Happy to report that we just received a gift from Adobe to pursue innovative machine-learning approaches for arts-inspired physics-based image synthesis. Thank you Adobe.
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TWIML Podcast on Geometry and Machine Learning
Glad to have been featured by TWIML on their weekly podcast on #machinelearning. I discussed our recent work on enhancing the invariant properties of #neuralnetworks connecting areas as diverse as physics, biomechanics, differential geometry, with a lot of intuition along the way. TWIML Podcast with Sam Charrington
NSF RAPID on COVID-19 modeling
Proud to be part of a team to receive a NSF RAPID on graph predictive models for COVID-19 modeling. Led by Gautam Dasarathy (EE), the team additionally includes Doug Cochran (Math), Huan Liu (CS), Patricia Solis (Geography, KER).
Upcoming talks, SIAM, DiffCVML, Notre Dame Math, TGDA@Ohio State
Honored to be invited for several talks this spring and summer. SIAM Mathematics of Data Science, DiffCVML workshop in conjunction with CVPR 2020, Math Department Seminar at the University of Notre Dame, and the TGDA@Ohio-State NSF Tripods Institute. Thank you 🙏
Awarded R01 for wearables and Riemannian computing
Humbled to announce that a team comprising me (AME + ECE), and Matt Buman (CHS), Anuj Srivastava (FSU, applied math), were just awarded a NIH R01. The title of the grant is "Dense life-log health analytics from wearable sensors using functional analysis and Riemannian geometry". Very excited !!
Pavan Turaga 