Feel free to spread the word! We hope to see you there.
Institute for Computational and Mathematical Engineering (ICME)
Institute for Computational and Mathematical Engineering (ICME)
FULL NOTICE HERE
Overview (from the site above)
Do you want to help aerospace engineers solve problems faster? Does the phrase “nonlinear partial differential equations used for unsteady computations” excite you? Do you want to try yourself with the complex computational software that NASA scientists use? This might be the challenge for you.
NASA’s Aeronautics Research Mission Directorate (ARMD) is responsible for developing technologies that will enable future aircraft to burn less fuel, generate fewer emissions and make less noise. Every U.S. aircraft and U.S. air traffic control tower has NASA-developed technology on board. It’s why we like to say, NASA is with you when you fly!
We need to increase the speed of computations on the Pleiades supercomputer, specifically for computational fluid dynamics, by orders of magnitude, and could use your help!
This isn’t a quest for the faint of heart. As a participant, you’ll need to gain access to FUN3D software through an application process with the US Government. Although this software usually runs on the Pleiades supercomputer, you can download and run it locally after applying HERE.
NASA’s Aeronautics Research Mission Directorate (ARMD) is tasked with innovating at the cutting edge of aerospace. Their work includes Innovation in Commercial Supersonic Aircraft, Ultra-efficient Commercial Vehicles and Transitioning to Low-Carbon Propulsion while also supporting the development of launch vehicles and planetary entry systems. These strategic thrusts are supported by advanced computational tools, which enable reductions in ground-based and in-flight testing, provide added physical insight, enable superior designs at reduced cost and risk, and open new frontiers in aerospace vehicle design and performance.
The advanced computational tools include the NASA FUN3D software which is used for solving nonlinear partial differential equations, known as Navier-Stokes equations, used for steady and unsteady flow computations including large eddy simulations in computational fluid dynamics (CFD). Despite tremendous progress made in the past few decades, CFD tools are too slow for simulation of complex geometry flows, particularly those involving flow separation and multi-physics (e.g. combustion) applications. To enable high-fidelity CFD for multi-disciplinary analysis and design, the speed of computation must be increased by orders of magnitude.
NASA is seeking proposals for improving the performance of the NASA FUN3D software running on the NASA Pleiades supercomputer. The desired outcome is any approach that can accelerate calculations by a factor of 10-1000x without any decrease in accuracy and while utilizing the existing hardware platform.
More info HERE.
A study group is a type of workshop which brings together mathematicians and people from industry. The meetings typically last for 5 days, Monday-Friday. On the Monday morning the industry representatives present problems of current interest to an audience of applied mathematicians. Subsequently the mathematicians split into working groups to investigate the suggested topics. On the Friday solutions and results are presented to the industry representative. After the meeting a report is prepared for the company, detailing the progress made and usually with suggestions for further work or experiments. Over the years they have proved to be an excellent way of building bridges between universities and companies as well as providing exciting new topics for mathematicians. Of course there is pressure involved in attempting to understand and solve a problem over a short time frame. This can often produce an exciting and intense atmosphere but, in general, a good time is had by all.
Experiments can often help guide a mathematical investigation (or cause even more confusion)
The original Study Groups with Industry started in Oxford in 1968. The format proved a popular way for initiating interaction between universities and private industry. The interaction often led to further collaboration, student projects and new fields of research. Consequently, study groups were adopted in other countries, starting in Europe to form the European Study Groups with Industry (ESGI) and then spreading throughout the world, regular meetings are currently held in Australia, Canada, India, New Zealand, US, Russia and South Africa. A vast range of topics have been covered in the meetings, including beer and wine bottle labelling, legal sale of rhino horn, spontaneous combustion, mortgaging of cows, building toys, city bike sharing strategies, determining fish freshness, etc. New forms of meeting have also evolved, such as the Mathematics in Medicine or Agri-Food Study Groups.
The popularity of study groups can be attributed to their mutually beneficial effects. For companies there is:
The academics benefit from:
An important feature of these meetings is that they can also highlight the talents of students, leading to employment opportunities with the companies. In South Africa, after attending a number of study groups, a group of students took a new direction. Noting the gap in the market for applying mathematics to real world problems they started their own company, Isazi Consulting. Now they return to the meetings this time posing their own problems, and looking for new recruits.
Information on the European Study Groups can be found on the website of the European Consortium for Mathematics in Industry. A good source of information for meetings in Europe and the rest of the world is the Mathematics in Industry Information Service, see
ECMI Study Groups https://ecmiindmath.org/study-groups/
MIIS Website http://www.maths-in-industry.org/
Centre de Recerca Matematica
Registration is now open for the 33rd Annual Mathematical Problems in Industry (MPI) Workshop, to be held June 19-23, 2017 at New Jersey Institute of Technology in Newark, NJ. The Department of Mathematical Sciences at NJIT is hosting the meeting, with Linda Cummings and Richard Moore acting as local organizers. Funding is provided by our industrial participants and the National Science Foundation.
The format of MPI 2017 will be familiar to those of you who have attended MPI or a similar week-long study group in the past. On Monday, several industrial participants present their research problems to an assembled group of professors, postdocs and graduate students working in the field of applied mathematics. These presentations are followed by break-out sessions, where teams form to work on the problems throughout the week. The week culminates in presentations delivered Friday to the assembled group of industrial
participants and applied mathematicians. A follow-up report is delivered to each industrial participant in the weeks following MPI. These reports are often modified and submitted for publication in peer-reviewed journals, and many past MPI workshops have produced fruitful long-term collaborations.
To learn more about MPI 2017 and prior workshops, please visit the workshop website:
A link on the left menubar will direct you to the online registration form. Spaces and funding are limited, so please register as early as possible. Young researchers and those with prior experience at MPI or the GSMMC (see below) are especially encouraged to apply, as are members of groups traditionally underrepresented in applied mathematics.
Graduate students who have not already done so in a previous year are strongly encouraged to participate in the Graduate Student Mathematical Modeling Camp (GSMMC), held at Rensselaer Polytechnic Institute the week immediately preceding MPI. You will automatically be registered for MPI as a Camp attendee. Please follow the following link to register for the GSMMC:
Although some of the industrial problems have already been selected, we are still
accepting applications to participate as problem-presenters. Please forward this email to industrial contacts who might be interested in exposing their research problems to a large body of creative problem-solvers with broad expertise in industrial applied math.
Looking forward to seeing you at MPI 2017!
Discover the basics behind the application of modern machine learning algorithms. The workshop instructors will discuss a framework for reasoning about when to apply various machine learning techniques, emphasizing questions of over-fitting/under-fitting, regularization, interpretability, supervised/unsupervised methods, and handling of missing data.
For more information, visit the Stanford ICME website: https://icme.stanford.edu/events/fundamentals-machine-learning-workshop
Attendees should have undergraduate-level knowledge of linear algebra and statistics, and basic programming experience (R/Matlab/Python). Please note that this is not a Stanford for-credit course.
Space is limited, so register today.
Thanks to Judy Logan from the Institute for Computational and Mathematical Engineering (ICME) at Stanford University and the Women in Data Science (WiDS) Conference for this post.