Dr. Zsolt Szalay, electrical engineer and economist, Associate Professor, has been awarded one of Hungary’s most prestigious professional recognitions in innovation and technical sciences, the Jedlik Ányos Prize. Each year, the award is granted to only five professionals whose work makes an outstanding contribution to inventive activity, the practical utilization of innovation, and the conscious protection and cultivation of intellectual property.

The prize is conferred by the Hungarian Intellectual Property Office and is traditionally presented in connection with the national holiday of March 15. Named after Ányos Jedlik — Benedictine monk, physicist, and inventor — the award reflects a philosophy that sees the true value of science in its ability to create new solutions and serve societal progress.

This year, Zsolt Szalay received the prize alongside distinguished figures such as Balázs Gulyás, President of the HUN-REN Hungarian Research Network; Gábor Bayer, Director of Development at 77 Elektronika Ltd.; Dr. Péter Lábody, Vice President of the Hungarian Intellectual Property Office; and Nobel Prize–winning physicist Ferenc Krausz. The diversity of the laureates clearly demonstrates that the Jedlik Ányos Prize recognizes socially impactful achievements across science, industry, and innovation alike.

Over the course of several decades as a researcher and educator, Dr. Szalay has achieved defining results in the fields of autonomous vehicles, automotive innovation, and industry collaboration. His work builds a bridge between academic research, industrial development, and practical application — precisely in the domain where scientific results evolve into tangible innovation and economic value.

On the occasion of the award, we spoke with him about his professional journey, motivation, responsibility, and what it means today to be an inventor in a rapidly transforming technological era.

The Jedlik Ányos Prize simultaneously recognizes inventive thinking and the conscious management of intellectual property. Which aspect feels closer to you — the moment of creation, or the systemic protection and utilization of what is created?

For me, the two cannot truly be separated. As an engineer, the moment of creation is naturally the strongest source of motivation: when a theoretical idea becomes a functioning system, when a student project or research concept evolves into real technology. That is the point at which innovation becomes a personal experience.

At the same time, in recent years it has become increasingly clear to me that scientific research alone is no longer sufficient. If a result does not find its way into industry, if intellectual property is not managed consciously, it often cannot generate real impact on the economy or society. In a university environment in particular, it is crucial to teach young engineers that innovation does not end in the laboratory — in fact, that is where it truly begins.

Today, I would phrase it this way: creation provides the inspiration, but utilization gives it meaning.

Was there a defining professional moment or decision in your career that, in light of this award, you now see as a turning point?

Yes, there were several, but perhaps the most decisive was when we began to treat autonomous vehicle research not merely as a scientific question, but as part of a broader ecosystem. It was the moment when it became clear that the role of a university is not limited to producing publications, but also includes shaping a development environment together with industry.

This recognition led us to stop treating education, research activities, and industrial collaborations as separate domains. Instead, we began organizing them as an integrated system of mutually reinforcing functions. Autonomous vehicle technology clearly demonstrated the necessity of this approach: in this field, vehicle dynamics, perception and decision-making algorithms, software architecture, and safety and compliance requirements all form parts of a single complex system. At a certain point, it became evident that their development could no longer be separated into distinct educational, research, and innovation tasks — what was required was a consciously built, ecosystem-like mode of operation.

Looking back, this was the turning point that defined the professional direction of the past decade.

Does such recognition close a chapter, or does it rather bring new expectations and responsibility?

For me, it clearly signifies a strengthening of responsibility. In engineering and academic careers, there are rarely true closures, because every result opens new questions. A professional award of this kind is primarily a confirmation that the direction represented so far — the close integration of university, industry, and innovation — may have been the right one.

At the same time, it also means that even greater attention must be devoted to the next generation. True impact is not measured in individual developments, but in how many engineers leave the university capable of creating new systems and thinking responsibly about the societal implications of technology.

On a personal level, this recognition reminds me that the ultimate goal of innovation is not technology itself, but the future we build with it. It was reassuring to see and hear at the award ceremony that the other laureates, regardless of discipline, share this same principle.

For this reason, I consider the work and mission of the Hungarian Intellectual Property Office — celebrating its 130th anniversary this year — particularly important. The Office does not merely provide legal frameworks; it actively contributes to ensuring that research results translate into industrial and societal utilization. It is evident that they think in 21st-century terms: their focus lies not only on protection, but also on fostering development and promoting the responsible use of knowledge — in alignment with the forward-looking spirit that already guided its foundation 130 years ago.

In the world of autonomous vehicles, an “invention” is often not a single device but the cooperation of complex systems. What does it mean today to be an inventor in an era of system-level innovation?

For a long time, the classical image of the inventor was associated with a single device or mechanical solution. In the world of autonomous vehicles, however, true novelty almost never resides in an individual component, but rather in the way different systems operate together. Sensors, artificial intelligence, vehicle dynamics, communication infrastructure, and safety architectures form a unified whole.

To be an inventor today therefore primarily means to think at the system level. The question is not how novel a component is in isolation, but whether it can create a new operational logic within a complex system. In many cases, the greatest innovation emerges at the interfaces, in the mode of integration, or in the structure of decision-making.

This type of work is fundamentally team-based. Such systems can only be realized through collaboration across multiple disciplines, which is why I always regard this mindset as a shared achievement. I am grateful to the colleagues and collaborators with whom these solutions were developed, and it is important to me that they also feel this recognition as their own.

At the same time, this requires a shift in perspective: an engineer must not only understand their own field in depth but also grasp how their work affects other disciplines and how boundary areas connect. Success often depends on one’s ability to perceive and interpret the interactions across these domains in a comprehensive manner. The modern inventor is, in essence, a system architect.

When does an engineer know that an idea is truly novel, rather than simply an improvement of an existing solution?

This is rarely the result of a single moment of realization. True novelty usually begins to reveal itself when a problem becomes simpler or more robust to solve — while at the same time opening up new questions. If a solution merely optimizes, it typically remains within the existing framework. Genuine novelty, however, often reshapes the framework of thinking itself.

From an engineering perspective, it is often a good sign when an idea initially feels “uncomfortable” — when it does not fully align with established models or development logic. Many innovations are difficult to recognize at first precisely because they are not obviously superior along familiar metrics; instead, they approach the problem from a fundamentally different angle.

The real validation usually arrives when other professionals begin applying the same approach. When an idea becomes reproducible and capable of being further developed by others, it crosses the threshold from improvement to true novelty.

Early in your career, you worked as an industrial development engineer, giving you first-hand experience in both academic and industrial environments. How did this dual perspective shape your research mindset?

Indeed, for me the industrial and academic perspectives did not follow one another sequentially; they were present in parallel from the very beginning. During my years as a development engineer, I learned very early on that every technical decision has concrete consequences — in cost, reliability, manufacturability, and above all, safety. This sense of responsibility has fundamentally shaped the way I approach research questions ever since.

When I transitioned into academia, it was already natural for me to view real-world applicability as the ultimate benchmark of engineering work. As a result, even in research, I consistently sought ways in which theoretical results could evolve into functioning systems. In the field of autonomous vehicles, this is particularly important: we are not developing demonstration prototypes, but technologies that must perform reliably in complex, real-world environments.

This dual experience helped me avoid seeing industry and academia as two separate worlds. Instead, I regard them as two necessary phases of a single innovation process: the university can open new directions and pose riskier questions, while industry provides feedback on which of these can become sustainably functioning solutions. For me, ideal research emerges where these two perspectives remain in continuous dialogue.

You often emphasize the practical utilization of research. At what point does a scientific result become “real innovation”?

Perhaps at the point when a result leaves the controlled environment of research and others can use it without the continuous presence of its creators. Scientific success is often measured by a deeper understanding of a problem; innovation, however, is born when a solution takes on a life of its own.

This boundary is often subtle: the question is no longer whether something works, but whether it is reproducible, scalable, and capable of creating long-term value. Genuine innovation also requires that a solution be integrable into existing processes — whether industrial or societal.

Many research results are technologically excellent, yet never become innovations because the usage context in which they would gain meaning fails to emerge. For me, therefore, innovation is not an event, but a transition: knowledge becoming operational practice.

In 1997, you founded Inventure Automotive, whose vehicle-data-based telematics solutions now operate in more than one million vehicles worldwide. What did entrepreneurship teach you about innovation that you might have perceived differently as a researcher?

Founding Inventure Automotive was a unique learning process for me, because it allowed me to experience directly how a technical idea becomes a real product. In research, it is often sufficient to prove that a solution works; in an entrepreneurial environment, the real question is whether it works sustainably across different countries, vehicle platforms, and usage contexts.

During the development of telematics systems, we quickly realized that technological success alone is not enough. Reliability, scalability, and the ability to create continuous value — often invisibly to the user — are equally important. When a solution operates in hundreds of thousands or millions of vehicles, every minor engineering decision is multiplied in its impact.

This experience later had a profound influence on my research work as well. I began looking at developments differently: not only asking whether something is technologically feasible, but also whether it can evolve into a system that is sustainable from a business perspective in the long term. Perhaps this is one of the most important lessons: the true test of innovation is time and scale.

What did you learn from industrial collaborations that you likely would not have experienced in a purely academic setting?

Perhaps the most important realization was that a significant proportion of engineering decisions are not purely technical. In real-world development, continuous trade-offs must be made among competing considerations: performance, cost, development time, risk, and regulatory compliance.

Industry also very quickly reveals whether a solution addresses a real problem. A technology may be highly sophisticated from an engineering standpoint, but if there is no genuine user demand behind it — if the use case is not authentic — it will not become innovation. This form of reality check fundamentally shapes one’s thinking.

In academia, we naturally seek the best technical solution. In industry, however, the right decision is often the one that represents the most balanced compromise under given circumstances — technically, economically, and from the user’s perspective alike. This teaches that innovation is not only creativity, but also responsible prioritization.

This mindset has become equally important in education for me: engineering students must not only solve problems, but also make decisions under uncertainty, while considering whether their solutions are capable of generating real impact.

One recurring question in Hungarian innovation concerns market entry. Where do you see the greatest obstacle today: technology, mindset, or ecosystem?

I increasingly believe that technology itself is no longer the primary bottleneck. In Hungary, high-level technical expertise and competitive research results are often present. The real challenge lies in the fact that the various actors of innovation — researchers, companies, investors, and regulators — operate on different time horizons.

Research accepts long-term uncertainty, while the market expects results that can be evaluated quickly. When these timeframes fail to align, many promising developments remain in an intermediate phase: technologically validated, yet lacking the maturity and business environment necessary for market introduction.

For this reason, I would describe it primarily as an ecosystem issue. Successful innovation requires not only good ideas, but also an environment capable of accompanying a technology from early-stage research through to market deployment. Creating this continuity is perhaps the most important task today.

What sustains your curiosity over the long term in a field where technology seems to reinvent itself almost every year?

Precisely this continuous transformation. In the field of autonomous systems, one can rarely feel “finished” for long — a new technological direction, a novel methodology, or an unexpected question always emerges, prompting a reconsideration of earlier answers. For me, this represents not uncertainty, but intellectual freedom.

Curiosity is sustained by the fact that behind technological progress lie fundamentally human questions: How can we trust a machine’s decision? How can automated systems be made safe? How does the role of mobility evolve within society? These questions do not become obsolete from one year to the next; they simply appear in new forms.

Thus, motivation is not tied to a specific technology, but to the ongoing learning process in which every new development also offers a new opportunity for deeper understanding.

As a researcher, department head, and educator, you operate in different roles. Which provides the most personal feedback?

Each role offers a different type of feedback, and perhaps that is precisely why they complement one another. As a researcher, one rarely receives immediate validation — years may pass before the true significance of a result becomes visible. As a department head, success is more indirect: it becomes tangible when a team begins to function autonomously or when younger colleagues establish their own direction.

The most immediate feedback comes from teaching. During a lecture or collaborative project, it becomes evident very quickly whether an idea resonates with students. When a complex technical relationship suddenly becomes clear to them, the feedback is immediate and genuine.

I have always sought to work as a mentor-type educator: not merely transmitting knowledge, but helping students discover problems independently and find their own paths to solutions. This approach allows education to become more than information transfer; it becomes the development of thinking and problem-solving capability. That is why I see teaching as a stable reference point alongside research and leadership work, which often operate in much longer cycles.

Was there ever a moment with a student or young researcher when you felt, “This is why it is worth doing”?

Yes — and interestingly, these moments are not necessarily tied to spectacular successes. Rather, they occur when a student or young researcher crosses a conceptual threshold — when they move beyond simply solving a task and begin to see behind the problem, formulating their own questions.

I vividly recall situations where, at the end of a project, someone did not say, “We are finished,” but instead asked, “What if we tried approaching this in a completely different way?” That is when independent engineering thinking begins to take shape.

For me, these moments provide the strongest affirmation, because they make visible that knowledge is not merely transferred — it continues to live and evolve in the work of the next generation.

In your view, what skills distinguish future innovators from good engineers?

A good engineer can precisely solve a well-defined problem. A future innovator, however, often plays a role in defining the problem itself. Today, the primary constraint is increasingly not access to information or technological tools, but the ability to recognize which questions are worth solving in the first place.

Beyond classical technical expertise, three capabilities are becoming decisive: recognizing interconnections between systems, collaborating effectively across disciplines, and managing uncertainty. An innovator does not necessarily know more within a single domain, but is capable of building bridges between different modes of thinking.

Perhaps this is the most fundamental distinction: while the engineer primarily provides answers, the innovator dares to ask new questions.

If Ányos Jedlik were alive today, which technological question do you think would most capture his interest?

What I find most fascinating about Jedlik’s work is that he was not merely interested in an invention itself, but in the phenomenon underlying it. If he were alive today, he would likely be drawn to fields where fundamental physical or engineering principles appear in new application contexts.

I believe he would be particularly interested in the relationship between energy and intelligent systems — for example, electric mobility, energy storage, or the physical and information-theoretical foundations of autonomous systems. These technologies simultaneously embody experimental engineering thinking and fundamental scientific curiosity, both of which characterized his work.

He would probably not focus on a single device, but rather on the broader question of how the physical world and information processing are becoming ever more tightly interconnected.

What would you say to young researchers who do not yet see how their work might achieve genuine societal or industrial impact?

I would tell them that this is a completely natural state. Most significant research results do not initially appear applicable, and it may take years or even decades for them to find their place. Impact rarely develops in a linear fashion.

It is important to understand that a researcher’s first responsibility is not necessarily to ensure immediate application, but to formulate the question precisely and to develop a deep understanding of the phenomenon. Real value often lies in generating a new perspective that others can later build upon.

For this reason, it is worth remaining open to collaborations and unexpected connections. Many innovations are not realized where they originally began, but where different modes of thinking intersect. One of the most rewarding aspects of a research career is that one often only later recognizes how far an earlier idea has ultimately traveled.