2017 Annual Affiliates Meeting


Annual Affiliates Meeting: April 10 - April 12, 2017

Location: Arrillaga Alumni Center

McCaw Hall

326 Galvez Street

Stanford, CA 94305

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The Annual Meeting will be hosted for the 49th consecutive year by the Computer Forum at the Arrillaga Alumni Center at Stanford University. The three-day event will present opportunities for our industrial partners to hear about latest developments in timely and critical areas of technology.

The Annual Security Workshop, now in its 18th year, will present cutting edge research on computer security from the Stanford Security Lab. Topics include web security, security for embedded devices and mobile phones, operating systems, code analysis, secure user interfaces, cryptography, and many others. The workshop is organized by Professors Dan Boneh and John Mitchell and will involve talks from faculty and PhD students.

April 10, 2017
McCaw Hall, Alumni Center

The theme of the Plenary Session, organized by Professor Fei Fei Li, and Dr. Steve Eglash will be "AI for Future Society" and will feature selected talks by faculty and industry leaders.

Artificial intelligence is having an increasingly large and pervasive impact on society. This symposium will showcase and examine the AI technologies like machine learning, computer vision, natural language processing, robotics, and genomics that will affect all of our lives and businesses by changing information sharing, healthcare, transportation, and more

The keynote speaker for the seated luncheon will be presented by Professor Shannon Vallor, Professor and Department Chair of Philosophy at Santa Clara University, on Ethical AI. The day will conclude with a reception and a poster session of CS and EE student research.

April 11, 2017

McCaw Hall, Alumni Center


This is a workshop organized by Professor Balaji Prabhakar and Mendel Rosenblum.

Networks have become very complex over the past decade. The users and operators of large cloud platforms and campus networks have desired a much more programmable network infrastructure to meet the dynamic needs of different applications and reduce the friction they can cause to each other. This has culminated in the Software-defined Networking paradigm.

But it is hard to program what you do not understand: the volume, velocity and richness of network applications and traffic seem beyond the ability of direct human comprehension. What is needed is a sensing, inference and learning system which can observe the data emitted by a network during the course of its operation, reconstruct the network's evolution, infer key performance metrics, continually learn the best responses to rapidly-changing load and operating conditions, and help the network adapt to them in real-time. The workshop brings together academic and industry groups interested in the broad themes of this topic. It highlights ongoing research at Stanford and describes initial prototype systems and results from pilot deployments.

April 12, 2017

McCaw Hall, Alumni Center