Tommy Van Der Vorst
Partner at Dialogic innovatie & interactie
Randstad, Netherlands
Summary
🤩
Rockstar🎓
Top SchoolTommy Van Der Vorst is a partner and senior researcher at Dialogic with 21 years of experience advising governments and enterprises on telecommunications, 5G and AI/ML strategy. He combines deep technical fluency and software development experience with policy-minded, data-driven research to rapidly prototype proofs-of-concept and performance-tuned models. His client portfolio spans OECD, ITU, Eurostat, major Dutch banks, regulators and ministries, reflecting strength in both public policy and commercial contexts. An active open-source contributor, he has contributed performance-focused Rust/WebGPU work to an ONNX runtime, bringing low-level optimization skills to high-level strategy. Outside work he balances technical hobbies—app development, electronics and video editing—with outdoor sports like snowboarding and road biking, and is learning Italian and cooking.
21 years of coding experience
13 years of employment as a software developer
MSc, Innovation sciences, MSc, Innovation sciences at Università Commerciale 'Luigi Bocconi'Gymnasium, N&T, with merit, Gymnasium, N&T, with merit at Sint-Janslyceum 's-HertogenboschMSc, Innovation Sciences, with merit, MSc, Innovation Sciences, with merit at Eindhoven University of Technology
English, Dutch, German, French, Italian
Stackoverflow
11reputation
3kreached
1answer
0questions
Github Skills (7)
rust10
webassembly10
onnx10
webgpu10
performance-optimization10
wgsl9
swift6
Programming languages (15)
Github contributions (5)
webonnx/wonnx
Dec 2021 - Sep 2022
A WebGPU-accelerated ONNX inference run-time written 100% in Rust, ready for native and the web
Role in this project:
Back-end Developer and Performance Engineer
Back-end Developer and Performance EngineerContributions:6 releases, 34 reviews, 294 commits in 9 months
Contributions summary:Tommy primarily contributed to the development of a WebGPU-accelerated ONNX runtime in Rust, focusing on feature implementations and performance optimizations. They added functionality to the example code, integrated templates into the binary, and refactored the codebase to correct and improve shader execution. The user also made efforts to refine and clarify code, address bugs and add test cases for existing functions. The user optimized the model's computational performance through implementation of new shader code and other general optimization techniques.
pytorchrustgpuacceleratedinference
pixelspark/ll.js
Sep 2013 - Sep 2016
Contributions:9 commits, 3 PRs, 5 pushes in 3 years
descentrecursiverecursive-descent-parserparser-generatorparser
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