Hugh Trumbull Adams '35 Professor of Computer Science, Princeton University
Currently serving as Assistant Director for Computer and Information Science and Engineering (CISE) at NSF.
Speaking June 28, 2022 at 9:00-10:15 EDT
Margaret Martonosi is the US National Science Foundation’s (NSF) Assistant Director for Computer and information Science and Engineering (CISE). With an annual budget of more than $1B, the CISE directorate at NSF has the mission to uphold the Nation’s leadership in scientific discovery and engineering innovation through its support of fundamental research and education in computer and information science and engineering as well as transformative advances in research cyberinfrastructure. While at NSF, Dr. Martonosi is on leave from Princeton University where she is the Hugh Trumbull Adams '35 Professor of Computer Science. Dr. Martonosi's research interests are in computer architecture and hardware-software interface issues in both classical and quantum computing systems. Dr. Martonosi is a member of the National Academy of Engineering and the American Academy of Arts and Sciences. She is a Fellow of the Association for Computing Machinery (ACM) and the Institute of Electrical and Electronics Engineers (IEEE).
Distinguished Researcher
IBM Research
Speaking June 29, 2022 at 9:00-10:15 EDT
José E. Moreira is a Distinguished Research Staff Member at the
IBM Thomas J. Watson Research Center. He received a B.S. degree
in physics and B.S. and M.S. degrees in electrical engineering
from the University of Sao Paulo. He received a Ph.D. degree in
electrical engineering from the University of Illinois at
Urbana-Champaign. Since joining IBM in 1995, Dr. Moreira has
worked on a variety of high-performance systems, including two
ASCI systems (Blue Pacific and White) and the Blue Gene/L
supercomputer, for which he was the System Software architect.
Dr. Moreira has been responsible for various architectural and
micro-architectural innovations in the three most recent generations
of POWER processors. He conceived the POWER10 matrix unit, the first
of its kind in a commercial processor. Dr. Moreira is a Fellow of
the IEEE (Institute of Electrical and Electronics Engineers) and
a Distinguished Scientist of the ACM (Association for Computing
Machinery). Contact him at jmoreira@us.ibm.com.
Distinguished Professor of Computer Science
Founding Director, Scientific Computing and Imaging Institute
University of Utah
Speaking June 30, 2022 at 9:00-10:15 EDT
Chris R. Johnson is a Distinguished Professor of Computer Science and founding
director of the Scientific Computing & Imaging (SCI) Institute at the University
of Utah. He also holds faculty appointments in the Departments of Physics and
Bioengineering. His research interests are in the areas of scientific computing
and scientific visualization. In 1992, with Professor Rob MacLeod, Professor
Johnson founded the SCI research group, now the SCI Institute, which has grown
to employ over 150 faculty, staff and students. Professor Johnson serves on a
number of international journal editorial and advisory boards to national and
international research centers. He is a Fellow of AIMBE (2004), AAAS (2005),
SIAM (2009), and IEEE (2014) and was inducted into the IEEE Visualization Academy
(2019). He has received a number of awards including the NSF Presidential Faculty
Fellow (PFF) award from President Clinton, a DOE Computational Science Award, the
Governor’s Medal for Science and Technology, the Utah Cyber Pioneer Award, the
IEEE Visualization Career Award, IEEE CS Charles Babbage Award, the IEEE Sidney
Fernbach Award, Rosenblatt Prize and most recently, the 2020 Leonardo Award.
Keynote Talk: Large-Scale Visual Analysis in the Age of Data
We live in the Age of Data. Ninety percent of all data in the world has been created
in the past two years alone, at a rate of exabytes per day. New data of all kinds
— structured, unstructured, quantitative, qualitative, spatial, and temporal —
is growing exponentially and in every way. Given the vast amount of data being
produced, one of our greatest scientific challenges is to effectively understand
and make use of it. Because visualization both facilitates the reasoning process
by supporting the human capacity to perceive, understand, and reason about complex
large-scale data and enables researchers to derive knowledge from data, visual data
analysis is one of our most important tools for understanding large-scale complex
data. In this talk, I will present recent visual analysis research and applications
in science, engineering, and medicine from the Scientific Computing and Imaging
Institute and discuss current and future visualization research challenges.