Speaker "Dr. SK Sharma" Details Back



Using deep learning to identify and engage selective, high-value audiences of digital content


The proliferation and adoption of streaming over the past few years has created a unique marketing challenge in that while content creators now benefit from virtually unlimited shelf space to showcase their intellectual property, the actual path to consumer discovery and engagement can often remain confounding and stochastic. Clearly, content owners navigating this brave new world must be able to rapidly identify which assets in their portfolio have the greatest potential for increased monetization across specific consumer groups, and ultimately, chart a course for how to reach and continually engage these consumers. While traditional recommendation systems like collaborative filtering adequately address the need to surface content to consumers, the inverse problem of finding high value audiences for specific songs and artists remains a challenge in the music industry, particularly after the recent and necessary implementation of GDPR. Here we outline how our Insights & Analytics team has leveraged innovations and advances in deep learning (i.e., unsupervised variational autoencoder models), to solve this grand marketing challenge for creators, owners, and managers of intellectual property in the music space.


-Senior analytics, digital marketing, and AI executive with a Caltech PhD and a solid track record conceptualizing and implementing major initiatives at Fortune 500 and PE portfolio companies gained through both technological leadership and operational experience in the VC, IP, and management consulting industries. -Functional and management expertise in productization of data science (machine learning, artificial intelligence), predictive/marketing analytics and insights, corporate development and strategy, intellectual property, organizational restructuring, and strategic sourcing. -Strong ability to connect analytical methods to business insights, decision recommendations, and developing human capital. -Accomplished computational scientist, digital innovator, and CTO with 15+ peer-reviewed research publications and 40+ presentations at international conferences across the fields of chemical physics and computational biophysics, along with a book chapter on high performance grid computing.