Erik M Lindgren

I am a graduate student at the University of Texas at Austin in the department of Electrical and Computer Engineering, where I am advised by Prof. Alex Dimakis. I am interested in machine learning, combinatorial optimization, and information theory. I received my bachelor's degree from Boston University.

I have interned at Google, where I worked on machine learning with the Ground Truth team, and Lattice Automation, where I worked on algorithms for synthetic biology.

You can contact me at erikml@utexas.edu.

Publications

Submodularity and Minimum Cost Intervention Design for Learning Causal Graphs
E. M. Lindgren, M. Kocaoglu, A. G. Dimakis, S. Vishwanath
NIPS DISCML Workshop, 2017 (contributed talk)

Exact MAP Inference by Avoiding Fractional Vertices
E. M. Lindgren, A. G. Dimakis, A. Klivans
[paper]
ICML, 2017

Leveraging Sparsity for Efficient Submodular Data Summarization
[paper] [video]
E. M. Lindgren, S. Wu, A. G. Dimakis
NIPS, 2016

A Rule-Based Design Specification Language for Synthetic Biology
[journal link]
E. Oberortner, S. Bhatia, E. M. Lindgren, D. Densmore
ACM Journal on Emerging Technologies in Computing Systems, 2014