جستجوی استاد راهنمای دانشگاهی

Luigi Acerbi is an Associate Professor at the Department of Computer Science, University of Helsinki, leading the Machine and Human Intelligence research group. He is affiliated with the Finnish Center for Artificial Intelligence (FCAI) and ELLIS (European Laboratory for Learning and Intelligent Systems). His research focuses on probabilistic machine learning, statistical inference methods (e.g., amortized and surrogate-based approaches), and computational and cognitive neuroscience, including Bayesian models of perception and resource-constrained rationality. Previously, he held postdoctoral positions at the University of Geneva and New York University. He earned his PhD from the Doctoral Training Centre in Computational Neuroscience at the University of Edinburgh, working with Sethu Vijayakumar and Daniel Wolpert. His work includes developing open-source tools like BADS (Bayesian Adaptive Direct Search) and VBMC (Variational Bayesian Monte Carlo), widely used for optimization and Bayesian inference in MATLAB/Python. He actively contributes to the academic community through teaching (e.g., BAMB! 2022 summer school tutorials on model fitting) and software development (GitHub repositories for optimization, inference, and AI tools like Athanor). His research bridges machine learning, neuroscience, and cognitive science, emphasizing robust and efficient statistical methods.

• Probabilistic Machine Learning
• Statistical Inference
• Computational Neuroscience
• +۴ مورد دیگر

Tiina Lindh-Knuutila is a Researcher in the Department of Neuroscience and Biomedical Engineering at Aalto University, holding a Doctoral degree in Engineering and Technology (2014) and a Master's degree from Helsinki University of Technology (2005). Her work bridges neuroscience and computational modeling to investigate brain dynamics during language processing. Education: Doctoral degree in Engineering and Technology, Aalto University (2014) Master's degree in Engineering and Technology, Helsinki University of Technology (2005) Research Interests: Her expertise centers on Magnetoencephalography (MEG) and semantic processing , with deep specialization in computational modeling of neural representations . She pioneers methods to decode brain responses to written language using vector space models and unsupervised learning, advancing understanding of how semantic features activate cortical networks during reading and cognitive tasks. Recent Research Trends: Her 2023-2025 publications reveal a cohesive focus on decoding semantic representations from MEG data, particularly examining morphologically complex words, misspelled-word effects, and cross-linguistic semantic norms. This work consistently applies machine learning to neural time-series data, highlighting evidence accumulation dynamics in semantic processing and establishing robust brain-decoding pipelines for linguistic stimuli. Grants and Projects: She contributes to two Academy of Finland-funded initiatives: the active consortium project Salmelin_konsortio: Aivojen, mielen ja taudin kulun toiminnallinen yksilöllisyys (2023-2027) investigating individual brain variability, and the completed Dyslexia: genes, brain functions, interventions project (2015-2019) that integrated MEG with dyslexia research. Collaborative Network: As a core member of Riitta Salmelin's research group, she engages in interdisciplinary collaborations spanning neuroscience, engineering, and computer science, with documented international exchanges including visiting researcher positions in 2008-2009.

• Neuroscience
• Magnetoencephalography
• Semantic Processing
• +۳ مورد دیگر

Roosa Yli-Pietilä is a Postdoctoral Researcher at Tampere University, Finland, actively contributing to the field of educational sciences with a focus on teacher well-being and professional agency. Her research is deeply rooted in understanding socio-emotional dynamics in primary education. Her research interests include teacher professional agency , burnout , well-being , teacher-student interactions , and educational psychology , particularly in Finnish primary schools. She employs advanced statistical methods such as Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze complex relationships in educational data. The trend in her recent publications (2023–2025) shows a consistent focus on the interplay between teachers' psychological states and their professional functioning. Her work bridges individual agency with systemic factors, often comparing cross-national data and exploring longitudinal patterns in teacher development. Although no scientific awards are listed, her research has gained visibility through Open Access publications and engagement on academic platforms like Mendeley and X (formerly Twitter). She has collaborated with prominent researchers including Kirsi Pyhältö, Tiina Soini, Janne Pietarinen, and others, indicating active participation in a robust research network. There is no mention of advising students or securing grants in the provided text. Roosa Yli-Pietilä is associated with Tampere University’s doctoral program, having completed her dissertation in 2025. While specific lab or research group details are not provided, her thematic fingerprint suggests affiliation with research in teacher education and well-being.

• Educational Psychology
• Teacher Professional Agency
• Burnout
• +۷ مورد دیگر