Here is how we enhance AI decision-making and battle harmful algal blooms

Bradley's work addresses the negative public health and economic impacts caused by harmful algal blooms (HABs). The blooms can produce toxins and cyanobacteria that could cause skin irritation, nausea, and liver or neurological damage. The estimated economic impact of HABs in the U.S. is $10-$100 million. Bradley will investigate how wastewater treatment and agricultural discharge interact with HABS and explore ways to enhance the removal of nitrogen and phosphorus from wastewater, both critical nutrients for algal growth. 

“On the wastewater side, we’re concerned about organic nitrogen and phosphorus that aren’t easily removed in wastewater treatment,” Bradley said. “What I want to understand is both how we can improve removing those in wastewater, and then also how they interact with harmful algal blooms out in the environment.”

Ji is working to enhance the decision-making behind large language models and big data applications like 5G networks, health care and finance models. Multi-objective optimization (MOO) provides a framework for these models to identify the best trade-offs among competing objectives and requests. Ji's work will develop new theoretical and algorithmic foundations for MOO, propose efficient and scalable multi-objective bilevel optimization, and advance MOO frameworks by incorporating fairness concepts.