Dan Adler is a PhD Candidate in Information Science at Cornell University. His work focuses on the implementation of data-driven measurement solutions in healthcare, focusing specifically on mental and behavioral healthcare.

Dan has conducted quantitative work, developing and validating machine learning models to measure symptoms of depression and schizophrenia, as well as qualitative work, thinking about tensions surrounding the implementation of these tools, and how we can improve evidence generation in data-driven mental health measurement research.

At Cornell, Dan is advised by Tanzeem Choudhury, and receives supervisory support from Deborah Estrin and Fei Wang.