Quintin Van Heerden
Optimisation & Decision Science Team Lead
Cape Town, Western Cape, South Africa
Summary
👤
Senior🎓
Top SchoolQuintin Van Heerden is an optimisation and decision-science leader with 14+ years of experience applying simulation, optimisation and data engineering to transport, logistics and urban systems. Currently leading the Optimisation & Decision Science team at Bash, he has built route solvers, combinatorial sourcing models, geospatial pipelines and serverless analytics platforms in production for supply-chain control towers. His research background—P.hD. work in simulation-optimisation and multi-agent freight contributions to the well-regarded MATSim project—underpins a pragmatic ability to turn academic models into scalable engineering solutions. Quintin combines hands-on back-end development with programme leadership, having led multi-year urban modelling projects, standardised public-transport data at provincial scale and mentored multidisciplinary teams. Based in Cape Town, he’s as comfortable writing neural nets for demand forecasting as he is designing LP fleet-mix models and infrastructure-as-code deployments.
14 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy - PhD, Industrial Engineering, Doctor of Philosophy - PhD, Industrial Engineering at Stellenbosch UniversityUniversity of Pretoria
English, Afrikaans, French, Spanish
Github Skills (8)
simulations10
simulation10
javas10
java10
data-structure5
algorithms5
algorithm5
data-structures5
Programming languages (3)
Github contributions (5)
matsim-org/matsim-libs
May 2012 - Mar 2014
Multi-Agent Transport Simulation
Role in this project:
Back-end Developer
Back-end DeveloperContributions:20 commits in 1 year 10 months
Contributions summary:Quintin contributed to the `matsim-libs` repository by implementing core back-end functionalities related to freight and agent-based transportation simulation. The commits showcase the creation of carrier plans and the simulation of vehicles using the freight contrib, indicating a focus on the underlying simulation logic. The user also added methods to generate scoring function- and replanning factories and implemented demand generation features within the project, highlighting involvement in multiple aspects of the project's core functionality.
agent-basedtransportation-planningagentagent-based-modelmatsim
quintinvh/quintinvh
Nov 2021 - Jan 2023
Contributions:5 pushes, 1 branch in 1 year 2 months
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