Oliver Hinder
Assistant Professor at University of Pittsburgh
Palo Alto, California, United States
Summary
👤
Senior🎓
Top SchoolOliver Hinder is an Assistant Professor and optimization researcher with 11 years of experience focused on efficient algorithms for finding local optima in continuous nonconvex problems. He splits his work between constrained optimization—developing interior point methods—and unconstrained first-order methods, with broader interests spanning market design, integer programming, machine scheduling, and machine learning. After a PhD in Operations Research from Stanford and a visiting postdoc at Google, he now leads research and teaching at the University of Pittsburgh while based in Palo Alto. Known for bridging rigorous theory and practical algorithms, he often targets problems where classical convex tools fall short, producing methods that scale to realistic, structured instances.
11 years of coding experience
3 years of employment as a software developer
Bachelor of Engineering with First Class Honors, Engineering Science, Bachelor of Engineering with First Class Honors, Engineering Science at University of AucklandDoctor of Philosophy (PhD), Operations Research, Doctor of Philosophy (PhD), Operations Research at Stanford University
Github Skills (32)
machine-learning10
google10
ai10
quadratic-programming8
julia8
mumps8
symmetry7
programming-language7
science7
hpc6
linear-algebra5
julialang5
matrix5
numerical5
optimization4
Programming languages (4)
Github contributions (5)
ohinder/OnePhase.jl
May 2017 - Jan 2022
Contributions:114 commits, 23 pushes, 6 comments in 4 years 9 months
ohinder/advanced_timer.jl
Nov 2015 - May 2021
Contributions:11 pushes, 1 branch, 1 issue in 5 years 6 months
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