Linda Hartman

Linda Hartman is a Senior Lecturer in Mathematical Statistics at the Centre for Mathematical Sciences, Faculty of Science, Lund University. She is actively involved in interdisciplinary research within the MERGE (ModElling the Regional and Global Earth system) initiative and contributes to Lund University’s profile areas in Engineering Health, Aerosols, and Nature-based Future Solutions. Her work bridges statistics with applications in medicine, environmental science, and technical development.

• Academic Rank: Senior Lecturer
• Department: Centre for Mathematical Sciences
• University: Lund University
• Research Affiliations: MERGE, LTH Profile Areas (Engineering Health, Aerosols), LU Profile Area (Nature-based Future Solutions)

Her research focuses on applied statistics in environmental, climate, and medical sciences. She specializes in statistical modeling and data analysis for sustainability, cancer research (particularly breast and ovarian cancer), and climate change. Her work supports the UN Sustainable Development Goals related to health, climate action, and responsible consumption.

The recent publications highlight her interdisciplinary reach, spanning aerosol science, oncology, and climate advocacy. Her articles reflect a strong trend in applying advanced statistical methods to real-world problems in medicine and environmental systems, often in collaboration with domain experts. She contributes both to peer-reviewed research and public discourse on climate policy.

Her scientific recognition includes:

• W-sektionens pedagogiska pris 2023 – awarded for excellence in teaching and pedagogical innovation.

Linda Hartman is actively involved in supervising students and advancing pedagogy in higher education. She has supervised master’s level research, such as the thesis on baseball statistics. She is deeply committed to teaching innovation, employing active and cooperative learning strategies. She contributes to organizing pedagogical seminars and is responsible for developing and teaching key courses in mathematical statistics and data analysis, including the advanced course on statistical learning and visualization. Her grants and projects include work on prognostic factors in breast cancer radioresistance and fog patterns at Swedish airports, demonstrating sustained external funding and collaboration.

She is a key member of research teams in both medical and environmental domains, contributing statistical expertise to interdisciplinary projects. Her leadership in organizing conferences and workshops, such as the ELLITE Focus Period Symposium on Machine Learning for Climate Science, underscores her active role in the academic community.