By integrating advanced technology, scientific innovation, and insights from our extensive network of partners, UConn’s Institute of the Environment and Energy generates knowledge that drives better decision-making for people, health, energy, food, and water. Viewed through the lens of sustainability, artificial intelligence, and climate change, these insights equip industry, agencies, and communities with the tools to anticipate risk, seize opportunities, and create a thriving, sustainable future.

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Research Highlights
Harnessing Source Heterogeneity for Cluster-Structured Transfer Learning

Harnessing Source Heterogeneity for Cluster-Structured Transfer Learning
IoEE-affiliated author(s): Kun Chen
Photo: Adobe Stock
Scalable Counterfactual Risk Estimation for Rare Events in Longitudinal Data

Scalable Counterfactual Risk Estimation for Rare Events in Longitudinal Data
IoEE-affiliated author(s): Kun Chen
Photo: Adobe Stock
Phase Shift Modulation and Compensation with NPV Observer in Single-Phase 5L-ANPC-FC Inverter

Phase Shift Modulation and Compensation with NPV Observer in Single-Phase 5L-ANPC-FC Inverter
IoEE-affiliated author(s): Ali Bazzi
Photo: Figure 1
Analytical Modeling of Slot Leakage Inductance for Hairpin Windings

Analytical Modeling of Slot Leakage Inductance for Hairpin Windings
IoEE-affiliated author(s): Ali Bazzi
Photo: Figure 9
Bayesian Model Merging

