Dear colleagues,

We are excited to share that three joint teams from UIC and Argonne National Laboratory have been selected for the George Crabtree Institute for Discovery’s Convergence Intelligence Seed Funding Program. These teams are leveraging artificial intelligence and data science to enhance how we observe, measure and understand natural phenomena.

The award represents a two-year commitment from each institution worth $225,000 per year, with each principal investigator receiving $75,000 annually. Over 50 applications were submitted, spanning disciplines from medical imaging and drug discovery to materials characterization, environmental monitoring and manufacturing optimization.

Congratulations to each team! Read on to learn more about their research.

Light-microscopy-based brain connectomics reconstruction via machine learning and high-performance computing | Ruixuan Gao (UIC) and Tom Uram (Argonne National Laboratory)

Developing machine learning methods and high-performance computing infrastructure to enable scalable, petabyte-scale reconstruction of whole-brain neuronal connectivity from advanced light-microscopy imaging data.

AI-enabled multi-electrode sensor array for detection and quantification of emerging contaminants | Ahmed Abokifa (UIC) and Jeffrey Elam (Argonne National Laboratory)

Developing machine-learning methods and advanced sensing platforms to enable real-time detection, identification and quantification of emerging contaminants, including PFAS, in complex water matrices by leveraging high-dimensional electrochemical signal data generated from multi-electrode sensor arrays.

Predictive Latent Models of Deformable Surgical Field Dynamics | Milos Zefran (UIC) and Neil Getty (Argonne National Laboratory)

Developing machine-learning methods and high-performance computing infrastructure to enable predictive latent modeling of deformable surgical field dynamics from large-scale robotic endoscopic imaging data.

For more information, please contact:
Jordi Cabana
jcabana@uic.edu
papka@anl.gov