acm - an acm publication

2019 - May

  • Computing a landing spot on Mars: an interview with Victor Pankratius

    The purpose of the Mars rover is in its name---to rove, explore, study Martian geology, look for signs of water, look for signs of life (past or present), etc. However, achieving these and other objectives requires putting the rover down on a suitable landing site, i.e. a site suitable for searching for the desired information and safe to land and function without hindrance or breaking down.

    The data for making these decisions comes from prior Mars missions. Selecting a suitable landing site is a complex process typically taking several years. Researchers at MIT's Kavli Institute for Astrophysics and Space Research prototyped a new software that can help NASA mission planners to more rapidly and reliably find landing sites, potentially reducing the total time required to weeks. In this interview, Victor Pankratius, leader of the research team, shares some insight into the project.

2018 Symposia

Ubiquity symposium is an organized debate around a proposition or point of view. It is a means to explore a complex issue from multiple perspectives. An early example of a symposium on teaching computer science appeared in Communications of the ACM (December 1989).

To organize a symposium, please read our guidelines.

 

Ubiquity Symposium: Big Data

Table of Contents

  1. Big Data, Digitization, and Social Change (Opening Statement) by Jeffrey Johnson, Peter Denning, David Sousa-Rodrigues, Kemal A. Delic
  2. Big Data and the Attention Economy by Bernardo A. Huberman
  3. Big Data for Social Science Research by Mark Birkin
  4. Technology and Business Challenges of Big Data in the Digital Economy by Dave Penkler
  5. High Performance Synthetic Information Environments: An integrating architecture in the age of pervasive data and computing By Christopher L. Barrett, Jeffery Johnson, and Madhav Marathe
  6. Developing an Open Source "Big Data" Cognitive Computing Platform by Michael Kowolenko and Mladen Vouk
  7. When Good Machine Learning Leads to Bad Cyber Security by Tegjyot Singh Sethi and Mehmed Kantardzic
  8. Corporate Security is a Big Data Problem by Louisa Saunier and Kemal Delic
  9. Big Data: Business, technology, education, and science by Jeffrey Johnson, Luca Tesei, Marco Piangerelli, Emanuela Merelli, Riccardo Paci, Nenad Stojanovic, Paulo Leitão, José Barbosa, and Marco Amador
  10. Big Data or Big Brother? That is the question now (Closing Statement) by Jeffrey Johnson, Peter Denning, David Sousa-Rodrigues, Kemal A. Delic