Anthony Jayanath Vivek

Real-time AI Optimization for HVAC Performance

This presentation demonstrates how simulation informed AI can transform traditionally time-consuming, reactive engineering processes into intelligent, adaptive workflows. By combining high fidelity CFD with fast, learning based models such as reinforcement learning and AI surrogates, AFRY has developed practical frameworks that improve both performance and efficiency for HVAC units.

The talk illustrates this approach through some real-world use cases where AI based climate control is implemented for clean rooms and hospitals, improving energy efficiency and comfort metrics. There is also a brief spotlight on other use cases for AI in simulation-based product development lifecycle.
Together, these examples form a single narrative: AI as an enabler of smarter decision making across design, validation, and operation, accelerating innovation while maintaining engineering trust and robustness.

Bio:
Anthony is a Development Leader in AI and Computational Fluid Dynamics at AFRY, Sweden. With a background in software development and a Master’s degree from Chalmers University focusing on fluid dynamics and thermal management for electric vehicles, he brings a rare combination of engineering physics and data driven methods.
Since 2020, he has delivered advanced simulation and AI enabled solutions across automotive, pharmaceutical, food, infrastructure, and process industries. His current focus is on integrating AI into CAE workflows to make engineering faster, more scalable, and more predictive across the product lifecycle.