Chief Executive Officer
I am a leader on a global business, Amazon Machine Learning (ML) Solutions Lab, whose mission is to work with companies and organizations from all industries to solve their business needs using machine learning. I have delivered high-impact ML products and solutions in finance (e.g., Bloomberg, JP Morgan Chase), healthcare and life sciences (e.g., Genentech, Roche), sports (e.g., NFL, Formula 1), and other sectors. Featured in articles by Forbes, Canaltech, Gartner, Intelligent Automation, Exame, Stadia Magazine, and more. I am passionate about making ML accessible to all and making the technology industry more diverse.
Multi-Tensor Decompositions for Personalized Pediatric Glioma Diagnostics and Prognostics
Comprehensive information on the genetics of pediatric gliomas is necessary in the search for effective diagnostic and prognostic tests, targets and treatments. Researchers will apply recently developed algorithms, used by computers to analyze data, to information from the Pediatric Brain Tumor Atlas in hopes of developing novel tests and therapies.
Sri Priya Ponnapalli
High-grade Gliomas (HGG) or astrocytomas in children nearly always result in a dismal prognosis. Although novel therapeutic approaches are currently in development, preclinical testing has been limited, due to a lack of pediatric-specific HGG preclinical models. These models are needed to help test
Low-Grade Gliomas also called astrocytomas are the most common cancer of the central nervous system in children. They represent a heterogeneous group of tumors that can be discovered anywhere within the brain or spinal cord. Although surgical resection may be curative, up to 20% of children still su