Simon Spoorendonk Research-level output at startup velocity. Copenhagen, Denmark · simon@spoorendonk.dk GitHub: https://github.com/spoorendonk LinkedIn: https://www.linkedin.com/in/spoorendonk/ Google Scholar: https://scholar.google.dk/citations?user=Sy8INIQAAAAJ&hl=en ORCID: https://orcid.org/0009-0007-4304-6956 Web: https://spoorendonk.dk/ Last updated: 2026-09-03. Canonical URL: https://spoorendonk.dk/cv.txt PROFILE ------- PhD computer scientist. Three-time founder in Copenhagen, two companies acquired. Twenty years of optimization and engineering — routing, scheduling, network flow. Peer-reviewed publications in Operations Research, Transportation Science, EJOR and Networks, plus four current preprints. 1,500+ citations, h-index 15. My work usually starts with someone talking about a problem they can’t solve. If that sounds familiar, write to me. EXPERIENCE ---------- Research engineering (2026 – present) Optimization and modern AI: solver libraries, published research, and systems built with AI coding agents. Four preprints since February: two new, two rewritten from the ground up. Founder & CEO, Flowty (2019 – 2026) Optimization solver for planning and scheduling in logistics. Tech lead on the solver and its architecture. Delivered in production with Ørsted; pilots with DHL, Svitzer and Unifeeder. Co-Founder & CTO, Onlaw (2017 – 2018) Legal research platform built on an NLP pipeline for semantic search over unstructured documents. Acquired by Karnov Group in 2020. Co-Founder & CTO, Halfspace (2013 – 2018) AI and data science consultancy for maritime, energy, insurance and the public sector. Acquired by Accenture in 2025. Software developer, Edlund A/S (2012 – 2013) Actuarial software for pension and insurance, where correct and auditable results were the product. Independent consultant, Freelance (2011 – 2019) AI and decision-support projects for insurance, pension and asset allocation clients. Postdoc, DTU (2009 – 2011) Principal investigator on a DKK 1.5M grant from the Danish Council for Independent Research. Decomposition algorithms for transportation and scheduling, in collaboration with Maersk Line. PhD student, University of Copenhagen (2005 – 2008) Thesis: Cut and Column Generation. Visiting PhD student, GERAD, Montréal (2007) Resource-constrained shortest path algorithms with Guy Desaulniers and Jacques Desrosiers. Software developer, WHO Regional Office for Europe (2001 – 2005) Help desk assistant, WHO Regional Office for Europe (1999 – 2001) ADVISORY AND TEACHING --------------------- External examiner, Censorkorpset i Datalogi, Denmark (2026 – present) The national external examiner corps for computer science, covering the Danish universities. Startup mentor, DTU Science Park (2025 – present) Coaching deep-tech founders on technology choices and scaling. External examiner, DTU Management Engineering (2012 – present) External examiner for master's theses in operations research and optimization. External lecturer, DTU Management Engineering (2013 – 2014) EDUCATION --------- PhD in Computer Science, University of Copenhagen (2008) Thesis: Cut and Column Generation. MSc in Computer Science, University of Copenhagen (2005) SELECTED PUBLICATIONS --------------------- Subset-row inequalities applied to the vehicle-routing problem with time windows M. Jepsen, B. Petersen, S. Spoorendonk, D. Pisinger. Operations Research 56(2), 2008. https://doi.org/10.1287/opre.1070.0449 A branch-and-cut algorithm for the symmetric two-echelon capacitated vehicle routing problem M. Jepsen, S. Spoorendonk, S. Ropke. Transportation Science 47(1), 2013. https://doi.org/10.1287/trsc.1110.0399 Liner shipping cargo allocation with repositioning of empty containers B. D. Brouer, D. Pisinger, S. Spoorendonk. INFOR 49(2), 2011. https://doi.org/10.3138/infor.49.2.109 A hybrid adaptive large neighborhood search heuristic for lot-sizing with setup times L. F. Muller, S. Spoorendonk, D. Pisinger. European Journal of Operational Research 218(3), 2012. https://doi.org/10.1016/j.ejor.2011.11.036 Cutting planes for branch-and-price algorithms G. Desaulniers, J. Desrosiers, S. Spoorendonk. Networks 58(4), 2011. https://doi.org/10.1002/net.20471 A branch-and-cut algorithm for the capacitated profitable tour problem M. K. Jepsen, B. Petersen, S. Spoorendonk, D. Pisinger. Discrete Optimization 14, 2014. https://doi.org/10.1016/j.disopt.2014.08.001 PREPRINTS --------- An open, reproducible branch-and-cut for the capacitated profitable tour problem: a component study S. Spoorendonk. arXiv:2607.04497, 2026. https://arxiv.org/abs/2607.04497 bucket-graph-spprc: an extensible C++ library for the shortest path problem with resource constraints S. Spoorendonk. arXiv:2606.30847, 2026. https://arxiv.org/abs/2606.30847 A parallel pull labelling algorithm for the resource constrained shortest path problem B. Petersen, S. Spoorendonk. arXiv:2511.01397, 2025. https://arxiv.org/abs/2511.01397 Tree-based formulation for the multi-commodity flow problem S. Spoorendonk, B. Petersen. arXiv:2509.24656, 2025. https://arxiv.org/abs/2509.24656 OPEN SOURCE ----------- bucket-graph-spprc — Header-only C++23 bucket graph labeling for the SPPRC — the pricing subproblem in vehicle routing column generation. https://github.com/spoorendonk/bucket-graph-spprc cptp — Branch-and-cut solver for the capacitated profitable tour problem and open s–t path variants. https://github.com/spoorendonk/cptp coso — Typed model API and C++23 structure-aware engine for routing, scheduling, assignment, packing, network flow and lot sizing (early development). https://github.com/spoorendonk/coso mcfcg — Column generation for minimum-cost multicommodity flow with path- and tree-based Dantzig-Wolfe decompositions. https://github.com/spoorendonk/mcfcg mip-heuristics — Four modern MIP primal heuristics (FeasibilityJump, FPR, LocalMIP, Scylla) implemented and benchmarked inside HiGHS. https://github.com/spoorendonk/mip-heuristics cbls — Constraint-based local search (ViolationLS) for mixed discrete-continuous optimization — C++23 with Python bindings. https://github.com/spoorendonk/cbls mipx — A from-scratch branch-and-cut MIP solver in C++23 with Python bindings (early development). https://github.com/spoorendonk/mipx md2mip — Compile natural-language optimization models into standalone solver CLIs (Python + HiGHS). https://github.com/spoorendonk/md2mip