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.
Optimizing Chlorination in Water Distribution Systems via Surrogate-assisted Neuroevolution Rivaaj Monsia, Daniel Young, Olivier Francon, Risto Miikkulainen To Appear In Proceedings of the Genetic and Evolutionary Computation Conference, 2026. 2026

Discovering Effective Policies for Land-Use Planning with Neuroevolution Daniel Young, Olivier Francon, Elliot Meyerson, Clemens Schwingshackl, Jacob Bieker, Hugo Cunha, Bab... Environmental Data Science, 4:e30, 2025. 2025

Leveraging Evolutionary Surrogate-Assisted Prescription in Multi-Objective Chlorination Control Systems Rivaaj Monsia, Olivier Francon, Daniel Young, Risto Miikkulainen arXiv:2508.19173, 2025. 2025

NeuroSAN+NeuroAI: AI-assisted Decision-making through a Synergy of Technologies Risto Miikkulainen, Dan Fink, Olivier Francon, Babak Hodjat, Noravee Kanchanavatee, Elliot Meyerson,... Technical Report 2025-01, Cognizant AI Lab, San Francisco, CA, 2025. 2025