Data Science: Recent Developments and Future Trends

Jan 30, 2017 · Herndon, United States of America

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.

Dr. Li Chen is currently an Associate Professor of computer science at the University of the District of Columbia. He received his BS, MS, and PhD in CS from Wuhan University (1982), Utah State University (1995), and the University of Bedfordshire (2001), respectively.   Chen has worked in both academia and industry. He was a lecturer at South East University and Wuhan University in China before serving as a visiting assistant professor at the University of North Dakota, visiting associate professor at the University of Maryland, and adjunct professor at Virginia Tech. In industry, he worked for companies as a senior software engineer.

Chen has given professional talks on various topics in many universities and colleges including the University of Toronto, University of Maryland, George Mason University, Rutgers University, NIH, and Georgetown University.  He was a visitor of DIMACS (Rutgers-Princeton) and a Scientific Researcher in the Fields Institute at the University of Toronto.

Chen is an ACM Distinguished Speaker .

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If you would like to present at a future Meetup, contact Sarah at [masked]. 

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6:30 pm - 7:00 pm - Pizza & Drinks  

7:00 pm - Presentations begin

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