Christopher Harshaw
Assistant Professor at Columbia University
New Haven, Connecticut, United States
Summary
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Senior🎓
Top SchoolChristopher Harshaw is an Assistant Professor of Statistics at Columbia University who brings a decade of experience at the nexus of algorithms, computation, and causal inference. His research develops algorithmic tools to improve the design and analysis of randomized experiments, with particular focus on interference and sequential experimentation. Trained in computer science (PhD, Yale) under advisors Dan Spielman and Amin Karbasi, he blends rigorous theoretical work with practical experimental design. After a postdoctoral fellowship at UC Berkeley, he now leads research that bridges optimization and causal methods, applying computational perspectives to statistical problems. Based in New Haven, he prefers email contact and maintains a concise public footprint while actively advancing methods that make experiments more robust and computationally efficient.
10 years of coding experience
Bachelor of Science (B.S.), Electrical and Computer Engineering, Bachelor of Science (B.S.), Electrical and Computer Engineering at Rice UniversityDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Yale University
Stackoverflow
155reputation
2kreached
1answer
2questions
Github Skills (13)
graph-algorithms6
algorithm6
np-hard6
iterator6
gurobi6
graph-coloring6
julia6
graph-theory6
predict4
stock3
flask2
machine-learning2
python2
Programming languages (2)
Github contributions (5)
crharshaw/GSWDesign.jl
Jan 2020 - Mar 2020
An efficient method for sampling from the Gram--Schmidt Walk Design.
Contributions:5 commits, 1 PR, 16 pushes in 2 months
crharshaw/SubmodularGreedy.jl
Apr 2021 - Jul 2021
Efficient greedy-based methods for constrained submodular optimization.
Contributions:9 commits, 7 pushes, 1 branch in 3 months
juliasubmodular-optimization
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