Location:  STEW 302-306

Time:  8:30 a.m. – 5:00 p.m.

Registration: www.conf.purdue.edu/salvendy

Gavriel Salvendy 3rd International Symposium on Frontiers in Industrial Engineering:

Information Engineering

September 29 & 30, 2015 - Purdue University

With the advent of the digital era, information has emerged as a co-equal building block of modern enterprises—alongside other components such as human agents, tangible materials and financial resources. Thus, aptly, the modern economy is often described as information economy. The growing importance of information, as a resource, has led to renewed interest in information engineering—a discipline that seeks to foster a structured engineering approach to the mining, storage, transportation, sharing, management and utilization of information.

Recognizing the vast impact that information engineering is poised to have on the industries, as well as the society, of the future, it has been chosen as the theme for the third Gavriel Salvendy International Symposium on the Frontiers of Industrial Engineering (IE), which seeks to “invite a select group of leading experts, IE and non-IE, to focus on one particular visionary theme of major promise”. The symposium features distinguished experts from various domains. Using actual real-world projects as context, the talks will provide overviews of ongoing cutting-edge efforts to harness the growing deluge of data and information to advance decision-making. The symposium should be of interest to researchers and professionals in any discipline that works with big data.

 Speakers and topics will include:

1. Data Science in the Financial Sector - Mark Bennett, Global Investment Bank and University of Chicago

2. Strategy Mining for Behavior Anticipation and Shaping - Alok Chaturvedi, Krannert School of Management, Purdue University

3. From Anecdotes to Analytics - How Data is Changing Healthcare and Hospital Operations - Tze Chiam, Value Institute, Christiana Care Health Systems

4. Divide & Recombine (D&R) with Tessera: High Performance Computing for Data Analysis - William Cleveland, Department of Statistics, Purdue University

5. Examples of Algorithmic Data Pipelines for Social Networks and Large Simulation Analysis - David Gleich, Department of Computer Science, Purdue University

6. Distributed Statistical Inference with Compressed Data - Lifeng Lai, Department of Electrical and Computer Engineering, Worcester Polytechnic Institute

7. Deep Learning for Computer Vision - Qian Lin, Emerging Technologies Lab, Hewlett Packard Laboratories

8. Big Data, Big Methods, Big Potential, Big Challenges - Marc Overhage, Cerner Corporation

9. The Internet in Attention Overdrive: Can We Find a Cure for Information Overload? - Bruno Ribeiro, Department of Computer Science, Purdue University

10. Data Analytics for Cyber Forensics - Marc Rogers, Purdue Polytechnic Institute, Purdue University

11. A New Method to Construct Large Gene Regulatory Networks Using Genetical Genomics Data - Dabao Zhang, Department of Statistics, Purdue University