Data Science: Recent Developments and Future Trends

Speaker:  Li Chen – Washington, DC, United States
Topic(s):  Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing

Abstract

Data contains science. How data is handled today is much different than the classical mathematical approach of using models to fit the data. Today, people are supposed to find rules and properties within the data set and sometimes among different data sets.

In this talk, we will explain data science and its relationship to BigData, cloud computing, and data mining. We also discuss current research problems in data science and provide concerns related to the data science industry. This talk will connect and group computer science, mathematics, information technology, social science, and other applications in order to give a comprehensive view of the future of data science. Emphasizing the bridge between computer science and math, we will explain why data science would serve as a tremendous engine to the development of the new computing and math theories.

Data science is about the study of: (1) The science of data, (2) Knowledge extraction from massive data sets (BigData) mainly using machine learning, (3) Data and data set relations, (4) BigData processing including tools such as Hadoop and Spark on cloud computing, and (5) Visualization of massive data and human–computer interaction.

In this talk, we give an overview of data mining and machine learning methods such as kNN, k-means, SVM, decision trees, PCA, and other popular methods. We also introduce timely problems for study including: smart search (also called the matrix completion problem or the Netflix problem), the subspace problem, financial data recovery, video tracking, and persistent data processing.  

For future research problems, we would like to discuss computing and algorithm design based on various MapReduce-based models. For applications, we provide a simple case study in image segmentation using MapReduce with detailed algorithm analysis.

About this Lecture

Number of Slides:  50
Duration:  60 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.