معرفی
Sebastian Mair is an Assistant Professor at the Division of Statistics and Machine Learning (STIMA) at Linköping University, Sweden. He previously served as a postdoctoral researcher at the Division of Systems and Control at Uppsala University and completed his PhD in the Machine Learning Group at Leuphana University of Lüneburg. His academic journey includes a Master of Science in Computer Science and a Bachelor of Science in Mathematics from the Technical University of Darmstadt, as well as a Bachelor of Science in Computer Science from Hochschule Darmstadt University of Applied Sciences.
His research focuses on statistical machine learning, with an emphasis on unsupervised learning, representation learning, and efficient data summarization. Key areas include generative modeling, probabilistic methods, and geometric data analysis. He has contributed to advancements in privacy amplification via importance sampling, task-specific graph subsampling, and self-supervised autoencoder architectures.
Publications span topics like privacy-preserving techniques, graph algorithms, and medical treatment optimization. While no scientific awards are explicitly mentioned, his work demonstrates significant contributions to foundational machine learning research.
As part of STIMA, he collaborates with a diverse team of researchers, including senior professors, postdocs, and PhD students. His teaching and research activities align with the division’s focus on modern data analysis and the international master’s program in Statistics and Machine Learning.
