جستجوی استاد راهنمای دانشگاهی

• Epidemiology
• Climate Science
• Statistical Modeling
• +۳ مورد دیگر

Panu Erästö is a Senior University Lecturer at Aalto University's Department of Information and Service Management. His research focuses on interdisciplinary applications of statistical modeling, epidemiology, and environmental science. Notably, he contributed to a groundbreaking 2020 study on SARS-CoV-2 aerosol transmission, highlighted by the Aallon Tutkimusvaikuttaja-palkinto award. His work spans infectious disease dynamics, climate reconstructions, and healthcare data analysis. Research Interests: - Statistical modeling of environmental and health data - Transmission dynamics of pathogens (e.g., Streptococcus pneumoniae) - Bayesian methods in paleoclimatology - Public health interventions and risk assessment Key Projects: - Led the interdisciplinary 'COVID-19: The Airborne Transmission Mode' project (2020) - Collaborated on Bangladeshi pneumococcal transmission studies (2009) - Developed climate reconstructions using fossil assemblages (2006) Awards: Aallon Tutkimusvaikuttaja-palkinto 2020 Grants & Collaborations: - Active in Aalto-VTT-Helsinki University partnerships - Coordinated multi-institutional pandemic response research

Kaie Kubjasمشاهده پروفایل

دانشیار

• Algebraic Statistics
• Nonlinear Algebra
• Matrix and Tensor Decompositions
• +۵ مورد دیگر

Kaie Kubjas is an Associate Professor at Aalto University in the Department of Mathematics and Systems Analysis, School of Science. Since 2024, she has held a tenured position, following a tenure-track role from 2017–2024. She earned her PhD in Mathematics at Freie Universität Berlin (2013) under Professors Christian Haase and Klaus Altmann, with postdoctoral research at institutions including the Max Planck Institute and MIT. Her research focuses on applied nonlinear algebra, algebraic statistics, and their applications in biology (e.g., phylogenetics and 3D genome reconstruction), as well as matrix/tensor decompositions. She has organized major events like the European Women in Mathematics General Meeting 2022 and the 2025 workshop on Algebraic Statistics and Multistate Models. Kubjas serves on editorial boards of journals like SIAM Journal on Applied Algebra and Geometry and Annales Fennici Mathematici . Recent work includes advances in log-concave maximum likelihood estimation, 3D genome reconstruction, and structured matrix decompositions. Her students, such as Olga Kuznetsova (Second Place MEGA 2021 Poster Award winner), have contributed to these areas. She regularly contributes to seminars like the Algebra and Discrete Mathematics at Aalto, fostering interdisciplinary collaboration.

• Statistics
• Public Health
• Epidemiology
• +۳ مورد دیگر

Reijo Sund is a Professor at the University of Eastern Finland (UEF) and holds a Docentship at the University of Helsinki's Faculty of Social Sciences. His research spans statistics, public health, and clinical epidemiology, with a focus on bone health, cancer survivorship, and genetic epidemiology. University: University of Eastern Finland Docentship: University of Helsinki Academic Rank: Professor His scientific work integrates biostatistical methods with population health studies, covering topics such as fracture risk prediction (FRAX®), cardiometabolic outcomes in children, cancer-related complications, and machine learning applications in medical imaging. Recent publications highlight collaborations across Finland and Sweden, with emphasis on longitudinal twin studies and large-scale register analyses. Research trends include: Genetic regulation of body size and morphology Diabetes-cancer comorbidity analysis 3D imaging biomarkers for bone strength Workload-health associations Sund has contributed to editorial work as a guest editor for BMC Health Services Research and participated in hosting academic visitors at the University of Helsinki.

• Mathematics
• Actuarial Mathematics
• Survival Analysis
• +۴ مورد دیگر

Jaakko Lehtomaa is a Lecturer at the Department of Mathematics and Statistics, University of Helsinki. He specializes in survival and event history analysis, with a focus on heavy-tailed risk processes in insurance and finance. His research explores asymptotic independence and support detection techniques in multivariate data, contributing to extreme value theory and stochastic processes. Affiliation: University of Helsinki, Department of Mathematics and Statistics Expertise: Actuarial mathematics, heavy-tailed distributions, risk modeling Research Trends His publications (2015–2023) span journals like Journal of Applied Probability , Risks , and Insurance: Mathematics and Economics . Key areas include tail estimation, large deviations, and directional component analysis for heavy-tailed data. Projects He contributes to the project Mathematical and statistical modeling of communicable and noncommunicable diseases (2025–2027), focusing on bridging academic research with practical disease modeling.

Krista Tuohimaaمشاهده پروفایل

مدرس

• Speech and language development
• Social communication
• Hearing loss in children
• +۳ مورد دیگر

Krista Tuohimaa is a Lecturer in Logopedics at the University of Oulu's Faculty of Humanities, specializing in speech, language, and social communication development in children with hearing impairments. She maintains a dual role as part-time speech-language therapist at Oulu University Hospital and private practice, with active research contributions since 2022. Primary affiliation: Research Unit of Logopedics, University of Oulu Research domains: Hearing-impaired child development, Social-pragmatic communication, Reading/writing acquisition Methodological focus: Longitudinal studies, Multicenter collaborations, Standardized assessments Her work examines speech perception-production dynamics across hearing conditions, social-pragmatic understanding in preschoolers, and literacy development in hearing-impaired populations. Current projects analyze nonword repetition skills and social communication factors using advanced statistical models. Professional network includes collaborations with Oulu University Hospital and multidisciplinary research teams. She employs mixed-methods approaches combining clinical observations with educational interventions.

Lauri Viitasaariمشاهده پروفایل

استادیار

• Statistics
• Mathematics
• Data Science
• +۳ مورد دیگر

Lauri Viitasaari is an Assistant Professor in Statistics, Mathematics, and Data Science at Aalto University School of Business, Finland, holding a position since January 2024. He also serves as an Adjunct Professor (title of docent) in Mathematics at the University of Helsinki (since September 2019) and in Applied Mathematics at the University of Vaasa (since November 2016). He earned his Doctor of Science (DSc) in Mathematics from Aalto University School of Science in February 2014. His research focuses on stochastic processes, probability theory, and their applications in data science and mathematical analysis. Key areas include stochastic differential equations, rough path theory, fractional Brownian motion, extreme value analysis, and convex regularization methods. His work bridges theoretical foundations with practical challenges in computational statistics and mathematical finance. Recent publications highlight contributions to stochastic pressure equations, discretization convergence rates, and latent variable models. He actively supervises bachelor's, master's, and PhD theses in these domains. His research has been published in journals like Electronic Communications in Probability , Journal of Differential Equations , and Journal of Multivariate Analysis .

Vanni Noferiniمشاهده پروفایل

دانشیار

• Numerical Analysis
• Linear Algebra
• Matrix Polynomials
• +۴ مورد دیگر

Vanni Noferini is an Associate Professor in the Department of Mathematics and Systems Analysis at Aalto University, part of the School of Science. His research focuses on numerical linear algebra, matrix theory, and their applications in network science and complex systems. He holds joint affiliations with the Mathematical Statistics and Data Science, Algebra and Discrete Mathematics, and Numerical Analysis groups within the department. His work spans topics including matrix polynomials, eigenvalue problems, structured matrices, and the analysis of networks using algebraic and spectral methods. Notable contributions include studies on Smith forms, Riemannian optimization for matrix nearness problems, and non-backtracking centrality measures in graphs. Noferini has authored over 50 publications in top-tier journals such as SIAM Journal on Matrix Analysis and Applications , Linear Algebra and Its Applications , and Journal of Complex Networks . His research also intersects with applications in control theory, graph algorithms, and random matrix theory.

• Environmental Engineering
• Wastewater Treatment
• Process Control
• +۳ مورد دیگر

Henri Uolevi Haimi is a Professor of Practice at Aalto University , affiliated with the Department of Water and Environmental Engineering under the School of Engineering. His work focuses on data-driven approaches for wastewater treatment systems, including sensor technologies, anomaly detection, and process optimization.

• Machine Learning
• Health Informatics
• Transportation Modeling
• +۴ مورد دیگر

Jaakko Hollmen serves as a Senior University Lecturer in the Department of Computer Science at Aalto University, affiliated with the Helsinki Institute for Information Technology (HIIT) and the Computer Science Lecturers research group. His interdisciplinary work bridges machine learning with critical applications in healthcare, transportation systems, and environmental science. His research focuses on advanced machine learning methodologies including Bayesian optimization, random forests, and principal component analysis. Key application areas span neonatal healthcare (mortality prediction, brain injury analysis), transportation modeling (activity-based model calibration), and environmental data science (weather-crop relationships, drug-environment interactions). His approach emphasizes practical implementations of complex algorithms for real-world problems. Hollmen's recent publications (2018-2023) reveal a consistent trajectory in developing machine learning solutions for high-dimensional data challenges, with increasing emphasis on medical applications. His work demonstrates strong cross-domain collaboration, particularly with medical researchers at Helsinki University Hospital. His notable recognition includes: Best paper finalist and runner-up award (Computer Track) at the first IEEE Life Sciences Conference (LSC) for research on predicting complications in very low birth weight infants (2017) As a core member of HIIT, Hollmen contributes to Finland's national information technology research infrastructure while maintaining active collaborations with medical and agricultural research groups. His current projects focus on optimizing transportation models and advancing clinical prediction systems through novel machine learning techniques.

• High Energy Physics
• Experimental Particle Physics
• Medical Imaging
• +۳ مورد دیگر

Erik Brücken is a University Lecturer and Docent at the Department of Physics, University of Helsinki. He actively participates in the Doctoral Programme in Materials Research and Nanosciences, as well as the Doctoral Programme in Particle Physics and Universe Sciences. His research spans high-energy physics, experimental particle physics, and detector development. Primary affiliation: Department of Physics, University of Helsinki Supervisory roles in two doctoral programs Active in CMS and ALICE collaborations Research Interests: Brücken's work focuses on experimental particle physics at colliders like the LHC, particularly in detector optimization and data analysis. His projects include the ALICE Time Projection Chamber Upgrade and multispectral photon-counting for medical imaging. Current research examines B meson decays, Higgs boson properties, and jet substructure in heavy-ion collisions. Recent Publications: His 2025 contributions include analyses of B0 meson decays, Higgs self-coupling constraints, top quark production cross-sections, and jet substructure studies in nuclear collisions. Projects: He leads a 2024-2027 European particle physics infrastructure project (TOTEM) and participates in collaborations related to detector development and beam characterization. Past projects include CMS Tracker upgrades and CDF experiments spanning 2002-2017. Academic Activities: Brücken organizes and presents at international conferences like the European Researcher's Night and Euroschool on Exotic Beams. He serves as a doctoral thesis committee member and contributes to peer review processes.

Markku Lanneمشاهده پروفایل

استاد

• Econometrics
• Time Series Analysis
• Macroeconomics
• +۳ مورد دیگر

Markku Lanne is Professor of Economics at the University of Helsinki's Faculty of Social Sciences, where he has served since August 2010. He also holds the position of Vice-Dean for Academic Affairs of the Faculty of Social Sciences and leads the Financial and Macroeconometrics research group. His academic journey includes previous appointments as Professor of Empirical Macroeconomics at the University of Helsinki (2007-2010) and Professor of Economics and Finance at the University of Jyväskylä (2003-2007). He maintains adjunct professorships (docent) in econometrics at the University of Helsinki (since 2001) and in financial econometrics at Aalto University (since 2008). Professor Lanne's research focuses on advanced time series econometrics with applications in macroeconomics and finance. His work centers on structural vector autoregression models, non-Gaussian time series analysis, identification methods, and macroeconomic forecasting. His research has significant implications for understanding economic shocks, inflation dynamics, and the relationship between financial markets and the real economy. He has developed innovative approaches to identifying structural economic relationships using non-Gaussian features of economic data. Lanne's publication record shows a clear progression toward increasingly sophisticated methods for analyzing non-Gaussian economic time series. His recent work (2022-2024) demonstrates a strong focus on statistical identification of structural relationships using non-Gaussian features, particularly in the context of vector autoregressive models. This research has important applications for understanding macroeconomic shocks, weather impacts on economies, and improving economic forecasting methods. His scientific recognition includes: Alfred Kordelin Foundation encouragement prize (2011) Good Teaching Award (2014) Professor Lanne actively supervises doctoral students and serves as a pre-examiner for doctoral theses. He has secured significant research funding, most notably a major Academy of Finland project on structural analysis of non-Gaussian macroeconomic and financial time series (2022-2026). He regularly contributes to the academic community through peer review for top journals including Journal of Econometrics, Journal of Business and Economic Statistics, and Review of Economics and Statistics. He leads the Financial and Macroeconometrics research group at the University of Helsinki, which focuses on developing and applying advanced econometric methods to macroeconomic and financial problems. The group maintains active collaborations with researchers internationally and contributes to both theoretical advances in econometrics and practical applications in economic policy analysis.

• High Energy Physics
• Particle Physics
• Experimental Physics
• +۳ مورد دیگر

Erik Brucken is a University Lecturer at the Department of Physics, University of Helsinki, affiliated with the Faculty of Science. He is also a supervisor for doctoral programs in Particle Physics and Universe Sciences, and Materials Research and Nanosciences. Research focuses on high energy physics and experimental particle physics, particularly in CMS experiment collaborations at CERN. Active in projects like the Euroopa hiukkasfysiikan tutki (2024–2027) and ALICE Time Projection Chamber Upgrade Project (2013–2018). His research interests include Higgs boson studies, top quark dynamics, jet physics, and detector development. He has published extensively on topics such as rare decays, muon identification, and quantum entanglement in collider experiments. Advises doctoral students in particle physics and collaborates widely, participating in conferences like the International Europhysics Conference on High Energy Physics and CMS Tracker Weeks. His work contributes to advancing detector technologies and computational tools for high-energy physics.

• Geropsychology
• Wellbeing and health
• Innovation expertise
• +۹ مورد دیگر

Tuomas Leisti is a Lecturer and Doctor of Psychology (PsT) at Metropolia University of Applied Sciences, affiliated with the Wellbeing Team 3. His professional roles include teaching psychology and research methods, supervising Master's theses, and contributing to RDI (Research, Development, Innovation) projects. He holds certifications as a licensed psychologist and professional teacher (AmO), with proficiency in Finnish (native), English (excellent), Swedish (average), and German (basic). Leisti's research focuses on geropsychology, wellbeing and health, innovation expertise, cognitive psychology, and the philosophy of mind. His doctoral work explored the role of consciousness in decision-making, with prior experience in human-technology interaction. He is particularly interested in decision-making processes, problem-solving, and the metacognitive skills underlying these activities. Key projects include the Wellbeing Hybridist initiative (2021–2023) and the pan-European COMHOM project (2025–2028), which addresses homelessness through data-driven solutions. His research outputs span over two decades, emphasizing subjective image quality evaluation, cognitive modeling, and quantitative methodologies. Leisti's work integrates empirical and philosophical approaches, addressing topics such as qualia, decision heuristics, and the interplay between conscious thought and judgment. Despite no explicitly listed awards, his extensive publication record reflects sustained contributions to psychological and applied research fields.

• Biostatistics
• Public Health
• Nutrition Science
• +۴ مورد دیگر

Jaakko Nevalainen is a Professor of Biostatistics and Head of the Health Sciences Unit at the University of Tampere , Faculty of Social Sciences. His work integrates computational methods and statistical theory to address health-related research questions in nutrition, diabetes, prostate cancer, and cardiovascular disease. He leads the LoCard research consortium, developing computational methods to study food consumption and health sustainability. His research has received significant funding from the Academy of Finland and Horizon Europe, resulting in over 160 peer-reviewed publications in top journals like Statistics in Medicine , Diabetologia , and JAMA . Key research areas include biostatistical method development, health economics, and applied epidemiology. His teams collaborate with institutions like the University of Helsinki and participate in population studies such as ProScreen (prostate cancer screening) and DIPP (type 1 diabetes). Major projects focus on food purchasing patterns, obesity-related health outcomes, and sustainable dietary transitions. He has secured major grants including Academy of Finland funding for the ProScreen trial and EU Horizon grants for LoCard. His interdisciplinary approach bridges statistical innovation with real-world health challenges, emphasizing translational research and data-driven policy recommendations.

Hannu Tuuriمشاهده پروفایل

مدرس

• Market Research
• Statistics
• Multivariate Methods
• +۳ مورد دیگر

Hannu Tuuri is a Lecturer and Market Researcher at Seinäjoki University of Applied Sciences (SeAMK). Their expertise includes statistical research, multivariate methods, and proficiency in IBM SPSS Statistics and Webropol software. Hannu holds a Master of Science (MSc) in the Statistics Degree Programme. Specialties: Market research, statistics, IBM SPSS Contacts: +358408302346 | hannu.tuuri@seamk.fi Research focuses on applying statistical methodologies to market analysis and data visualization. Active in developing educational materials for applied statistics and software training within higher education contexts.