Adolfo Escobedo

Enabling Circular Economies of Recyclable Materials Through Matrix Completion

Accurately filling in missing information in commodity flow data would allow us to design improved methods of systematic recycling.

Program: MORE

A Novel Approach to Perform Rank-One Updates in Machine Learning

Developing efficient and error-free machine learning algorithms would lead us to more equitable and informed decisions.

Program: MORE

Evaluating Collective Intelligence Strategies for Visual Detection

Studying how collecting and aggregating data from multiple people can best inform visual detection tasks.

Program: FURI

A Novel Approach to Perform Rank-one Updates in Machine Learning

Developing efficient and error-free machine learning algorithms would lead us to more equitable and informed decisions.

Program: MORE

Efficient Methodology for Assessing and Improving Secure Shredding Bin Service Sizing

Studying the benefit and cost structure of paper recycling methods will assist large corporations in improving their sustainability efforts.

Program: FURI

Input-elicitation Methods for Crowdsourced Human Computation

Investigating better ways to collect opinions from people will improve data quality and motivate less-biased crowdsourcing results.

Program: FURI

Integration of Renewables and Cost-Efficient Technologies in Transmission Expansion Planning

Modeling the optimizing techniques during extreme weather events will minimize the investment and operational costs of the electric power systems network.

Program: MORE

The Optimal Waste Reduction (OWR) Tool

Developing a prescriptive decision-making tool will help users set optimized economic, social and environmental goals for recycling waste materials.

Program: FURI

Application of Axiomatic Distance Calculation of Incomplete Rankings in Genomics

Program: MORE