IDLab: Fascinating Research, Tough Deadlines, and Academic Drive

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The International Laboratory of Intangible-driven Economy (IDLab) was established at the HSE campus in Perm 11 years ago. Its expertise in data processing and analysis allows researchers to combine fundamental studies with applied projects, including the development of risk and cybersecurity models for Sber. The head of the laboratory, Professor Petr Parshakov, and Senior Research Fellow Professor Mariya Molodchik spoke to the HSE News Service about IDLab’s work.

— When was the laboratory created?

Mariya Molodchik

Mariya Molodchik: In 2014. The idea came from Elena Shakina, who now works with us remotely. Professor Ángel Barajas from the University of Vigo (Spain), a visiting professor at the HSE campus in Perm since 2010, played a crucial role in shaping the laboratory. He regularly travelled to Perm, delivering lectures on business valuation and actively supporting our research on the role of intellectual resources in creating business value. Before 2014, we were engaged in other HSE-funded projects like Centre—Branches, Research and Study Group, and Teacher—Students. All of this helped us prepare for launching the laboratory.

A distinctive feature of our application for international laboratory status was that we invited not one professor, as the competition required, but four

Ángel Barajas encouraged his colleagues to join: Professor Dennis Coates from UMBC (USA), Professor Felix J. Lopez Iturriaga from the University of Valladolid (Spain), and Professor Carlos Jardón from the University of Vigo (Spain). As a result, the laboratory was enriched by the knowledge and expertise of four renowned international academics with strong publication records. This became a key point of growth for us. It brought intellectual and emotional drive—without which the laboratory could not have come together. I should also note that the Perm team and the international professors shared the same values: a commitment to creating new knowledge, seeking unconventional solutions, maintaining absolute integrity in econometric assessments, providing detailed theoretical justifications for our hypotheses, and using the latest tools for collecting, processing, and analysing data. We were fortunate to build a team whose members were aligned in their values.

Our professors were excellent mentors. They readily shared their knowledge, visited Perm, and spent a great deal of time with us. We are grateful to HSE for its grant support, without which intensive academic mobility would not have been possible—for instance, attending conferences across Russia and presenting at specialised conferences abroad. Today, we continue to collaborate with them as co-authors of academic papers.

Petr Parshakov

Petr Parshakov: It is important to understand that establishing a research unit in Perm 11 years ago was considerably more difficult than it would be today. The enthusiasm of the laboratory’s founders undoubtedly played a decisive role. It is also essential to acknowledge the active support of the Perm campus administration in addressing administrative and organisational matters.

— Your laboratory studies intangible assets. What does this concept encompass?

Mariya Molodchik: Firstly, human capital. Secondly, everything pertaining to relationships and collaboration, both within a team and with external partners. The third component is structural capital, which reflects how business processes are organised and new knowledge is created.

— Your key research areas include the technological transformation of companies, the intellectual capital of individuals, groups, and organisations, as well as sports and esports as a laboratory for behavioural economics. What connects these diverse topics?

Mariya Molodchik: Our team is now quite large, and we work within an umbrella framework. All our topics are united by the common thread of intangible assets. For example, technological transformation relates to structural capital, as it improves business processes. Intellectual capital can be examined at different levels, while sport serves as a testing ground where we can validate various hypotheses—including those concerning intellectual resources.

— The laboratory has carried out a series of applied projects. Which would you consider the most significant?

Mariya Molodchik: We began in 2014 with fundamental research; applied projects emerged later.

Petr Parshakov: Despite the diversity of the laboratory’s research areas, one of our main competencies is data processing and analysis. Many projects lie at the intersection of economics, management, and data analytics.

Our fundamental work strengthened our data-analysis capabilities, which later proved essential for applied tasks

Many applied projects are carried out jointly with the Laboratory for Labour Market Studies, headed by Sergey Roshchin, as human capital is of interest to both units. Together, we have completed projects for Rostrud and developed tools like the Navigator of Professions and Skills and Pythia. We also have joint applied projects with the HSE AI Research Centre and co-developed risk and cybersecurity models for Sber.

We have now reached a point where we can effectively combine fundamental science with applied research, which ensures our stability as a research unit.

Mariya Molodchik: The two most recent grants we received from the Russian Science Foundation focus on using artificial intelligence to assess workplace burnout and employing large language models to simulate economic behaviour.

The ideas for these grant applications grew directly out of our applied projects. This demonstrates a two-way spillover effect, where ideas and approaches flow from fundamental research into applied work and back again.

— Which HSE units do you collaborate with?

Mariya Molodchik: One of our distinguishing features is our extensive collaboration across the university. In addition to the Laboratory for Labour Market Studies, we work with Dmitry Dagaev’s Laboratory for Sports Studies on sports economics. In Moscow, we actively collaborate with the School of Finance led by Irina Ivashkovskaya. We also work closely with the Institute for Statistical Studies and Economics of Knowledge (ISSEK) on digitalisation research. At the Perm campus, we conduct joint studies with the Centre for Cognitive Neuroscience, and in St Petersburg, with the Department of Management under Maxim Storchevoy. We have many such partnerships, as our research is inherently interdisciplinary.

— Among your projects, the skills navigator stands out. What tasks does it help solve?

Petr Parshakov: I would describe the navigator as a tool that reveals how employers perceive employee competencies. The advantage of our project is that, together with our colleagues from the Laboratory for Labour Market Studies, we started from labour market data. This is more objective than having a panel of experts define roles like IT specialist, engineer, or driver. When an employer lists the required competencies for a particular occupation, it allows us to track dynamics—such as the emergence of new skills. It also facilitates the study of new frameworks and libraries.

— Another interesting project is your analytics on graduate employment using artificial intelligence.

Petr Parshakov: This is another case where we, together with the Laboratory for Labour Market Studies, started from data to build a model that predicts career trajectories—where graduates might work and how much they are likely to earn. This is the foundation of Pythia, a new resource for applicants that provides information previously unavailable in student advisory services.

It can be used during the university admissions process to show prospective students likely career paths, the demand for their chosen professions, and potential salaries.

— To what extent does artificial intelligence help you process and analyse large volumes of data? How long did it take to train AI for the laboratory’s tasks?

Petr Parshakov: Data processing and analysis have always been a core strength of our team. It is an area we wanted to develop further—we attended summer schools and still consider it a key priority for strengthening our competencies. If you are skilled at working with data, you can answer a wide variety of research questions. We use AI models in academic research to analyse texts and leverage them for practical projects, as companies’ websites and reports contain vast amounts of unstructured data. We do not have a single universal model; instead, we create and train a new model for every task. The one that took the longest to train was the large language model designed to give users clear insights into their future study and career paths.

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— How does the laboratory manage to combine practice-oriented projects with active academic work and publications in high-ranking domestic and international journals?

Mariya Molodchik: It is no coincidence that we submitted a grant application on burnout—juggling multiple lines of work is not easy.

Petr Parshakov: We have a great team. New people join projects, and from the beginning, when Mariya Molodchik and Elena Shakina founded the laboratory, they set the right professional tone. We understood the importance of fulfilling our commitments and continue to uphold their values. This is possible partly thanks to our data-analysis competencies, which are in demand for both fundamental and applied projects. Moreover, we see a clear synergy: we use the results of fundamental research in applied projects, and vice versa.

We also use outsourcing, hiring external developers, many of whom are HSE graduates.

— Tell us about your cooperation with the Iran University of Science and Technology. What are the main areas of joint research?

Mariya Molodchik: We have been working with our Iranian colleagues since 2020, when they first contacted us. They also work in the field of intellectual capital and became interested in an article we co-authored with Carlos Jardón in an international journal.

This year, we applied for the International Academic Cooperation project and successfully passed the competitive selection. On our side, the project involves 20 participants: 12 are staff members of our laboratory, and another eight were specially invited to carry out project tasks. The project is designed to actively involve students—undergraduates, Master’s students, and doctoral students—who make up half of the Russian participants. Five researchers from the Iran University of Science and Technology are also taking part.

In terms of research competencies, the Russian and Iranian teams complement each other. IDLab excels in working with open data and advanced econometric analysis. Our Iranian colleagues, in turn, have strong expertise in case-study methods and preparing applied analytical materials for government bodies, particularly on stimulating non-resource exports.

We have already held a joint seminar in the short time since the project launched. Furthermore, at the end of October, the international iCARE 2025 conference and a seminar for early-career researchers on preparing literature reviews were successfully held.

— How are the laboratory’s research results applied in the educational process?

Mariya Molodchik: They are applied continuously, as our staff teach at all levels. For example, I teach Microeconomics to first-year students and, when covering production theory, I use our research on enterprise digitalisation. Petr Parshakov teaches Data Analysis and uses data from Russian companies to demonstrate factors that increase competitiveness. Overall, all laboratory members are actively involved in teaching.

— How actively do you recruit young staff, senior students, and doctoral students?

Mariya Molodchik: Around 90% of our staff are under 39. Every year, we take on between three and seven interns, giving students the opportunity to work on real projects with interesting research tasks, strict deadlines, and genuine academic drive. We actively recruit young people: we currently have seven Bachelor’s students, five Master’s students, and two doctoral students working with us. Last year we joined the unified Master’s–Doctoral track; three of our staff members are enrolled, and another doctoral student was admitted to the academic programme this year.

Petr Parshakov: Our students have excellent academic supervisors and regularly win research competitions. Many have continued their studies at top universities in Russia and abroad.

IDLab and the Iran University of Science and Technology (IUST) have launched a series of educational seminars for early-career researchers. On October 31, 2025, the first seminar of this new cycle was held. The series aims to help young researchers develop the skills needed to prepare and publish academic articles. The first seminar focused on literature reviews—both traditional methods and those based on artificial intelligence. The event was held as part of the HSE’s International Academic Cooperation project and brought together around 30 doctoral students and students from Russia and Iran. More details are available via the link.