Carleton Coffrin is a staff scientist in Los Alamos National Laboratory’s Advanced Network Science Initiative. His research interests focus on how optimization algorithms can be applied to applications on infrastructure networks. His background spans many forms of optimization including mathematical programing, constraint programming, and local search. Recently Carleton has been exploring online learning via open-online courses and youtube videos as well was novel computing architectures such as, quantum computers, neuromorphic computers and memristors.
PhD in Artificial Intelligence, 2012
Brown University
MS in Computer Science, 2010
Brown University
BS in Computer Science, 2006
University of Connecticut
BFA in Technical Theatre, 2006
University of Connecticut
Co-Instructor with Pascal Van Hentenryck, Discrete Optimization (delivered by Coursera) Melbourne University, Melbourne, VIC, 2013 - Present
Co-Instructor with Peter Stuckey, Modeling for Discrete Optimization (delivered by Coursera) Melbourne University, Melbourne, VIC, 2015
Teaching Assistant for Peter Stuckey, Modeling for Discrete Optimization (COMP90046) Melbourne University, Melbourne, VIC, 2014 and 2015
Graduate Teaching Assistant for Claire Mathieu, Design and Analysis of Algorithms (CSCI1570) Brown University, Providence, RI, 2010 and 2012
Graduate Teaching Assistant for Pascal Van Hentenryck, Solving Hard Problems in Combinatorial Optimization: Theory and Systems (CSCI2580) Brown University, Providence, RI, 2011
2019 R&D 100 Award for Severe Contingency Solver: Electric Power Transmission
Los Alamos National Laboratory 2019 Distinguished Performance Award for Critical Infrastructure Optimization Software
Los Alamos National Laboratory 2018 LAAP Award for Leadership in the Quantum Computation Summer School
Los Alamos National Laboratory 2018 LAAP Award for C2S Development Efforts
Los Alamos National Laboratory 2017 LAAP Award for Exploration of Quantum Computation
Los Alamos National Laboratory 2017 Early Career Researcher Award for Large-Scale Nonlinear Optimization via Cloud Computing
PES 2014, Application of Modern Heuristic Optimization Algorithms for Solving Optimal Power Flow Problems, finalist (1 of 5), for Heuristic MINLP for Optimal Power Flow Problems
Northeastern INFORMS 2011, Student Poster Competition, First Place, for Vehicle Routing for the Last Mile of Power System Restoration
INFORMS 2010 Doing Good with Good OR Competition finalist (1 of 6), for Strategic Planning for Disaster Recovery with Stochastic Last Mile Distribution
Los Alamos National Laboratory 2010 LAAP Award for Outstanding Summer Research in Power Grid Restoration for Disaster Recovery