About me

I am a tenured Associate Professor in the Department of Statistics and Actuarial Science at the University of Iowa (Go Hawkeyes!). I joined Iowa in Fall 2015 after postdoctoral research at SAMSI and Duke University, where I was mentored by David Dunson and Barbara Engelhardt. I received my Ph.D. in Statistics in 2013 from Purdue University under the guidance of Rebecca Doerge. My academic path in statistics began at IIT Kanpur, where I completed a five-year integrated M.Sc. in Mathematics and Scientific Computing in 2007.

My research focuses on scalable Bayesian computation, dimension reduction, and array-variate mixed models. I develop divide-and-conquer methods to scale posterior inference. Recently, my work has emphasized applications of array-variate models and high-dimensional Gaussian processes to neuroscience, including multimodal data from local field potentials, gene expression, and imaging.

I collaborate extensively with scientists and clinicians and teach students across a range of backgrounds. At Iowa, I developed and regularly teach two courses in statistical learning (launched in Fall 2016 and Spring 2023).

I like the following quote from ChatGPT (5):

May your likelihood be informative, your priors well-founded, and your posterior tightly concentrated near the truth. ChatGPT “Yoda”

Funding

My research has been supported by the Office of Naval Research, the National Science Foundation’s Division of Mathematical Sciences, and National Institue of Mental Health. Current support includes NSF DMS-2506058 (Co-PI), NIH R01 OD039332 (Co-Investigator with Rainbo Hultman and Hanna Stevens as MPIs), R01 AG089922 (Co-Investigator with Catherine Marcinkiewcz and Rainbo Hultman as MPIs), and R01 MH137086 (Co-Investigator with Rainbo Hultman as MPI).

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