PRESIDENT S FORUM NOVEMBER 7, PDF Free Download

PRESIDENT S FORUM NOVEMBER 7, 2013

PURDUE MOVES GROWTH IN COMPUTER SCIENCE Sunil Prabhakar Professor and Head Jennifer Neville Associate Professor

COMPUTER SCIENCE A CENTRAL DISCIPLINE Advances in computing, communications and information technology: Accelerate the pace of discovery and innovation in nearly all other fields of inquiry; Are crucial to achieving our major national and societal priorities. F. Jahanian, Director of CISE, NSF

THE PAST THIRTY YEARS Life Changers The top innovabons of the last 30 years, according to judges at the Wharton School of the University of Pennsylvania. 1. Internet, broadband 2. PC and laptop computers 3. Mobile Phones 4. E- mail 5. DNA tesbng and sequencing 6. MagneBc resonance imaging 7. Microprocessors 8. Fiber opbcs 9. Office solware 10. Laser/roboBc surgery 11. Open- source solware 12. Light- emirng diodes 13. Liquid crystal display 14. GPS devices 15. E- commerce and aucbons 16. Media file compression 17. Microfinance 18. Photovoltaic solar energy 19. Large- scale wind turbines 20. Internet social networking

Credit: Intel Corporation

PURDUE COMPUTER SCIENCE

HISTORY OF COMPUTER SCIENCE Purdue established the nation s first CS department in 1962 Recently celebrated 50th anniversary Many PhD graduates played a vital role in the creation of CS departments at other universities

DEMAND FOR GRADUATES OF COMPUTER SCIENCE PROGRAM Robust and growing demand for CS students. Hands-on, profitable internships Job placement near 100%; top salaries; sustained career advancement. Expansive Corporate Partners Program Separate CS Career Fair Company days in the Lawson Commons

CS CORPORATE PARTNERS A VERY DIVERSE GROUP

ENTREPRENEURSHIP OPPORTUNITIES AND SUCCESSES Long-standing culture of entrepreneurship among students and faculty Lawson Software Tripwire Arxan Technologies FoundOPS Several startups currently underway

RESEARCH LEADERSHIP Top 20 world ranking (Shanghai Jiao Tong) Research funding at an all time high Home to world-class Centers NSF Science and Technology Center on the Science of Information (CSoI) Center for Education and Research in Information Assurance and Security (CERIAS)

CENTER FOR SCIENCE OF INFORMATION First NSF-Sponsored Science and Technology Center centered in Indiana $25 million over five years Advancing the foundations of Information Theory Bryn Mawr Howard MIT Princeton Purdue Stanford Texas A&M UC Berkeley UC San Diego UIUC NaBonal Science FoundaBon/Science & Technology Centers Program 66

CERIAS INTERDISCIPLINARY PURDUE CENTER Top-ranked security center in the US Focus on interdisciplinary research Faculty members from 18 Purdue departments Research areas include Network & End-System Security Human Centric Security Policy, Law and Management

RESEARCH AREAS Bioinformatics and Computational Biology Computational Science and Engineering Databases and Data Mining Distributed Systems Graphics and Visualization Information Security and Assurance Machine Learning and Information Retrieval Networking and Operating Systems Programming Languages and Compilers Software Engineering Theory of Computing and Algorithms

FROM DATA TO KNOWLEDGE Data mining: The process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data U. Fayyad, G. Piatetsky-Shapiro & P. Smyth, AI Magazine, 1996 Machine learning: How can we build computer systems that automatically improve with experience? T.M. Mitchell, Fredkin Professor, CMU 2006 2 2

THE DATA MINING PROCESS Data Selection Target data Preprocessing Processed data Machine Learning Knowledge Interpretation/ evaluation Patterns Mining

THE DATA REVOLUTION The last 30 years of research in ML/DM has resulted in wide spread adoption of predictive analytics to automate and improve decision making. As big data efforts increase the collection of data so will the need for new data science methodology. Data today have more volume, velocity, variety, etc. Machine learning research develops statistical tools, models & algorithms that address these complexities. Data mining research focuses on how to scale to massive data and how to incorporate feedback to improve accuracy while minimizing effort.

ML @ PURDUE Chris Clifton David Gleich Jennifer Neville Yuan (Alan) Qi Luo Si SVN Vishwanathan

EXAMPLE: FRAUD DETECTION Exploit organiza4on rela4onships among stock brokers to improve iden4fica4on of fraud and malfeasance and aid regulatory oversight.

EXAMPLE: FRAUD DETECTION

EXAMPLE: COMPLEX SYSTEMS Data summarization Feature creation Machine Learning Maintenance Development Design Use distributed logs ﬁles to understand complex system behavior and detect, diagnose, and iden4fy likely causes of performance problems

LOOKING FORWARD Research impact $300 billion in annual value to US healthcare Training impact 140,000-190,000 additional data science jobs McKinsey Global Ins4tute

GROWTH PLAN EXPANDING COMPUTER SCIENCE Capitalize on current success and meet the future demand for CS graduates Demand + Excellence + Societal Need Increase enrollment by 27% to 1000 undergraduates, 311 graduate Increase faculty and staff Create degree programs Professional MS in Data Science Joint programs, Core Curriculum

CYBER-SUSTAINABILITY IN PARTNERSHIP WITH AGRICULTURE Data is the new frontier for agriculture Capitalizing on Purdue's strengths to leverage the power of computing for feeding a growing world Purdue will become the pre-eminent leader in Cyber-Sustainability for Agriculture Increased entrepreneurship in this promising area

PRESIDENT S FORUM NOVEMBER 7, 2013