Year-long Research Programs

SAMSI’s research programs are large-scale efforts focusing on interfaces among statistics, applied mathematics and other disciplinary sciences. The programs typically run a full academic year. They involve long and short term research fellows from U.S. and international institutions, and SAMSI postdoctoral fellows. Graduate students from our partner universities and from other universities, both national and international, are active participants. The programs also engage researchers working in industry, governmental agencies and national laboratories.

Current Research Programs

Program on Statistical, Mathematical, and Computational Methods for Precision Medicine (PMED)

Essential to precision medicine are quantitative methods for translating heterogeneous data sources into actionable information to guide treatment decisions. Mathematical, statistical, and computational scientists have favored different approaches to this challenge. This SAMSI program will facilitate this critical interdisciplinary exchange by bringing together leading mathematical, statistical, computational, and health sciences researchers to pursue innovative, data-driven methodology for precision medicine.

August 1, 2018 – May 31, 2019

Model Uncertainty: Mathematical and Statistical (MUMS)

The primary goal of this SAMSI program brings together researchers from the UQ and MU communities to attack a variety of common goals. In addition, the MUMS program will also engage a myriad of disciplines and a diverse set of applications.

August 1, 2018 – May 31, 2019

Upcoming Programs (2019-2020)

Program on Games, Decisions, Risk and Reliability (GDRR)

This program will include game theory and adversarial risk analysis topics, relate these to decision theory, and also apply decision theory to risk analysis. An exciting aspect of the program will be to address non-standard utility functions that take account of the cost of memory, computation, and human effort to set up the analysis—these considerations are directly relevant to issues that arise in machine learning and data science.

Past Research Programs

To view our research programs from previous years, please CLICK HERE.