Program Purpose

The Mission of the Distinguished Speakers Program

The DSP is an outreach program of ACM that brings distinguished speakers from academia, industry, and government to give presentations to ACM chapters, members, and the greater IT community in a variety of venues and formats.

The History of the Distinguished Speakers Program

The Distinguished Speakers Program has been in existence for over twenty years. Traditionally, the program was comprised of speakers from academe that traveled to individual ACM chapters and larger, regional "magnet events" to deliver lectures on their field(s) of expertise. A core group of lecturers would commit to serve for one year, with the option to stay on. Now, a speaker is given a 3 year term. ACM headquarters reimbursed lecturers for their travel expenses; chapters were responsible for local expenses. In this way it served as indirect financial support for chapters, especially those struggling with access to quality content and speakers.

In recent years, the program has been almost exclusively marketed to, and used by, student chapters, with positive feedback from both students and speakers. Recognizing the potential for the DSP to serve as a premier outreach program for all ACM chapters and members, the Membership Services Board created a committee in 2005 to review the current program and to set goals for expanding its size and scope.

The newly reconstituted committee updated the program's topic categories based on feedback from different constituencies, including ACM members, student and professional chapters, Special Interest Groups, and ACM Board Chairs. With an updated topic listing in place, recruitment began for new speakers, from academe, industry, and government.

The Distinguished Speakers Program has always operated in the spirit of service and outreach. Its goals are to provide some of the best content ACM has to offer through its network of high quality speakers and to facilitate professional networking. The committee is still accepting nominations for speakers. If you know someone who would like to participate, or you yourself would like to participate, please see our nomination form.

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Prediction-Serving Systems

ACM Queue’s “Research for Practice” is your number one resource for keeping up with emerging developments in the world of theory and applying them to the challenges you face on a daily basis. In this installment, Dan Crankshaw and Joey Gonzalez provide an overview of machine learning server systems. What happens when we wish to actually deploy a machine learning model to production, and how do we serve predictions with high accuracy and high computational efficiency? Dan and Joey’s curated research selection presents cutting-edge techniques spanning database-level integration, video processing, and prediction middleware. Given the explosion of interest in machine learning and its increasing impact on seemingly every application vertical, it's possible that systems such as these will become as commonplace as relational databases are today.