Original article was published by Angela Wilkins on Artificial Intelligence on Medium
Ken Kennedy Institute Conference: COVID-19 and the influence on Data Science
The virtual Ken Kennedy Institute Data Science Conference on Oct. 26–28 2020 will focus on COVID-19 and how the pandemic has influenced the use of data and data science. Speakers will discuss everything from the genome analysis to data governance, from human behavior to water treatment plants, and will highlight the role of computing hardware and software in these endeavors.
The annual Ken Kennedy Data Science Conference has been interested in exposing how data science can be used to address interesting challenges for translating data to knowledge through advances in data engineering, analytics, machine learning, deep learning, reinforcement learning, and more broadly, artificial intelligence.
Recognizing that discovery and innovation happens at interfaces of disciplines and communities, the conference aims to bring together a diverse set of people from multiple communities spanning academia and industry. In hopes of improving connections in these virtual times, we have implemented a virtual conference platform that prioritizes networking matches based on each attendee’s interests and goals. When viewing matches, attendees can send a meeting request and message, or start a video chat directly in the platform.
The conference will feature talks by leading experts, which will be complemented by thematically organized sessions with talks selected from submitted abstracts, such as COVID-19, algorithms & foundations, business impact, and healthcare. We will also have a student poster session, networking breaks and sponsor booths. The poster session is open to applicants until Oct. 12.
This year the conference was expanded to include a special collaboration with MD Anderson that takes place on Wednesday and will offer a discussion on the D3CODE effort. The Data-Driven Determinants for COVID-19 Oncology Discovery Effort (D3CODE) was established to create a cross-functional, institution-wide data science initiative linked to understand cancer in context of the pandemic.