Dimension Reduction

Illinois Tech applied mathematics professor Fred Hickernell honored as SIAM fellow

Illinois Tech Professor of Applied Mathematics Fred Hickernell has been named a SIAM fellow for his outstanding research and contributions to high-dimensional integration and approximation. He is developing software libraries that make cutting-edge computational methods accessible to researchers.

A manifold fitting approach for high-dimensional data reduction beyond Euclidean space

A new technique accurately describes high-dimensional data using lower-dimensional smooth structures, overcoming the limitations of traditional methods. The approach achieves cutting-edge estimation accuracy and convergence rates while enhancing computational efficiency through GANs.

AI technology for safer integrated analysis of data held by multiple organizations

A research team at the University of Tsukuba has developed a secure AI technology that allows for the shared analysis of personal and identifiable data from multiple organizations. This will enhance the accuracy of AI analysis, particularly in disease prediction and educational effectiveness.

Garmin GPSMAP 67i with inReach

Garmin GPSMAP 67i with inReach provides rugged GNSS navigation, satellite messaging, and SOS for backcountry geology and climate field teams.

Researchers develop equations to prevent the collapse of our globe’s most imperiled ecosystems

A team led by Jianxi Gao developed equations to measure and compare distances to tipping points across various mutualistic systems, allowing for the triage of declining ecosystems. This method enables the identification of areas that need intervention most urgently, providing a critical sense of urgency to mobilize resources.