Daniel Young
Ph.D. Student
Daniel is a Ph.D. student working on using AI for social good, in particular using evolutionary algorithms to assist in decision making for policies such as climate change. He works at the Cognizant AI Lab and is part of Project Resilience, a nonprofit open-source collaboration with the UN to use AI for sustainable development. He is also interested in multi-agentic systems.
Homepage:
https://danyoungday.github.io/
Publications
Discovering Effective Policies for Land-Use Planning with Neuroevolution 2025
Daniel Young, Olivier Francon, Elliot Meyerson, Clemens Schwingshackl, Jacob Bieker, Hugo Cunha, Babak Hodjat, and Risto Miikkulainen, Environmental Data Science, Vol. 4 (2025), pp. e30.
Leveraging Evolutionary Surrogate-Assisted Prescription in Multi-Objective Chlorination Control Systems 2025
Rivaaj Monsia, Olivier Francon, Daniel Young, Risto Miikkulainen, arXiv:2508.19173 (2025).
NeuroSAN+NeuroAI: AI-assisted Decision-making through a Synergy of Technologies 2025
Risto Miikkulainen, Dan Fink, Olivier Francon, Babak Hodjat, Noravee Kanchanavatee, Elliot Meyerson, Xin Qiu, Darren Sargent, Hormoz Shahrzad, Deepak Singh, Jean Celestin Yamegni Noubeyo, and Daniel Young, Technical Report 2025-01, Cognizant AI Lab.
Labs
Currently affiliated with Neural Networks