Research

The group addresses software engineering research problems and challenges of industrial relevance and origin and has a strong basis in software engineering.

The research interests and activities of the group can best be described by the recent and ongoing projects and other activities. Below are some selected projects with pointers to further information. The list of all our projects is available in of the University.

The project investigates the impact of AI on software work and collaborates with companies to develop a vision for sustainable and human-centered software work. Solutions are sought for current challenges such as the skills shortage and workload management, as well as for long-term transformations. The project enhances participants' ability to anticipate, understand, and prepare for various futures, learn by experimenting with new work methods, and develop skills and competencies. Additionally, it provides guidelines for management, HR, and operational teams, and improves companies' ethical and responsibility competencies in the face of the AI revolution. The project supports employee well-being and motivation, encourages creativity and enthusiasm, and strengthens ethical and responsible productivity growth.

. Together with Reaktor, we are conducting a groundbreaking study to explore how generative AI tools affect software development productivity. While there has been a lot of talk about the productivity impact of genAI tools, we're here to provide the concrete evidence that matters.

About the Engineering Large Foundational Models () Project. The integration of Large Foundation Models (LFMs) and Generative AI into business, while expansive, introduces a wide array of risks and challenges due to costs, compliance issues, and technical complexities. The ELFMo project aims to address these challenges by providing a framework for effective integration, also enabling enterprises to navigate legal, security, and ethical concerns while aligning with European regulations. ELFMo empowers organizations to reliably integrate LFMs and Generative AI into their infrastructures and offerings, allowing them to maintain control over risks, challenges, and opportunities.

EM4QS (2024-26) Enhanced Middleware for Quantum Software (2025-26) is a joint project with the University of Jyväskylä funded by Business Finland. The project looks at the quantum stack. Our main focus is on transpiling – how to convert high-level quantum programs into a form that a specific hardware can efficiently execute it. WIth clever transpiling, the length of a quantum program can be dramatically reduced. Shorter programs are less sensitive to noise and thus give more reliable results.

FrameQ – Framework for analyzing the feasibility of quantum computing use cases (2023-24) project is a Business Finland funded project for developing a framework for analyzing the feasibility of quantum computing use cases. The work is done together with VTT. The main focus is on machine learning and optimization use cases. The existing quantum hardware limits the opportunities (too few qubits and too sensitive to interference) but the field is developing rapidly. The thinking behind our work is that once the hardware starts to be useful the bottleneck will be software and the ability to map real-life use cases to quantum. 

is funding two doctoral researchers working on quantum software. One of them focuses on quantum machine learning, and the other one on the efficient compilation of quantum programs. 

ESE is a part of the that aims to improve doctoral education in software engineering in Finland, aligning it with real-world industry and societal needs and promoting higher-level academic-industry collaboration. The network operates following the Finnish Acceleration of Scientific Talent (FAST) method. FAST aims at reducing graduation times to three years while maintaining high doctoral education standards and to facilitate thesis work done in close collaboration with non-academic partners to support doctoral students’ needs outside of academia. The FAST method is based on agile development principles, elaborated during the past two decades of software engineering research and built on the collaborative research model with continuous technology transfer.

– Next generation multiplatform Ocean observing technologies for research infrastructures is a Horizon Europe-funded project (2023–2027) that develops novel technologies to improve ocean observations. The technologies developed will represent the next level in systematic, long-term autonomous ocean observations. ESE's focus is on the easy-to-use online training platform, offering training for technical staff to enable them to operate seamlessly across research infrastructures.

Multimodal Fusion based Anomaly Detection for Improving Microservice-based System (MuFAno, 2023–2026): Understanding software behavior is important for modern software development, where software must evolve quickly without sacrificing reliability. At the end of the day, the users do not care if poor software service is due to operations (Ops) or development (Dev) failures, thus, both types of anomalies must be resolved quickly. Overall, our work aims for scientific breakthroughs enabling a path towards a fully automated software system monitoring and healing. This area will become even more important in the future as our lives and societies become ever more dependent on software-controlled services and devices. We collaborate with the software industry to ensure the ecological validity of our findings. Multiple academic partners also support our work. Funded by the Research Council of Finland, and .

(2023–2026): One of the main challenges of our times is the spread of misinformation on the Internet. Exposure to false information and poor critical reading skills may endanger citizens' decision-making on important issues. The project aims to ensure that educators have sufficient research-based knowledge and tools to educate adolescents to have sufficient critical reading skills required in the Internet era. The project increases understanding of the development of critical reading skills and factors affecting the development of these skills. The project aims to identify how to best support learning of critical reading at homes and schools. The project assesses adolescents' critical reading skills and develops tools, practices, and materials to support the development of these skills. The results inform the development of pre-and in-service teacher training. The Critical project aspires to prepare all adolescents to deal with misinformation on the Internet.

Emission free pulping () is a 5-year research program (2024–2028) that aims to significantly reduce biomass burning and increase the product yield from wood from approximately 50% to around 70%. The program is projected to have a budget of around 15 million euros over the next five years. In a Business Finland-financed project (2024–2026), which is a part of the program, on exploratory research on data sharing and artificial intelligence within the program. 

WELLS Research to Business (2023–2025). examine and promote well-being, working life skills and life-long learning. The research aims to explore the interrelationship between well-being and working/studying and how this interrelationship develops over time. We aim to recognize the potential groups who are likely to have problems and who are at higher risk of work or study-related burnout. The objective is to develop integrated interventions to help these groups and explore their effects and impact on participant well-being, work and study processes, as well as achievements. 

The activities in the area of empirical software engineering include the membership in  A recent paper in that collaboration: .

The group has strong background in knowledge-based configuration from its very beginning in 1990’s. See e.g., KBC wiki or our paper on from times when some of the group members worked at TKK, currently Aalto University.

Dr. Zafar Hussain completed his doctoral dissertation on topic

Dr. Lalli Myllyaho's thesis was on the topic  

Dr. Simo Mäkinen did his thesis on .

Dr. Hanna Mäenpää did her thesis in the group on the topic . 

Dr. Sezin Yaman graduated from the group with the thesis:

Assistant Professor Dr. Fabian Fagerholm did his PhD thesis in the group on the topic .

: Industrial Machine Learning for Enterprises (2021–2024): Smart software solutions, including AI and machine learning (ML), have shown a great potential to automate processes that were not accessible to automation. Since AI and ML differ from classical software development regarding fundamental activities and processes, it is unclear how AI and ML can be integrated into existing industrial-grade software development processes. Addressing the industrialisation of ML development and operations, the IML4E project will develop the IML4E framework, covering methods, techniques and tools dedicated to delivering and maintaining high-quality smart software in efficient, scalable and manageable processes. IML4E is a part of ITEA 4 that is the Eureka Cluster on software innovation. 

Industrial-grade Verification and Validation of Evolving Systems (, 2020–2024): The use of AI and complex, evolving systems (ES), i.e. systems that rapidly change, either due to fast iteration cycles in development or due to their capability to self-adapt and learn, will grow significantly in automation, computation and novel digital services. Targeting the challenges in verification and validation of AI and evolving systems, IVVES will systematically develop Artificial Intelligence approaches for robust and comprehensive, industrial-grade V&V of “embedded AI”, i.e. machine-learning for control of complex, mission-critical evolving systems and services covering the major industrial domains in Europe.

VesselAI Maritime Digitilization: (2021–2023) aimed at realising a holistic, beyond the state-of-the-art AI-empowered framework for decision-support models, data analytics and visualisations to building digital twins and maritime applications for a diverse set of cases with high impact, including simulating and predicting vessel behaviour and manoeuvring (including the human factor), ship energy design optimisation, autonomous shipping and fleet intelligence.

The Artificial Intelligence Governance and Auditing () focused (2020–2022) on the implementation of responsible and transparent algorithmic decision-making, particularly artificial intelligence (AI).

CACDAR (Creative and Adaptive Cooperation between Diverse Autonomous Robots) is a research project (2020–2022), funded by the Academy of Finland) which studies robust software engineering methods to develop flexible software for consumer robots. The focus is on novel software architecture design methods for cooperative robotics drawing from artificial intelligence (AI), emphasizing a subfield of AI called computational creativity.  We will use three advancing stages of development and evaluation (an abstract “block world” simulator, a 3D simulator and physical robots operating in real-world scenarios), identifying challenges and opportunities on each stage.

The Academy of Finland project ​Extreme​ ​Continuous​ ​Experimentation​ ​in​ ​Software​ ​Engineering​ ​(xCESE) (Sep 2018–Aug 2022).  Experimentation is a novel, data-oriented way of understanding users and develop software. Some companies already run running hundreds of experiments simultaneously or tens of thousands yearly. We aim at supporting the running of very high numbers of experiments with a theoretically rigorous basis for automating the experiment generation. Ultimately, the automation opens new avenues for creative experiment generators that can explore feature configurations unforeseen by human developers

The 4APIs project funded by Business Finland (Jun 2019–Jan 2021). The role of software and data becomes increasingly important for future competitive advantages. Application Programming Interfaces (API) and their utilization as a platform enabling technology are the keys in the transition from SaaS model to platform thinking. Succeeding in such new technological and business environments requires fundamental developments taking into account and shaping the new rules of the systems and players. In our vision, the key areas are API design principles, complex systems development competencies, and ecosystem creation and management capabilities.

The PEAMS (Platform Economy for Autonomous Mobile Machines Software Development) (Jun 2021 - Mar 2023) project, initiated by Business Finland, aims to research software solutions for intelligent machines. The current state of product development with custom software solutions is not as efficient and does not open new business opportunities. Therefore, one of the main objectives of PEAMS is to investigate whether these issues can be alleviated by transitioning to open-source software. Before proceeding with the actual transition, folks at the University of Helsinki will investigate what are the essential factors for the successful intelligent mobile machine platform and evaluate possible candidates based on the defined criteria.

dLearn.Helsinki is a collaboration with the researcher from the Faculty of Educational Sciences in the field of educational tools particularly for learning problem-solving and cooperation skills. The collaboration started  in , where . The collaboration has thereafter continued with a TUTL funding from Business Finland investigating the commercialisation potential of the ideas. The project succesfully lead to the founding of a spin-out company TeamFluent in 2020. 

– Intelligent Recommendation & Decision Technologies for community-driven requirements engineering was a three-year Eu Horizon 2020 RIA project started in the beginning of 2017 and ended 2019. See the .

was a national project in Finland funded by Tekes and coordinated by DIMECC. The group is participating in the project among the collaborative team from the University of Helsinki, including also the Networking group by Prof. Sasu Tarkoma and Security of Prof. Valtteri Niemi.  

An exciting collaboration with the Discovery research group lead by Prof. Hannu Toivonen for the new research area in the intersection between computational creativity and self-adaptive software, with the goal of developing novel software architectures that can creatively adapt themselves in unforeseen situations. The collaboration was concretely carried out in a CACS (Cooperation-Aware Software and Creative Self-Adaptivity) project funded by Academy of Finland (2018–19). See our paper on this: 

In the the group has been working on the software engineering paradigm called continuous experimentation in which data from real usage of software is collected and analysed for decision-making in software development. See, CE Cookbook (), or .

that investigated Dynamic Distributed Software Development Competencies. See also:

The group was also active in Cloud Software Programme was a large national programme funded by Tekes (from 2010–2013) and the related FidiPro (Finnish Distinguished Professorship) of Prof. Jürgen Münch in the topic Cloud Software Factory. These initiatives concentrated on utilisation of Cloud infrastructure and transition to Agile software development practices.