Damian Dailisan
Postdoctoral Researcher at ETH Zürich
Zurich, Zurich, Switzerland
Summary
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Senior🎓
Top SchoolDamian Dailisan is a postdoctoral researcher and data scientist with 12 years of experience applying reinforcement learning, large language models, and computational modeling to smart-city mobility and infrastructure. Based at ETH Zürich, he leads projects on decentralized traffic control and adaptive systems, blending deep RL with domain-specific simulators to reduce congestion and improve urban decision-making. He has a strong track record translating research into real-world impact—leading the MINERVA smart city effort and contributing code enhancements to the widely used Flow RL traffic framework to improve simulator interoperability. A former startup co-founder and Chief Science Officer, Damian pairs academic rigor (PhD in Physics, Most Outstanding Ph.D. Graduate) with product-minded delivery across Europe, Asia, and North America. He is multilingual (English, Filipino, German B1–B2) and teaches complex social-systems modeling, reflecting a talent for communicating technical ideas to diverse audiences. Open to applied-AI and mobility roles in Zurich and Switzerland, he focuses on ethically grounded, deployable AI for transport and infrastructure.
12 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD Physics, Physics, Most Outstanding Ph.D. Graduate, Doctor of Philosophy - PhD Physics, Physics, Most Outstanding Ph.D. Graduate at University of the Philippines
German, English, Filipino, Japanese
Stackoverflow
31reputation
631reached
0answers
1question
Github Skills (8)
web-framework10
python10
reinforcement-learning10
backend9
automation-testing9
automation9
automations9
bokeh6
Programming languages (9)
Github contributions (5)
flow-project/flow
Sep 2019 - Mar 2021
Computational framework for reinforcement learning in traffic control
Role in this project:
Back-end Developer
Back-end DeveloperContributions:87 commits, 10 PRs, 53 pushes in 1 year 6 months
Contributions summary:Damian made several modifications to the project's codebase, primarily focusing on the `flow/utils/registry.py` and `flow/utils/rllib.py` files. Their contributions involve enhancing the environment registration process and improving the compatibility of the codebase with different versions, potentially in the context of reinforcement learning environments. Furthermore, they also removed trailing whitespace, and added some functionalities on the utility and visualization files. These changes collectively indicate a focus on improving the core functionality and usability of the Flow framework.
autonomousreinforcement-learningvehicle-controldeep-reinforcement-learningbenchmark
temetski/temetski.github.io
May 2016 - Mar 2025
Contributions:1 PR, 39 pushes, 3 branches in 8 years 11 months
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