Perimeter researcher turns CEO

Aida Ahmadzadegan-Shapiro, CEO and founder of quantum AI company ForeQast, started her physics journey with a fascination for the cosmos. Her early love of astronomy evolved into a passion for theoretical physics, eventually leading her to specialize in quantum information and machine learning. She was soon working at the forefront of quantum-AI integration during her postdoctoral research with Roger Melko, Research Associate Faculty and founder of the Perimeter Institute Quantum Intelligence Lab (PIQuIL).

Ahmadzadegan-Shapiro's research focused on quantum optimization and hybrid AI algorithms. As she pushed the boundaries of fundamental research, she started seeing a powerful opportunity: to take the tools of quantum science out of the lab and apply them to some of industry’s most complex problems. In 2021, she co-founded ForeQast Technologies and began building AI and quantum-inspired solutions for critical challenges in supply chain and operations planning.

Perimeter caught up with Ahmadzadegan-Shapiro to learn more about her shift from research to entrepreneurship, and how her training as a physicist prepared her for the fast-paced, ever-changing world of business.

This interview has been lightly edited for clarity and length.

What was it like making the first jump from academia to industry?

It was a leap into the unknown. I had spent years building mathematical models and writing code for problems most people don’t even know exist. But I started to feel that these tools, especially quantum optimization, had real potential outside of academic papers. I met my co-founders and we decided to test that hypothesis.

We iterated fast. Every few months, we were building prototypes, talking to users, pivoting, trying to find where this technology could make the biggest impact. Eventually, we landed on supply chain disruptions, one of the most complex and under-optimized problems in the real world.

What are the problems your technology helps solve?

Say you have hundreds of packages and dozens of delivery windows: that’s an optimization nightmare. Our engine can reduce miles traveled, improve delivery time predictions, and ultimately cut costs.

Later, we expanded into sales and operations planning, helping companies make smarter decisions about what to stock, when to reorder, how much to buy. That kind of inventory forecasting is full of uncertainty, and it’s where AI and optimization together can really shine.

How do you use AI and quantum computing to improve supply chain performance?

We combine classical AI and quantum-inspired methods. AI helps extract structure from messy, real-world data such as customer emails, historical sales patterns, even weather events. Quantum optimization enters when we need to solve hard decision problems under constraints. It’s not about replacing classical tools but about using the right engine for the right part of the problem.

Our customers don’t care if it’s quantum or classical. They care about better decisions, faster. That’s what we deliver. Most of what we deploy today runs on classical infrastructure, but we design our algorithms with quantum in mind. As hardware improves, we’re ready. Our approach is about solving real problems now, while being architecturally future proof.

What were the challenges in launching a startup?

One of the hardest parts was communicating value, not just technology. In research, the work speaks for itself. In business, no one cares how elegant your algorithm is unless it directly solves their problem. We had to learn to translate complexity into clarity, and focus relentlessly on outcomes: cost savings, time reductions, forecast accuracy.

We also faced the classic deep-tech challenge of building something before the market fully understands it. That meant we had to educate while executing. It’s a tough balance but it pushed us to be extremely customer-focused and that ultimately made our product better.

How did research help prepare you for running a startup?

Research taught me how to live with uncertainty. In quantum physics, you often work for months on a problem without knowing if a solution exists. That ability to persist, to experiment, fail, and revise, is essential in entrepreneurship.

But research also gave me depth. When you’ve spent years building algorithms from scratch, you can navigate complexity with confidence. That becomes a real strategic advantage. You’re not just repeating what others have done. You’re creating new intellectual property, new methods, new ways of thinking. That foundation let me lead from both the technical and strategic sides of the business.

What are some non-academic skills that have helped you succeed as a startup?

I found I had a strong instinct for storytelling, for helping people see the bigger picture. Early on, I was the CTO, but I naturally gravitated toward customer conversations, investor pitches, and product strategy. I loved connecting the dots between a technical insight and a market need. Eventually, I stepped into the CEO role.

That transition wasn’t just about title. It was about learning how to build a company, not just a product. Fundraising, team building, market analysis, sales. I had to learn fast, but physics gave me the tools to do that: structure, focus, and the ability to break down complex systems into tractable pieces.

What are you excited about in the field of AI and quantum technology?

I think we’re just scratching the surface of what’s possible. AI has matured rapidly and we’re now seeing it handle unstructured data and decision-making with increasing sophistication. Quantum, especially quantum optimization, is on a slower hardware trajectory, but the theoretical groundwork is strong and investment is catching up.

What excites me most is the convergence: using AI to extract meaning from data and quantum-inspired algorithms to act on that meaning in constrained, high-stakes environments. I see a future where these tools are embedded into systems we use every day — powering not just tech companies, but supply chains, hospitals, cities. That’s the kind of transformation I want to help drive.