Jara Uitto is an Assistant Professor in the Department of Computer Science. His research focuses on Massively Parallel Computation, Distributed Computing, and Sublinear Computing, with a particular emphasis on graph algorithms and distributed systems. Research Interests: Massively Parallel Computation (MPC) Distributed Algorithms and Symmetry Breaking Graph Theory and Edge Processing Algorithm Design for Sparse Graphs Approximation and Optimization in Streaming Models Key Project: Massively Parallel Algorithms for Large-Scale Graph Problems (2020-2024) , where he led research on optimizing algorithms for distributed and parallel computing environments. Publications highlight contributions to symmetry breaking, parallel coloring, and approximation algorithms in dynamic streams. His work bridges theoretical foundations with practical distributed computing challenges.
Elina Mainela-Arnold is a Professor and Head of the Department of Psychology and Speech-Language Pathology at the University of Turku, Finland. She earned her Ph.D. in Communicative Disorders and Psychology from the University of Wisconsin-Madison and her Master’s in Speech-Language Pathology from the University of Helsinki. She previously served as an assistant professor at Penn State University and the University of Toronto. Research Interests: Her research investigates domain-general cognitive mechanisms in language acquisition, focusing on individual differences in children with typical development and those with Developmental Language Disorder (DLD). She explores bilingualism, cognitive processing, and neurocognitive underpinnings of language learning. Her work informs both theoretical models and clinical practice. Recent Research Trends: Her recent publications highlight auditory processing, procedural learning, intra-individual variability, and non-linguistic cognitive predictors in language development. She uses ERP, longitudinal cohort data (e.g., FinnBrain), and cross-linguistic designs to examine language outcomes in monolingual and bilingual children. Scientific Awards and Recognition: Contributor to the CATALISE international consensus panel (2016–2017), which established evidence-based diagnostic criteria for childhood language impairments. Her research influenced the adoption of the term Developmental Language Disorder in the ICD-11. Advising and Grants: She mentors Bachelor’s, Master’s, and Doctoral thesis students. While specific grant details are not listed, her involvement in large-scale studies like FinnBrain and international collaborations indicates active grant-funded research. She teaches courses such as Language Across the Lifespan, Bilingualism, and Cognitive Processes. Labs and Teams: She is affiliated with the FinnBrain Birth Cohort Study and the InterLearn research group, engaging in interdisciplinary research at the intersection of psychology, neuroscience, and speech-language pathology.
Outi Sarpila is a Professor of Sociology at the University of Turku, Faculty of Social Sciences. She is actively engaged in research, teaching, and academic leadership, with a focus on the sociology of physical appearance, consumption, and social inequality. Her work is supported by major Finnish research funders, including the Academy of Finland and the Emil Aaltonen Foundation. Her research interests include the sociology of physical appearance , beauty-based social inequality , consumption practices , and survey methodology . She investigates how physical attractiveness influences labor market outcomes, political representation, and everyday life, often through large-scale survey data. Her work also extends to the development of reference budgets to define a minimally decent standard of living in Finland. Recent publications reveal a strong trend in analyzing gendered beauty inequality in labor markets, appearance pressures in digital spaces (especially during the pandemic), and material living standards through detailed consumption surveys. Her interdisciplinary work bridges sociology, economics, political psychology, and public policy. Scientific Projects and Grants: SOMA : The social mechanisms behind the economic consequences of physical appearance (Academy of Finland, 2019–2023), Principal Investigator Finland as an appearance society (Emil Aaltonen Foundation, 2016–2018), Project Leader Member of the Consumption Reference Budget Research Team at the University of Turku Advising and Teaching: She supervises Master’s theses and doctoral dissertations, teaches social theory and inequality at the bachelor’s level, and leads PhD seminars. She also coordinates the Finnish Society course for exchange students. While specific student names are not listed, her active supervision role is clearly stated. Labs and Research Teams: She leads the SOMA research project and is a key member of the reference budget research group. Her team produces detailed data reports on food, clothing, and leisure consumption, contributing to public policy debates on living standards.
Andre Sanches Ribeiro is a tenured Professor in the Faculty of Medicine and Health Technology at Tampere University, Finland, where he also leads the Laboratory of Biosystem Dynamics (LBD). His research lies at the intersection of computational modeling, single-cell biology, and synthetic biology, with a focus on understanding bacterial gene regulatory networks under stress conditions. He is affiliated with the Biosciences department and conducts interdisciplinary research combining experimental and computational approaches. His primary research interests include Gene Expression Dynamics , Gene Regulatory Networks , Single-Cell Biology , Systems Microbiology , and Synthetic Biology . He applies methods from stochastic modeling, network theory, and signal processing to decode transcriptional programs and regulatory mechanisms in bacteria. His lab uses live single-cell microscopy, RNA-seq, flow cytometry, and synthetic gene engineering to study how gene circuits function in vivo, particularly under antibiotic stress. The recent publications demonstrate a strong trend in understanding transcriptional regulation at multiple scales—from single promoters to entire regulatory networks. His work integrates empirical data with dynamic models, focusing on phenomena such as transcription attenuation, bimodal expression, and genome-wide stress responses. The lab has developed valuable genetic tools, including a widely accessible library of fluorescent reporters for global regulators in E. coli, distributed through AddGene. Andre S. Ribeiro has mentored several PhD students to completion, including Ines Baptista and Suchintak Dash, and continues to train the next generation of systems biologists. His lab actively collaborates with researchers internationally, as seen in joint publications with experts like Barry Sanders. Though no specific grants are listed, the sustained output and infrastructure suggest active funding support. The Laboratory of Biosystem Dynamics, founded in 2009, has evolved from a purely computational group into a multidisciplinary team with wet-lab capabilities. The lab maintains a strong online presence through its website , Twitter , YouTube , and repositories like AddGene , promoting open science and collaboration.
Timo Hämäläinen is a Professor of Computer Engineering at Tampere University, leading the Unit of Computing Sciences within the Faculty of Information Technology and Communication Sciences. He is a core member of the System-on-Chip research group and the Computer Engineering Team, actively contributing to the System-on-Chip Hub initiative. His research focuses on System-on-Chip (SoC) design methodologies, FPGA-based high-level synthesis, real-time embedded systems, and open-source hardware-software co-design frameworks like RISC-V and HEVC encoding. He has pioneered work on agile SoC development processes and validation techniques for large-scale hardware systems. Key research areas include: High-level synthesis (HLS) optimization for FPGAs Real-time processor architectures and context-switching latency reduction Formal verification of IP-XACT-compliant SoC designs Resilient RISC-V MPSoC implementations Hardware-accelerated algorithms for signal processing and networking His recent publications (2023-2025) emphasize agile SoC development frameworks, hardware-software co-design for real-time systems, and validation methodologies for large-scale embedded systems. He has contributed to open-source projects like Kvazaar HEVC encoder and the Kactus2 IP-XACT toolchain. Academic advising includes students such as Santéri Mäki-Äijö (formal verification), Arto Oinonen (RISC-V tooling), and Sakari Lahti (processor modeling). His work integrates academic research with industrial collaboration through frameworks like the Fault-slip-Through quality assessment methodology.
Mikko Sipilä is a Professor of Polar and Arctic Atmospheric Research at the University of Helsinki's Institute for Atmospheric and Earth System Research (INAR), where he also serves as Head of the Värriö Sub-Arctic Research Station. He leads the Polar and Arctic Atmospheric Research group (PANDA) that he established in 2015, which comprises 12 members including post-doctoral researchers and graduate students. His educational background includes: Doctor of Philosophy (PhD) in Physics, University of Helsinki (2010) Title of Docent in Physics, University of Helsinki (2015) Master of Science (MSc) in Physics, University of Helsinki (2006) Sipilä's research focuses on atmospheric nucleation processes, particularly in polar and arctic environments. His work bridges fundamental gas-to-particle conversion mechanisms with large-scale climate impacts, with special emphasis on how biogenic emissions form extremely low volatile organic compounds that drive new particle formation. His research has significant implications for understanding climate feedback mechanisms in sensitive polar regions. Analysis of his publication record reveals a strong trajectory from fundamental molecular processes to large-scale atmospheric implications, with numerous high-impact publications in Nature and Science. His work consistently addresses how microscopic atmospheric processes influence macroscopic climate phenomena, particularly in polar regions which are experiencing rapid climate change. His notable scientific achievements include: Marian Smoluchowski Award for Aerosol Research (2017) Finnish Association for Aerosol Research Award (2011) Clarivate Analytics Highly Cited Scientist (2018-2020) Finnish Academy Award (2020) Sipilä has secured substantial research funding totaling approximately 5 million EUR as principal investigator, including prestigious grants from the European Research Council and Academy of Finland. He has supervised 10 graduate students to completion and currently mentors 6 more. His research group operates cutting-edge facilities at the Värriö Sub-Arctic Research Station in Finnish Lapland, which serves as a critical platform for studying atmospheric processes in a rapidly changing climate. The PANDA research group maintains strong international collaborations, participates in major polar expeditions including those to Antarctica and Svalbard, and contributes to global initiatives like the MOSAiC expedition. Sipilä's work bridges fundamental atmospheric science with practical applications through spinoff companies he co-founded, demonstrating significant societal impact beyond academia.
Professor Ville Alopaeus holds a faculty position at Aalto University’s School of Chemical Engineering, specifically within the Department of Chemical and Metallurgical Engineering. He has been a professor since 2008, following a career at Neste in process development. His research focuses on separation processes, phase equilibria, and modeling for sustainable energy and materials. Key contributions include advancing the green transition through economically viable renewable energy solutions and optimizing processes for materials like ionic liquids and bio-compounds. Education and Career: Alopaeus has led teaching evaluation committees and departmental roles, emphasizing education alongside research. He has supervised over 130 master’s theses and contributes to chemical engineering education programs, blending research insights into teaching. His courses cover fundamentals and applied topics like plastics recycling and renewable raw materials. Research Interests: Alopaeus’ work spans process modeling, phase equilibria, and multiphase phenomena. He develops data-driven models for predicting thermodynamic properties (e.g., infinite dilution activity coefficients) and explores sustainable solvents like ionic liquids. Recent studies include CO₂ capture, hydrogen solubility in bio-oils, and biorefinery processes. Awards and Recognition: Honors include the Teacher of the Year award (Aalto University Student Union), Young Researcher Prize, and scholarships from Finnish foundations. His work bridges academia and industry, addressing large-scale sustainability challenges. Grants and Labs: He collaborates on projects like the AI-on-Demand platform and contributes to research groups focused on chemical engineering and process innovation. His lab focuses on multiphase systems, CFD modeling, and sustainable process design.
Markus Perola serves as a University Researcher at the University of Helsinki, holding dual roles as Supervisor for the Doctoral Programme in Biomedicine and the Doctoral Programme in Population Health. He maintains an active external position at THL (Finnish Institute for Health and Welfare) since 2001, demonstrating long-term commitment to national public health research. His research spans Biomedicine , Genetic Epidemiology , and Population Health , with particular focus on Genetic determinants of autoimmune diseases and diabetes Chronobiology and socioeconomic interactions Mitochondrial mechanisms in liver disease Large-scale biobank analytics (FinnGen) Electronic health record mining for clinical insights cutting-edge methodologies in precision medicine and population-scale data integration. Analysis of his 367 publications reveals dominant themes in genomic epidemiology and translational biomedicine , with recent work emphasizing AI-driven risk prediction (particularly for COVID-19 outcomes), mitochondrial pathways in chronic diseases, and fine-scale genetic ancestry mapping. His research increasingly integrates multi-omics data with real-world clinical records. His scientific leadership includes major EU-funded initiatives: B1MGplus (€10,420 funding) EU/PROPHET (€66,681 funding) PRIMUS privacy-preserving meta-learning project GoE: Genome of Europe initiative FinnGen biobank consortium Perola actively supervises doctoral candidates through two university programs while contributing to 34 media engagements that translate complex genomic findings for public understanding. His work demonstrates consistent translational impact from basic genetic mechanisms to clinical applications and public health policy.
Kristian Koerselman is a Senior Researcher at the Finnish Institute for Educational Research , University of Jyväskylä. His work focuses on the economics of education, utilizing quantitative methods to evaluate educational policies and systems. Primary fields: Economics of Education, Labor Economics, Policy Evaluation Key projects: Finnish student financing systems, PhD employment patterns, intergenerational mobility in academia His research group, Empirical Microeconomics (EME) , explores causal relationships in educational and labor markets through large-scale register data and randomized experiments. Publications highlight his expertise in Finnish higher education policy, doctoral career analysis, and social equity in academic access. Koerselman's collaborations span Finnish institutions, including studies on pandemic-era education and labor market disruptions. While his work emphasizes European contexts, he maintains a strong focus on Finland's educational systems and outcomes.
Lassenius Casper is a Professor at the Department of Computer Science, School of Science, Aalto University. His research focuses on agile software development methodologies, scaling frameworks like SAFe, continuous delivery, and DevOps practices. He has contributed extensively to understanding challenges and benefits in large-scale agile transformations, particularly in global and distributed organizations. Key research interests include: Agile Scaling Frameworks (e.g., SAFe) Continuous Delivery and DevOps Software Engineering Education Agile Adoption Challenges Large-Scale Agile Development Recent publications explore topics such as data-limited experimentation in software ecosystems, challenges in adopting agile frameworks, and the impact of minimum viable products on software failure. His work emphasizes empirical studies and case analyses in industry settings.
Pasi Fränti is a Professor of Computer Science at the University of Eastern Finland (UEF) since 2000, affiliated with the School of Computing within the Faculty of Science, Forestry and Technology. He holds MSc and PhD degrees from the University of Turku (1991 and 1994). His research focuses on machine learning, data mining, pattern recognition, and location-based systems, with notable contributions to clustering algorithms, image compression, and speech technology. Fränti leads the Machine Learning research group at UEF and has supervised 25 PhD students, covering topics like clustering, image/audio compression, and location-aware systems. His work bridges theoretical advances with practical applications in healthcare optimization, mobile services, and intelligent systems. He has published extensively, with over 79 journal articles and 167 conference papers, including 14 IEEE Transactions papers. Recent research highlights include optimizing health station locations via clustering algorithms, outlier detection improvements, and gamified location-based services (e.g., Mopsi). His interdisciplinary projects address challenges in urban planning, energy systems, and biomedical signal processing. Fränti actively critiques academic publishing practices, advocating for open science and peer review reforms. Key projects include the IMPRO initiative (2018–2023) supporting health/social services reform, and contributions to journals like Applied Computing and Intelligence . His lab develops tools for real-time data clustering and spatial analysis, with applications in mobile user behavior prediction and smart city infrastructure planning.
Martín Brun Moratorio is a Postdoctoral Research Fellow at the Finnish Centre of Excellence in Tax Systems Research (FIT) at Tampere University's Faculty of Management and Business. He earned his PhD from Universitat Autònoma de Barcelona (UAB) in 2024 and maintains affiliations with Economics of Inequality and Poverty Analysis (EQUALITAS) and the Network on Welfare and Policy in Latin America and the Caribbean (WAPLAC). His research program centers on Behavioral and Experimental Economics, with particular emphasis on how cognitive abilities shape economic decision-making. Brun has conducted innovative lab-in-the-field experiments with school students to investigate the developmental trajectory of fairness preferences, finding that meritocratic views increase with age and cognitive ability. His methodological approach combines experimental economics with careful analysis of cognitive processes. Brun's publication record reveals three interconnected research strands: (1) the relationship between cognitive ability and economic preferences (particularly regarding redistribution and health policy), (2) the development of fairness preferences during adolescence, and (3) reproducibility in economic research. His recent work demonstrates that high-cognition individuals show greater support for redistribution and circumstance-based vaccine distribution, suggesting a link between cognitive processing and prosocial preferences. He actively participates in collaborative research examining: Cognitive development and fairness preferences Role models and STEM education engagement Taxation effects on tourism Study practices in higher education Reproducibility challenges in economics Brun's methodological contributions extend to large-scale replication efforts, where he has examined researcher variation in experimental design and analysis. His work bridges theoretical insights with practical policy implications across multiple economic domains.
Henri Jalo is a Postdoctoral Research Fellow at the Faculty of Management and Business, Department of Information and Knowledge Management at Tampere University. His research focuses on extended reality (XR) technologies, organizational adoption challenges, and their applications in facility management, industrial collaboration, and digital campus environments. He specializes in mixed methods studies analyzing user resistance, enabling factors for technology diffusion, and virtual team dynamics. Key research themes include: Extended Reality (AR/VR/MR) adoption in SMEs and industrial sectors Metaverse collaboration and virtual workspaces Technology-enabling factors for digital transformation Social virtual reality applications in property lifecycle management His recent work (2021–2024) emphasizes XR's strategic role in organizational innovation, remote collaboration, and facility lifecycle optimization. He has conducted large-scale surveys on XR adoption in European manufacturing and pioneered studies on metaverse collaboration effectiveness over sustained periods. Publications highlight interdisciplinary approaches combining information systems theory with practical industry challenges in construction, real estate, and higher education environments. Current projects likely explore emerging XR applications in post-pandemic organizational workflows and digital twin integration.
Gleb Tikhonov is a postdoctoral researcher at the University of Helsinki , affiliated with the Faculty of Biological and Environmental Sciences and the Organismal and Evolutionary Biology Research Programme . He also holds a postdoctoral position at Aalto University in the Department of Computer Science . His work bridges statistical ecology, machine learning, and computational biology. Research Interests : Development of joint species distribution modelling (JSDM) for ecological communities Integration of statistical and machine learning methods High-performance computing implementations Phenological and dispersal pattern analysis Publications demonstrate expertise in applying advanced statistical frameworks to ecological questions, including fungal dispersal mechanisms, microbiome variation, and climate change impacts. His LIFEPLAN project (funded by the European Commission Joint Research Centre) focuses on planetary biodiversity synthesis using big data. Education : PhD in Biological and Environmental Sciences, University of Helsinki (2018) MS in Applied Mathematics, Lomonosov Moscow State University (2014)
Jetro Tuulari is an Associate Professor and Docent in the Department of Clinical Medicine at the University of Turku, where he also serves as Research Manager in Clinical Neurosciences and Doctoral Researcher in the Department of Computing. He is the Principal Investigator of the FinnBrain Neuroimaging Lab and Head of Neuroimaging at the InterLearn Centre of Excellence. He is affiliated with the Centre for Eudaimonia and Human Flourishing at the University of Oxford and part of the international Lifespan consortium developing human brain growth charts. His research focuses on how early life exposures, genetics, and environmental factors shape brain structure and function, influencing long-term health and wellbeing. Using advanced neuroimaging techniques such as MRI, fMRI, dMRI, PET, and EEG, his team investigates developmental cognitive neuroscience, with emphasis on maternal health, childhood adversity, obesity, and intergenerational effects. His work bridges clinical medicine, computing, and population neuroscience, contributing to large-scale cohort studies like FinnBrain, ABCD, and the Developing Human Connectome Project. His recent publications (2024–2025) reflect a strong trend in population neuroscience, neonatal brain development, epigenetics, and methodological innovation in neuroimaging. Key themes include maternal BMI and brain development, prenatal stress and child outcomes, transgenerational epigenetic inheritance, and AI-driven analysis of neuroimaging data in conditions like Long COVID. Finnish Medical Foundation Emil Aaltonen Foundation Sigrid Juselius Foundation Signe and Ane Gyllenberg Foundation Hospital District of Southwest Finland State Research Grants Alfred Kordelin Foundation Juho Vainio Foundation Orion Research Foundation He supervises a vibrant research team of post-doctoral fellows, doctoral students, and undergraduates within the FinnBrain Neuroimaging Lab. He has played a key role in launching the Human Neuroscience Master’s Programme at the Turku Brain and Mind Center and coordinates courses on neuroimaging methods. His international collaborations include researchers at Oxford, Cambridge, KCL, Charité – Universitätsmedizin Berlin, and the University of California, Irvine. He leads the FinnBrain Neuroimaging Lab, which conducts multimodal neuroimaging analyses within the FinnBrain Birth Cohort. The lab is part of broader initiatives like InterLearn and the Lifespan consortium, focusing on synergistic data analysis, brain network modelling, and population-level neuroscience.
