ATCx AI for Engineers 2025 Global Virtual Event

ATCx AI for Engineers 2025, Altair's global virtual event, which focuses on the practical impact of AI in engineering. Bringing together industry experts, engineers, and technologists, the event showcases how AI is being applied across various domains, disciplines, and the world.

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18 Jun, 2025. 6 minutes read

ATCx AI for Engineers 2025 Global Virtual Event

Topic

Manufacturing

Tags

artificial intelligence
manufacturing intelligence
manufacturing systems
Simulation Software

Introduction

Artificial Intelligence is fundamentally transforming engineering. From streamlining design iterations to enhancing complex simulations, AI has evolved into a critical tool for product innovation. As industries face demands for faster development, higher performance, and increased sustainability, engineers are shifting toward intelligent, data-driven workflows.

At the forefront of this transformation is Altair, a global leader in computational science and artificial intelligence. With nearly four decades of expertise in simulation, high-performance computing and technology, Altair’s technologies empower engineers to design, simulate, and optimise faster and more effectively. Its platforms, such as SmartWorks, HyperWorks, and PhysicsAI, are used across the aerospace, automotive, electronics, and manufacturing industries to tackle complex engineering challenges with precision and agility.

This philosophy will take centre stage at ATCx AI for Engineers 2025, Altair’s global virtual event, which focuses on the practical impact of AI in engineering. Bringing together industry experts, engineers, and technologists, the event showcases how AI is being applied across various domains, disciplines, and the world.

One of the standout sessions features Ujwal Patnaik, Global Senior Director of Product Strategy at Altair, presenting his keynote “100 Use Cases Later: What AI Has Taught Us About Engineering”.

Rather than speculating about AI’s future potential, this session focuses on what AI is already doing—today. Ujwal draws from 100 real-world engineering implementations, spanning applications from crash simulation and battery health prediction to HVAC optimisation. The goal isn’t to walk through each use case, it’s to decode the bigger picture: What patterns emerge from successful AI workflows? What’s working across industries? Where is the real ROI—whether in time saved, waste eliminated, or quality gained?

As Ujwal puts it, “AI isn’t just a tool – it’s becoming a new way of engineering ”. And once you’ve seen what 100 real AI solutions look like, the natural question becomes: What’s stopping you from doing the 101st?

Register now.

Engineering at the Speed of Intelligence

Modern engineering isn’t just about performance it’s about making the smartest decisions in the shortest amount of time. As product requirements become increasingly complex and development cycles compress from years to months, engineers require tools that enable them to design, simulate, and optimise without delay. AI has emerged as a force multiplier. When paired with simulation, it unlocks the ability to explore more design alternatives, predict failures earlier, and reduce the need for repetitive physical testing. With Altair’s PhysicsAI, engineers can build surrogate models that replicate simulation results with a fraction of the computational effort—freeing up time and resources to innovate. Tasks like optimising aerodynamics or thermal dissipation now take hours instead of weeks. This speed doesn't come at the cost of accuracy, it’s built on it.

What 100 Use Cases Reveal

In his keynote, Ujwal Patnaik doesn’t just recount stories. He extracts patterns. Across the 100 use cases he analyses, four themes repeatedly emerge:

  1. Start small, scale smart
    The most successful AI projects don’t aim to overhaul an entire product lifecycle on day one. They begin with high-impact, focused use cases, such as optimising component geometry, predicting mechanical fatigue, or accelerating computational fluid dynamics (CFD) studies. These small wins build momentum.

  2. Physics + AI is greater than either alone.
    Hybrid modelling is a recurring strategy that combines simulation data with machine learning models. By training AI on historical simulation results, teams create fast, reliable predictors that reduce solver time while preserving fidelity.

  3. The engineer remains central.
    Contrary to common fear, AI isn’t replacing engineers—it’s augmenting them. In the most effective deployments, engineers guide the models, define the constraints, and interpret results. AI handles the repetition, but humans retain control over the process.

  4. Data infrastructure matters
    Projects didn’t fail because the AI didn’t work—they struggled when data was siloed, messy, or incomplete. Clean, connected, and structured data pipelines made the difference between experimentation and scaled success.

Ultimately, the session drives home one message: AI isn’t magic it’s a method. And like any method, it works best when it’s grounded in engineering judgment and enterprise readiness.

Empowering Engineers, Not Replacing Them

AI is only as powerful as the people who use it. That’s why Altair’s platforms are built with engineers, not data scientists, in mind. Altair SmartWorks is a low-code/no-code environment that allows engineers to integrate AI into their workflows without writing complex code. It democratises access to machine learning, making advanced analytics part of every engineer’s toolbox. Instead of relying on black-box tools, SmartWorks offers transparency and control. Engineers can train, validate, and deploy models themselves, keeping their domain knowledge at the centre of every prediction. This human-in-the-loop approach is a defining philosophy across Altair's offerings. AI supports creativity, accelerates exploration, and strengthens decision-making, but it’s the engineer who leads.

Geometric Deep Learning: Engineering’s New Ally

A compelling area of advancement is Geometric Deep Learning (GDL). Traditional machine learning is most effective with structured data, such as spreadsheets or image grids. However, engineering problems often involve complex 3D geometries such as meshes, surfaces, and point clouds, which GDL is specifically designed to handle. With GDL, engineers can build AI models that learn directly from CAD geometries and mesh data. Applications include stress prediction, crash analysis, fluid flow modelling, and structural optimisation, all executed significantly faster than traditional simulations. Altair’s work with PhysicsAI is pushing this frontier forward, allowing companies to simulate smarter and learn continuously from their geometry-driven design history.

Three Sessions You Shouldn’t Miss

Beyond keynotes, ATCx AI for Engineers 2025 features three in-depth technical sessions that offer actionable insights for different domains:

Simulation-Driven Design

This session explores how simulation has moved upstream in the development process. Engineers now use simulation not as a validation tool but as a real-time design driver. Presenters will share how meshless solvers, cloud-enabled simulation platforms, and integrated optimisation loops are unlocking rapid design exploration. Companies will demonstrate how they’re bringing new products to life with fewer physical prototypes and faster iterations.

Where Physics Meets AI

Here, Altair will showcase powerful hybrid approaches that combine classical physics solvers with data-driven AI models. The session features examples where AI has accelerated electromagnetic, thermal, and structural analysis without compromising reliability. Attendees will learn how to build and validate surrogate models, reduce simulation runtimes, and enhance overall design throughput. Emphasis is placed on keeping engineers informed while making workflows more scalable and intelligent.

Accelerating AI Adoption for Smart Manufacturing

Manufacturing is undergoing a major digital shift—and AI is at its core. This session explores how companies are utilising AI to implement predictive maintenance, defect detection, and real-time process optimisation. Altair’s experts will share frameworks for bridging the gap between IT and operations, overcoming challenges with legacy systems, and achieving early ROI. Live examples will show how manufacturers are embedding AI at the edge and on the shop floor to build truly adaptive systems.

To support a global audience, sessions will run in two time zones—APAC/EMEA and AMER/LATAM—and include live translations in eight languages: Spanish, French, Italian, Portuguese, German, Japanese, Chinese, and Korean.

Why ATCx AI for Engineers 2025 Matters

In today’s high-stakes engineering environment, access to cutting-edge tools isn’t enough. What matters is how quickly teams can turn those tools into solutions. That’s where events like ATCx become vital. They don’t just showcase technology. They offer a learning environment where strategy meets implementation.

The value of this event lies in its practical focus. Instead of abstract discussions, sessions are grounded in real business challenges—like reducing design cycle time, improving simulation coverage, and managing data across global teams. Whether you're a simulation analyst or a product innovation lead, you’ll come away with techniques and frameworks that apply immediately.

With a mix of case studies, product demonstrations, and strategic guidance, ATCx AI for Engineers 2025 provides participants with the knowledge and tools to start or scale their AI journey. The conversations will go beyond algorithms, to focus on the intersection of people, processes, and performance.

Whether you’re a hands-on design engineer, a digital transformation leader, or a systems architect, this event offers unmatched insight into the practical use of AI across engineering disciplines. The content isn’t theoretical, it’s built around real problems, proven results, and scalable solutions.

This is not a future vision, it’s happening now. And ATCx AI for Engineers 2025 is where you’ll see how.

Register now.

References

Topic

Manufacturing

Tags