On 23 June 2026 the European Research Council announced its Advanced Grants round. According to BTA, 3,329 proposals competed and about 9% were funded: 319 researchers shared 838 million euros. Dr. Bernhard Haeupler of INSAIT received one of those grants, worth 2.5 million euros, for research into new algorithms and mathematical tools for optimising large networks (transport, logistics and internet networks).
INSAIT describes the award as Bulgaria's first-ever ERC grant in natural sciences and engineering. Dr. Haeupler joined INSAIT in 2024; INSAIT says he previously worked at MIT, Carnegie Mellon University and Google Research. INSAIT is an institute of Sofia University "St. Kliment Ohridski", launched in April 2022 in partnership with ETH Zurich and EPFL, with Prof. Martin Vechev as its founder and scientific director. Prof. Vechev and Dr. Haeupler were both featured in a NOVA TV report about INSAIT and the role of fundamental research.
A grant like this is a signal. A strong one, but a signal, not an ecosystem on its own. The distinction matters for anyone making hiring or investment decisions based on where talent is heading.
Fundamental research does three things companies cannot easily buy on the open market. It brings researchers of international standing to a country, people whose presence raises the bar for everyone around them. It trains the next cohort of engineers and scientists, the people that companies later hire. And it makes a location credible to partners abroad, including in the DACH region, where many of the companies that work with Bulgarian engineering teams are based.
That credibility compounds slowly. One grant will not by itself convince a company abroad to build a team in Sofia. A pattern of internationally recognised work, sustained over years, changes the calculation. It takes sustained investment: from the state, from universities, and from companies willing to work with research institutions rather than only hire their graduates.
At KONDEVS we build enterprise integration, BPM and AI systems for clients in the DACH region and beyond, from Bulgaria. So when we read about new algorithms for optimising large networks, we think about the path those algorithms would have to travel before they could run inside a business process.
That path is rarely short. A promising method becomes useful to a business only through engineering: integration with the systems that hold the data, process design that decides where and when a model acts, and governance that keeps everything auditable and accountable in production. The algorithm is the starting point. The integration layer, the orchestration logic, the exception handling, the observability and the ownership model are where the delivery work lives.
Network optimisation is not an abstract academic topic. It shows up in logistics routing, supply chain planning and infrastructure capacity management. But production constraints (data access, system integration, policy enforcement, operational accountability) can dominate delivery risk even when the underlying algorithm is sound. Research and production work need each other. Research expands the methods and trains people in rigorous thinking. Production forces clarity about constraints, reliability and what "good enough" means under load.
Three plain suggestions for technology leaders watching this space:
- Follow the research that is relevant to your problems. Network and process optimisation is a business problem too. If you run logistics, transport or internet-scale platforms, the work coming out of institutions like INSAIT may eventually matter to your operations.
- Treat local research talent as a reason to build teams here. The presence of internationally recognised researchers changes the hiring pool over time. If you already work with Bulgarian engineering teams, or are considering it, factor the research ecosystem into your location decision: not as hype, but as one serious input among several.
- Plan the engineering path from method to production system. Do not wait for a finished product to drop out of a lab. Think now about the integration, process design and governance work that would be needed to put a new optimisation method to work inside your existing systems.
What will determine whether this grant becomes part of a larger story is what happens next: whether the investment continues, whether companies engage with the research rather than only applaud it, and whether the engineering work that connects new methods to real systems gets the attention it deserves. The algorithm is the beginning; making it accountable, observable and operational inside the processes that run a business is the work that follows.
Congratulations to Dr. Haeupler, Prof. Vechev and the INSAIT team on an achievement that raises the profile of Bulgarian research on the European stage. KONDEVS helps companies turn AI into production systems inside their processes; if that is the problem you are working on, we would welcome the conversation.
