The School of Computing, along with the SCI Institute, Harvard University, NVidia, and FaceBook Reality Labs sponsored a reception honoring Ivan Sutherland. The reception was held during the SIGGRAPH 2018 conference along with a panel discussion on virtual reality.
During the SIGGRAPH conference Dr. Ivan Sutherland was inducted into the SIGGRAPH Academy
College of Engineering article
VR@50 reception photo gallery
VR@50: Reception Honoring Ivan Sutherland
Please join us Monday August 13th, 6:00pm – 8:00pm, for a reception in honor of Ivan Sutherland, the “Father of Computer Graphics,” on the 50th anniversary of his legendary 1968 paper “A Head-mounted Three-dimensional Display.” This reception complements the SIGGRAPH 2018 panel VR@50, which will take place earlier the same day, August 13, 10:45am – 12:15pm.
The reception program (6:30pm – 7:30pm) will include remarks by Ivan and by several of his former students (Ed Catmull, Henry Fuchs, Henri Gouraud, Alan Kay, Bob Sproull, John Warnock), and an informal discussion among these speakers and guests.
We’ll provide hors d’oeuvres, soft drinks, and a cash bar. The reception is sponsored by the University of Utah, Harvard University, NVIDIA, and Facebook Reality Labs.
For questions please email: email@example.com .
We hope you are able to join us for this unique and historic celebration.
Venue and details:
Vancouver Convention Center
Monday, August 13, 2013
6:00pm – 8:00pm (program: 6:30pm – 7:30pm)
West building, room MR 306
Please contact Chris Coleman for access code. firstname.lastname@example.org
Platforms for Advanced Wireless Research (PAWR) is a public-private initiative between the National Science Foundation (NSF) and a group of companies that committed resources to the program.
Because of the scale of the program, the NSF created a PAWR Project Office (PPO) to oversee the program on behalf of the NSF. The PPO is jointly operated by US Ignite and Northeastern University.
Platform for Open Wireless Data-driven Experimental Research (POWDER) is the name of the UofU platform, which is one of the (anticipated) four platforms that will be funded through PAWR.
By John Regehr
Ranking university programs can be useful: it helps students decide which school to attend, it helps prospective professors decide where to apply for jobs, and it lets university administrators determine which of their units are performing exceptionally well.
What does it really mean for one department to be ranked higher than another? Does it mean that they publish more papers? That more of their graduates create successful companies? It isn’t clear that there’s any single right answer to these questions.
It is clear, however, that ranking can be done badly, and unfortunately, according to the Computing Research Association, this is what has happened to the US News and World Report rankings for computer science, which is perhaps the most widely used and influential ranking. The CRA issued a statement describing a number of problems with the methods used by US News and World Report–including the fact that they do a poor job tracking the venues where computer scientists publish research papers–and concludes: “Anyone with knowledge of CS research will see these rankings for what they are—nonsense–and ignore them. But others may be seriously misled.”
Beyond the problems identified by the CRA, the US News rankings are also hard to interpret since the criteria they are based on are not public. We don’t know the formula they use, nor do we have access to the data that they use as input to the secret formula. This makes it hard for people, such as prospective students, to get benefit from rankings, because it just isn’t clear what it means for one computer science department to be ranked above another.
Beyond the problems identified by the CRA, the US News rankings are also hard to interpret since the criteria they are based on are not public. We don’t know the formula they use, nor do we have access to the data that they use as input to the secret formula. This makes it hard for people, such as prospective students, to benefit from rankings.
Computer science professor Emery Berger, at the University of Massachusetts at Amherst, has come up with a better way to do rankings called CSRankings. His method is transparent: anyone can inspect the formula that it uses and also the data is fed into the formula. The entire implementation for his ranking system is available as open source software!
CSRankings is based on the idea that the best computer science departments are the ones that publish the most articles at “top tier” conferences. These conferences might accept only 10-20% of the papers submitted for publication each year and they are where the best researchers tend to submit their best work.
Ranking university programs can be useful: it helps students decide which school to attend, it helps prospective professors decide where to apply for jobs, and it lets university administrators determine which of their units are performing exceptionally well. What does it really mean for one department to be ranked higher than another? Does it mean that they publish more papers? That more of their graduates create successful companies? It isn't clear that there's any single right answer to these questions. Read more...
By counting only top-tier publications, instead of total publications, CSRankings avoids the problem of inflating the ranking of researchers who publish a large number of low-quality publications. The CSRankings system is carefully designed to be a zero-sum game: the total credit that it gives to a top-tier paper cannot be inflated by adding authors to a paper.
The openness of the CSRankings system and its data set is a huge advantage. The best thing is that the CSRankings web site allows everyone to explore the data.
Let’s say that a prospective student is interested in operating systems and formal verification. That person can select only those two areas of interest and the site will show the departments that publish heavily in top-tier conferences in those specific areas. A prospective student can then drill down at the department level and see who the key players are in those areas and read their code and papers.
This is a fundamentally different use of a ranking system. The ultimate purpose of the rankings is to guide us toward accurate data that can be used to make informed decisions.