Recent Work
Duality Theory for Balancing Weights:
We derive a dual formulation of minimax weighting estimators for causal inference and domain adaptation based on general classes of outcome functions. Accepted at AISTATS 2022.
Model-based RL and Causal Inference:
Leveraging structure on both the policy and the dynamics of an MDP to get sharper lower bounds for off-policy evaluation with unobserved confounding. Presented at ICML 2021.
When Can We Achieve Small Error in Observational Causal Inference?
A characterization of the error of reweighting estimators for the counterfactual mean using two terms, an integral probability metric and a phi-divergence. Presented at the Causal Assumptions 2021 Workshop.
Work in Progress
Distribution of Wealth in Two Asset Models:
Dynamic models of household wealth with income shocks and both liquid and illiquid assets. Emphasis on the relationship between housing wealth, income uncertainty, and debt.
Income Uncertainty Over Long Horizons:
Assessing the predictability of income trajectories over spans of 10-30 years using administrative tax records from Iceland. Emphasis on the joint evolution of income, assets, and housing.
Previous Publications
Accelerating Genomic Data Analytics with Composable Hardware Acceleration Framework. Tae Jun Ham, David Bruns-Smith, Brendan Sweeney, Yejin Lee, Seong Hoon Seo, U. Gyeong Song, Young H. Oh, Krste Asanovic, Jae W. Lee, and Lisa Wu Wills. IEEE Micro (2021). Genesis: a hardware acceleration framework for genomic data analysis. Tae Jun Ham, David Bruns-Smith, Brendan Sweeney, Yejin Lee, Seong Hoon Seo, U. Gyeong Song, Young H. Oh, Krste Asanovic, Jae W. Lee, and Lisa Wu Wills. International Symposium on Computer Architecture (ISCA), 2020. IEEE Micro Top Picks. Enhancing network visibility and security through tensor analysis. Muthu Baskaran, Thomas Henretty, James Ezick, Richard Lethin, and David Bruns-Smith. Future Generation Computer Systems, 2019. Fpga accelerated indel realignment in the cloud. Lisa Wu, David Bruns-Smith, Frank Nothaft, Qijing Huang, Sagar Karandikar, Johnny Le, Andrew Lin, Howard Mao, Brendan Sweeney, Krste Asanovic, and David Patterson. IEEE International Symposium on High Performance Computer Architecture (HPCA), 2019. Memory-efficient parallel tensor decompositions. Muthu Baskaran, Tom Henretty, Benoit Pradelle, M. Harper Langston, David Bruns-Smith, James Ezick, and Richard Lethin. IEEE High Performance Extreme Computing Conference (HPEC), 2017. Best Paper Finalist A quantitative and qualitative analysis of tensor decompositions on spatiotemporal data. Tom Henretty, Muthu Baskaran, James Ezick, David Bruns-Smith, and Tyler A Simon. IEEE High Performance Extreme Computing Conference (HPEC), 2017. Cyber security through multidimensional data decompositions. David Bruns-Smith, Muthu M. Baskaran, James Ezick, Tom Henretty, and Richard Lethin. Cybersecurity Symposium (CYBERSEC), 2016.