Daphne Cornelisse
PHD Candidate
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolDaphne Cornelisse is a PhD candidate in Transportation Engineering at NYU and a research scientist intern at NVIDIA with eight years of interdisciplinary experience at the intersection of reinforcement learning, simulation, and computational neuroscience. She has applied fast RL training techniques across industry labs including Waymo and academic groups at Harvard and Mount Sinai, translating cognitive science insights into scalable simulation pipelines. As founder of Negentropy she coached over 20 students to degree completion, demonstrating a rare blend of hands-on mentorship and research rigor (students’ average rating: 97/100). Comfortable moving between research and production settings, she brings strong machine learning foundations from a summa cum laude MSc in AI and practical ML and web development bootcamp training. Based in New York, she combines curiosity-driven experimentation with a proven track record of shipping reproducible RL workflows in fast environments.
8 years of coding experience
2 years of employment as a software developer
MSc. Artificial Intelligence (Summa cum laude), MSc. Artificial Intelligence (Summa cum laude) at Radboud UniversityMachine Learning Bootcamp, Artificial Intelligence, Machine Learning Bootcamp, Artificial Intelligence at Turing CollegeDoctor of Philosophy - PhD, Transportation Engineering, Doctor of Philosophy - PhD, Transportation Engineering at New York UniversityBSc. Liberal Arts & Sciences (Honours), Major Neuroscience, BSc. Liberal Arts & Sciences (Honours), Major Neuroscience at Erasmus University CollegeChinese Language Course, Chinese Language Course at Erasmus University Rotterdam
English, Chinese, French, Dutch
Github Skills (44)
simulator10
brian10
computational-neuroscience9
neurons9
simulation9
pytorch9
python9
machine-learning9
simulation-framework9
gpu9
code-generation9
deep-learning9
neuroscience9
spiking-neural-networks9
nbdev9
Programming languages (3)
Github contributions (5)
Emerge-Lab/gpudrive
Jun 2024 - Apr 2025
1 million FPS multi-agent driving simulator
Contributions:2 releases, 99 reviews, 136 PRs in 9 months
Emerge-Lab/nocturne_lab
Sep 2023 - Aug 2024
A data-driven, fast driving simulator for multi-agent coordination under partial observability.
Contributions:5 reviews, 51 PRs, 223 pushes in 11 months
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