Cooperative Institute for Research in Environmental Sciences at the University of Colorado Boulder

Fadil Inceoglu

Research Interests

I am a Research Scientist in Space Physics and Machine Learning, and I am working with the GOES-R MAG team and hope to have collaborations with other teams as well. My research area covers a wide range from long-term variations in solar activity levels from cosmogenic radionuclides and solar dynamos to short(er)-term variations from surface magnetograms of the Sun and solar differential rotation rates from global helioseismological inversions. I also apply various Machine Learning methods to detect activity structures on solar images, to predict occurrences of solar flares, CMEs, and SEPs, to detect anomalies in data and generate correction algorithms to mitigate them. I have a PhD in Physics, a MSc in Nuclear Sciences, and a BSc in Astronomy and Space Sciences. 

Automated detection of Coronal Holes on AIA/SDO, Active Regions and Sunspot on HMI/SDO images (work in progress). This study is a follow-up to Inceoglu et al. 2022b ApJ.

Lowpass (left) and bandpassed (right) filtered surface magnetic field and flow field (rotation rate residuals) at different depths (Inceoglu et al., 2022a ApJ).

The Long short-term memory cell. We used LSTMs together with unsupervised k-shape method to correct the offset anomalies in GOES-16 MAG data (Inceoglu et al., 2021b SW)

Honors and Awards

  • 2020 CIRES/ NOAA Administrator Award for GOES-R team (team award)