Overview
AI workloads are accelerating demand for higher-density, more power-intensive data centers, putting new pressure on cooling performance, energy efficiency, capacity utilization, and operational resilience. As facilities scale to support AI and high-performance computing, operators and engineering teams need faster, more reliable ways to understand thermal behavior, evaluate infrastructure decisions, and optimize operations before issues affect performance or uptime.
Join these two-part webinars to explore how Synopsys simulation, digital twin, surrogate modeling, and AI-driven optimization technologies can help data center teams move from reactive operations to predictive, insight-driven decision-making. In the first session, we will examine how simulation-based digital twins create a virtual representation of the data center, combining physics-based models with operational data to evaluate cooling performance, infrastructure utilization, and “what-if” scenarios in a risk-free environment.
In the second session, we will focus on how surrogate models, also known as reduced order models (ROMs), enable rapid evaluation of design alternatives and operational strategies. By reducing computational time from hours to seconds, surrogate models can help teams accelerate scenario exploration, optimize PUE, improve collaboration, and democratize simulation insights across engineering, operations, and business stakeholders.
Session Details
Session 1 – October 19, 2026
Digital Twins for Smarter Data Center Operations
As AI workloads continue to drive higher rack densities and increased power consumption, data center operators face growing challenges in managing cooling performance, energy efficiency, capacity utilization, and operational risk. In this session, attendees will learn how simulation-based digital twins combine physics-based simulation with operational data to create a virtual replica of the data center that mirrors real-world behavior. The session will show how digital twins help evaluate “what-if” scenarios, improve thermal management, support proactive operations, and provide a foundation for continuous performance improvement across the facility lifecycle.
Session 2 – October 22, 2026
Accelerating Data Center Innovation with Surrogate Models and AI-Driven Optimization
As data centers evolve to support increasingly demanding AI workloads, engineers and operators must make faster decisions about cooling infrastructure, energy efficiency, capacity planning, and future expansion. This session will explore how surrogate models, or ROMs, built from simulation results and operational data can capture complex system behavior while enabling rapid evaluation of alternatives. Attendees will learn how surrogate models fit within broader digital twin workflows, support AI-driven optimization, and make simulation insights more accessible to engineering, operations, and business teams.
What Attendees Will Learn
- Simulation-based digital twins for predictive data center operations
- Thermal performance, cooling optimization, and PUE improvement workflows
- Risk-free “what-if” scenario evaluation across the data center lifecycle
- Surrogate models and ROMs for rapid design and operational decision-making
- AI-driven optimization and simulation democratization for cross-functional teams
Who Should Attend
This webinar series is designed for data center operators, facility engineers, infrastructure architects, thermal and mechanical engineers, digital twin program leaders, operations managers, sustainability leaders, and engineering managers responsible for planning, designing, operating, or optimizing AI-ready data centers. Attendees will gain practical insight into how simulation, digital twins, surrogate models, and AI-driven optimization can support better decisions around cooling, energy efficiency, capacity planning, reliability, and lifecycle performance.
Speaker
- Jose-Luis Gonzalez Hernandez
Date / Time:
Session #1: October 19, 2026 - 11 AM EST
Session #2: October 22, 2026 - 11 AM EST
Session #1: October 19, 2026 - 11 AM EST
Session #2: October 22, 2026 - 11 AM EST
Venue: Virtual
- Cost:
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