Jun Yu

Jun Yu2023-08-23T13:36:02+02:00


Affiliate Professor.

“Nothing puzzles me more than time and space; and yet nothing troubles me less, as I never think about them.”(Charles Lamb)

I am leading the research group on statistical learning and inference for spatiotemporal data.

We work on tackling theoretical data science problems and developing statistical learning methods for solving real-life problems, which originate from various application areas, including atmospheric icing, automobile industry, biomedical engineering, climate research, epidemiology, forestry, geochemistry and hydrology, radiation oncology, spatial ecology, sports science, and transportation.

Regarding the statistical learning and inference studied: statistical learning with sparsity, compressive sensing, mathematics of data science, hierarchical spatiotemporal modelling, nonparametric density/intensity estimation and smoothing techniques, statistical inference for hidden Markov models and random fields, summary statistics for point processes, and wavelet theory applied to signal and image analys.

In terms of data analysis tools: intelligent data sampling using compressive sensing, large-scale environmental data model, multimodal image processing, tree growth models, and general modelling of biological populations in space and time.

Current Projects

  • Statistical Learning for Chronosilviculture (Kempe Foundation)

    Bertold Mariën (IceLab), Maria Eriksson (PI, UmU), Jun Yu (PI, UmU)

  • Compressive sensing and statistical learning with sparsity

    Zhiyong Zhou (ZUCC), Armin Eftekhari (PI), Ali Dadras, Hoomaan Maskan, Jun Yu (PI, UmU)

  • Next generation quantitative magnetic resonance imaging for individualized radiotherapy

    Anders Garpebring (PI), Tufve Nyholm, Tommy Löfstedt, Jun Yu (UmU)

  • Pioneering ultrasound imaging methods for neuromuscular diagnostics

    Christer Grönlund (PI, UmU), Robin Rohlén (LU), Jun Yu (UmU)

  • Statistical modelling and intelligent data sampling in MRI and PET measurements for cancer therapy assessment

    Zhiyong Zhou (ZUCC), Ida Häggström (Chalmers UT),  Anders Garpebring, Jan Axelsson, Klara Leffler, Jianfeng Wang, Jun Yu (PI, UmU)

The Latest Posts

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Lessons from SFI CSSS

Lessons from the 2023 SFI Complex Systems Summer School Four weeks filled with interesting lectures, exciting discussions and hikes in the beautiful surroundings - this was IceLab PhD student Hanna Isaksson’s [...]

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