Research

By application area:

Climate

• I am currently working on a regression based causal inference method using satellite images.

• Characterization of spatial and temporal trends in extreme precipitation using functional principal component analysis (abstract)
  Miyabi Ishihara, Michelle Yu, Mark Risser, Christopher Paciorek.
  Presented at JSM, LBNL, IMSC, BSTARS, 2019.
  Keywords: functional analysis | extreme value | spatiotemporal visualization

Planetary Remote Sensing

• A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery
  Esther Rolf^*, Jonathan Proctor^*, Tamma Carleton^*, Ian Bolliger^*, Vaishaal Shankar^*, Miyabi Ishihara, Benjamin Recht, Solomon Hsiang.
  Nature Communications, 2021.
  Keywords: satellite imagery | machine learning | socioeconomic, environmental monitoring

Health

• Shortening the Edinburgh Postnatal Depression Scale using Optimal Test Assembly Methods: Development of the EPDS‐Dep‐5
  Daphna Harel, Brooke Levis, Miyabi Ishihara, Alexander W. Levis, Simone N. Vigod, Louise M. Howard, Brett D. Thombs, Andrea Benedetti, The DEPRESsion Screening Data (DEPRESSD) EPDS Collaboration.
  Acta Psychiatrica Scandinavica, 2021.
  Keywords: integer programming | screening accuracy

• Shortening self‐report mental health symptom measures through optimal test assembly methods: Development and validation of the Patient Health Questionnaire Depression 4
  Miyabi Ishihara, Daphna Harel, Brooke Levis, Alexander W Levis, …, Brett D. Thombs.
  Depression and Anxiety, 2019.

Education

• Assessment of pedagogical practices and processes in low and middle income countries: Findings from secondary school classrooms in Uganda
  Edward Seidman, Sharon Kim, Mahjabeen Raza, Miyabi Ishihara, Peter F Halpin.
  Teaching and Teacher Education, 2018.
  Keywords: factor analysis | multilevel regression | classroom quality

Biosciences

• Highly developed social care of cooperative breeding of wasps (abstract)
  Miyabi Ishihara, Jeremy Field, Hiroshi Toyoizumi.
  Presented at SWARM, 2015.
  Keywords: stochastic model | regression | swarm behavior