Behrouz Babaki
Applied Research Scientist at Wise Systems, Inc.
Montreal, Quebec, Canada
Summary
👤
Senior🎓
Top SchoolBehrouz Babaki is an applied research scientist in Montreal with 11 years of experience bridging machine learning, combinatorial optimization, graphical models and AI planning to solve real-world decision problems. He has a PhD from KU Leuven and consecutive postdoctoral roles at Polytechnique Montréal and Mila, where he developed methods like graph neural networks to learn solvers and combined optimization with fairness-aware ML for applications from kidney allocation to planner improvement. Currently at Wise Systems, he translates research-grade hybrid approaches into production-ready solutions for routing and scheduling. Behrouz’s work uniquely blends deep learning with integer and constraint programming, and he often tackles problems at intersections—e.g., using probabilistic inference to inform combinatorial search—bringing both theoretical rigor and applied impact.
11 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at KU Leuven
Stackoverflow
81reputation
30kreached
7answers
0questions
Github Skills (25)
clustering-algorithm10
k-means-clustering10
clustering10
python8
kmeans8
algorithm8
cluster-analysis6
optimization6
dbscan6
sat6
partitioning6
machine-learning6
hierarchical-clustering6
artificial-intelligence6
constraint-programming5
Programming languages (3)
Github contributions (5)
Behrouz-Babaki/codeforces
Jul 2015 - Sep 2021
Contributions:15 pushes in 6 years 2 months
Behrouz-Babaki/MinSizeKmeans
Feb 2019 - Mar 2021
A python implementation of KMeans clustering with minimum cluster size constraint (Bradley et al., 2000)
Contributions:1 review, 8 commits, 9 PRs in 2 years
k-means-clusteringpythonconstrained-clusteringkmeans-clusteringclustering-algorithm
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