Research problems in Big Data and Data Science

Speaker:  Sunil Kumar Vuppala – Bangalore, India
Topic(s):  Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing

Abstract

The talk covers introduction of big data and data science, high level research problems in 5 categories: Core Big data area to handle the scale, Handling noise and uncertainty in the data, Security and privacy aspects, Data Engineering and Intersection of Big data and Data science. The talk covers a research methodology to solve specified problems and top research labs to follow which are working in these areas.

Agenda:

Introduction to Big data and Data Science

AI vs ML vs DL

Data science life cycle 

Research categories and problems in Big data

Research issues in data science + Big data

Real world applications

Gartner Hype cycles

Summary of Top 20 Research problem statements for scholars in 5 categories

References of top research labs 

Q&A


About this Lecture

Number of Slides:  30.
Duration:  90 minutes
Languages Available:  English
Last Updated: 

Request this Lecture

To request this particular lecture, please complete this online form.

Request a Tour

To request a tour with this speaker, please complete this online form.

All requests will be sent to ACM headquarters for review.