. Please, register using this link.

Inaugural Neocortex Seminar Series Presentation via Zoom

Seminar Title: Sampling- and Estimation-based Strategies for Data Collection in Wafer-Scale Evolution Simulations
Speaker: Matthew A. Moreno, PhD
Affiliation: University of Michigan

Date: March 5, 2026
Time: 2:00 PM (EST)
Host: Paola A. Buitrago, Neocortex PI | Sergiu Sanielevici, Neocortex co-PI

Register and get the Zoom coordinates for the presentation here.

Sampling- and Estimation-based Strategies for Data Collection in Wafer-Scale Evolution



Abstract
Emerging AI/ML-oriented hardware accelerators, like the 880,000-processor Cerebras Wafer-Scale Engine (WSE), have potential to open new frontiers in computational modeling through orders-of-magnitude scale-up of high-performance computing (HPC) workloads. In the context of evolutionary biology, these technologies offer new opportunities for digital experiments exploring cross-scale biological phenomena — such as many-species eco-evolutionary dynamics and evolutionary transitions in individuality (e.g., multicellularity, eusociality). Effectively harnessing AI/ML accelerators for scientific computing workloads, however, poses substantial engineering challenges. One such challenge is tracking simulation dynamics that take place across a vast, highly-distributed fabric of memory-constrained processors. This talk will present technical and practical aspects of sampling- and estimation-based data collection strategies developed to support digital evolution on the Wafer-Scale Engine. At scale, these strategies enable the tracking of evolutionary history across trillions of simulated organisms in agent-based models. The talk will also review recent work migrating experiment and data management pipelines for general-purpose, SDK-based Wafer-Scale computing to the Cerebras Wafer-Scale Cloud.

Bio:

Matthew Andres Moreno is a postdoctoral scholar at the University of Michigan, advised by Dr. Luis Zaman. His research spans evolutionary biology, high-performance computing, and artificial life, developing computational tools and methods for large-scale evolution simulations. At the University of Michigan, he is affiliated with the Ecology and Evolutionary Biology department, the Complex Systems program, and Michigan Institute for Data and AI in Society programs. He completed his graduate studies at the BEACON Center for the Study of Evolution in Action at Michigan State University, advised by Dr. Charles Ofria. He is a former Eric and Wendy Schmidt AI in Science Postdoctoral Fellow and NSF Graduate Research Fellow.

We look forward to your participation!

The Neocortex team