Sep 30th - Oct 1st 2014
The Ritz-Carlton, Pentagon City
Washington, D.C.

Software has put the information revolution in the hands of billions of people. And yet, we continue to misunderstand programming. Far from giving it pride of place as the single most important lever in creating the digital future, programming is radically misunderstood as a minor technical detail. We don't teach it well; we design screens and widgets instead of computational models; we're not prepared to program non-silicon-based computers. We discourage designers from learning to think in programs—and programmers from thinking as designers. 


JONATHAN ALDRICH, Associate Professor, School of Computer Science, Carnegie Mellon University
Wyvern: The Human Dimension of Programming Language Security

WALTER BRIGHT, Computer Programmer and Author
Topic: The D Programming Language 

ROBERT CHARETTE, Founder and President, ITABHI Corporation
Programming in the New Risk Ecology 

MICHAEL FRANZ, Professor, University of California, Irvine 
Code Diversity and Biologically-Inspired Computer Defenses

VIKAS GUPTA, Co-founder and Chief Executive Officer, Play-I
Kids Programming Robots 

TODD HYLTON, Senior Vice President, Brain Corporation

ALAN KAY, TTI/Vanguard Advisory Board
Timeless Software

JINI KIM, Founder, NunaHealth, and MIKEY DICKERSON, subcontractor to QSSI and formerly Site Reliability Engineer, Google

MARK MAYBURY, Vice President and Chief Technology Officer, MITRE
10X Transformational Change

MICHAL MIGURSKI, Chief Technology Officer, Code For America
Harnessing Technology to Solve Community Problems

IKE NASSI, Chief Executive Officer and Founder, TidalScale 
Software Scaled Computing: Resizing the Computer to Fit the Application

CARLOS OLGUIN, Head, Bio/Nano/Programmable Matter Group, Autodesk Research
Programmable Matter 

EMINA TORLAK, Assistant Professor, University of Washington
Programming for Everyone: Languages That Automate Coding, Verification, and Debugging

JAKE VANDERPLAS, Director of Research in the Physical Sciences for the eScience Institute, University of Washington
Big Data Brain Drai