We are part of a team led by Johns Hopkins, funded by the DARPA TIAMAT program, to develop new techniques for autonomy transfer! https://iaa.jhu.edu/multimillion-dollar-darpa-grant-to-support-transfer-of-autonomy-between-environments/

We are proud to be part of the ExpandAI award with the UT-Austin NSF AI Institute on the Foundations of Machine Learning (IFML). The awards are aimed at "Expanding AI Innovation through Capacity Building and Partnerships program, NSF is supporting projects that are diversifying AI research across the U.S." The ASU award will leverage expertise… Continue reading ExpandAI Award: ASU + UT-Austin IFML on Pervasive Systems

We are pleased to bring a diverse set of work spanning geometry, generative-AI, and AI-art to CVPR2023. Main conference paper + highlight: PolyINR https://lnkd.in/d7v6uCpi (Rajhans Singh and Ankita Shukla) Deep learning for Geometric Computing workshop paper: Deep Geometric Moment https://lnkd.in/d6tRkeZQ (Rajhans Singh and Ankita Shukla) Generative Models for Computer Vision workshop paper with Adobe Research… Continue reading CVPR 2023

We received a 18 month Phase 1 planning grant from the NSF PIPP program, with a large team consisting of Patricia Solis (KER + SGSUP), Visar Berisha (CHS + ECEE), Giulia Pedrielli (SCAI), Gautam Dasarathy (ECEE), Lalitha Sankar (ECEE), Daniel Rivera (SEMTE), Laimonas Kelbauskas (KE), Ni Trieu (SCAI + BioDesign), Michael Simeone (ASU Library Data Science and Analytics), Timothy… Continue reading NSF Predictive Intelligence for Pandemic Prevention

Pavan Turaga and Max Bernstein of the Geometric Media Lab receive a gift from Adobe Research, to investigate the role of machine learning techniques in the future mobile filmmaking practices.