The Global App Initiative, a student run organization at BU, is doing meaningful work developing free mobile apps for non-profits. The Hariri Institute supports this initiative by providing a space for the group to meet monthly. Read more from a BU Today article about the development of the GAI and the non-profits who benefit from their service.
The data age has arrived. From crowd-sourced product reviews to real-time traffic alerts, “big data” has become a regular part of our daily lives. In 2013, researchers estimated that there were about 4 zettabytes of data worldwide: That’s approximately the total volume of information that would be created if every person in the United States took a digital photo every second of every day for over four months! The vast majority of existing data has been generated in the past few years, and today’s explosive pace of data growth is set to continue. In this setting, data science — the ability to extract knowledge and insights from large and complex data sets — is fundamentally important.
While there is a rich history of companies using data to their competitive advantage, the disproportionate beneficiaries of big data and data science have been Internet technologies like social media, search, and e-commerce. Yet transformative uses of data in other spheres are just around the corner. Precision medicine and other forms of smarter health care delivery, individualized education, and the “Internet of Things” (which refers to devices like cars or thermostats communicating with each other using embedded sensors linked through wired and wireless networks) are just a few of the ways in which innovative data science applications will transform our future.
Starts: 8:00 am on Monday, March 2 2015
Ends: 6:00 pm on Monday, March 2 2015
Location: 8 St. Mary’s Street, 9th Floor
This day-long workshop will feature 30 talks by leading computer vision researchers, covering a broad range of topics. Please complete the Registration Form on the workshop webpage. Registration is free of charge, but space may be limited. The workshop is co-sponsored by the Hariri Institute, the Department of Computer Science, and the Department of Electrical and Computer Engineering.
CCS Seminar Features Yoshitaka Tanimura, “Simulating, Modeling, and Analyzing Two-Dimensional THz-Raman Spectroscopies”
The Boston University Center for Computational Science will be hosting a seminar featuring Professor Yoshitaka Tanimura from the Department of Chemistry at Kyoto University, Japan.
Simulating, Modeling, and Analyzing Two-Dimensional THz-Raman Spectroscopies
12:00 PM on March 24, 2015
Physics Research Building, 3 Cummington Mall, Room 595
Abstract: Understanding dynamics in complex environments of molecular liquids and biological systems has been a central topic of investigation in chemistry and biology, because many important chemical processes occur exclusively in such media. Recently, two-dimensional (2D) THz-Raman spectroscopy has been used to investigate the intermolecular modes of liquid. We calculate such 2D spectroscopy signals for liquid water, methanol, and formamide using an equilibrium-non-equilibrium hybrid MD simulation algorithm originally developed for 2D Raman spectroscopy. These signals are analyzed in terms of anharmonicity and nonlinear polarizability of vibrational modes using a Brownian oscillator (BO) model with linear-linear (LL) and square-linear (SL) system-bath interactions from the hierarchal equations of motion approach for a non-Markovian noise. All of the characteristic 2D profiles of the signals obtained from MD are reproduced using the LL+SL BO model indicating that this model captures the essential features of the inter-molecular motion. We analyze the fitted 2D profiles in terms of anharmonicity, nonlinear polarizability, and dephasing time. The origin of the echo peaks of librational motion and the elongated peaks parallel in the probe direction are elucidated by the optical Liouville paths.
Joint CCS/PChem Seminar Features Paul Champion, “Vibrationally Enhanced Deep Proton Tunneling in Protons”
The Boston University Center for Computational Science and Physical Chemistry will be hosting a special joint seminar featuring Professor Paul Champion, Physics Department Chair at Northeastern University.
Vibrationally Enhanced Deep Proton Tunneling in Proteins
2:00 PM on February 20, 2015
Physics Research Building, 3 Cummington Mall, Room 595
Abstract: Ground electronic state proton tunneling kinetics have been measured over an unprecedented dynamic range of time and temperature using a light-triggered “proton wire” in green fluorescent protein. The data reveal a large temperature-dependent kinetic isotope effect and demonstrate sub-nanosecond vibrationally enhanced “deep tunneling” at room temperature for a typical hydrogen bonded donor-acceptor (D-A) oxygen equilibrium distance of ~2.7-2.8â«. A two-dimensional quantum oscillator model, which includes normal modes composed of the D-A and hydrogen atom stretching motions, predicts the temperature and isotope dependence of the observed rates on an absolute scale using only three free parameters: the equilibrium tunnel distance (0.78â«), a Marcus reorganization energy (1175cm-1), and the D-A stretching frequency (271 cm-1). We conclude that room temperature deep tunneling is likely to dominate proton transfer through typical H-bonded networks in proteins.
IDC Smart Cities Research Director Ruthbea Clarke, a BU NSF SCOPE partner, presents 2015 global smart cities predictions webcast, IDC FutureScape: Worldwide Smart Cities 2015 Predictions, on Dec 17.
“When in 2012 a computer learned to recognize cats in YouTube videos and just last month another correctly captioned a photo of “a group of young people playing a game of Frisbee,” artificial intelligence researchers hailed yet more triumphs in “deep learning,” the wildly successful set of algorithms loosely modeled on the way brains grow sensitive to features of the real world simply through exposure.
Using the latest deep-learning protocols, computer models consisting of networks of artificial neurons are becoming increasingly adept at image, speech and pattern recognition — core technologies in robotic personal assistants, complex data analysis and self-driving cars. But for all their progress training computers to pick out salient features from other, irrelevant bits of data, researchers have never fully understood why the algorithms or biological learning work.”
The new work, completed by Hariri Institute Fellow, Pankaj Mehta of Boston University, and David Schwab of Northwestern University, demonstrates that a statistical technique called “renormalization,” which allows physicists to accurately describe systems without knowing the exact state of all their component parts, also enables the artificial neural networks to categorize data as, say, “a cat” regardless of its color, size or posture in a given video.
Pankaj Mehta presented these results at BU’s Hariri Institute as his Junior Fellow Award Lecture.
December 1, 2014 from StateTech
A project team of academia and industry experts is making headway on a multimillion-dollar cloud computing initiative announced by Massachusetts Gov. Deval Patrick in April.
If all goes as planned, the three-year project, known as the Massachusetts Open Cloud (MOC), will pave the way for cloud consumers to customize infrastructure and platform services to best meet their needs. Patrick is hopeful that MOC’s public cloud computing infrastructure will spur Big Data innovation in the state.
Azer Bestavros, director of the Rafik B. Hariri Institute for Computing and Computational Science & Engineering at Boston University, likens the new model to a shopping mall, where customers can choose from multiple retailers and mix and match products and services. In the cloud computing world, this model doesn’t exist, Bestavros says. “All you have are stores like Walmart. They own and operate everything.”
Boston University leads the MOC project team. The MOC project received $3 million in state funding, according to Bestavros. “We have commitments of up to $20 million from universities and industry.”
MOC is an architecture and a model for other governments, he adds. It functions similar to a shopping mall in that technologies from multiple MOC service providers will be located in the same location or data center. Ideally, MOC won’t be restricted to government customers. The general public and companies will be able to buy cloud services using an online user interface, much like the one offered by Amazon Web Services.
Cisco, Intel, Red Hat and Juniper Networks are among the growing number of companies partnering with the MOC project. Academia partners include Northeastern University, University of Massachusetts, Harvard University and the Massachusetts Institute of Technology.
Jan Mark Holzer, a senior consulting engineer at Red Hat, says his company is helping MOC build the cloud infrastructure around OpenStack. Red Hat has moved some hardware into the MOC-designated data center and will continue to install hardware and software for at least the next six months. Hozer stressed that the MOC and its member partners are not interested in promoting a particular vendor or product. It’s an open project.
Hozer says he is hopeful that MOC will be open for research use fairly soon, which could mean months, rather than years.
It’s too early to say how much the MOC services will cost, but the price points have to be competitive because agencies aren’t required to use the services.
Tech professionals who work at election offices have pretty full calendars these days; but Albert Grimes, CIO at the Massachusetts Office of Campaign & Political Finance, took time out of his busy schedule to chat about how the office handles the flood of political contribution data that comes in shortly before Election Day. Grimes spoke at Boston University’s Hariri Institute for Computing and Computational Science & Engineering along with Paul Clark, a data analyst and disclosure business architect with the Federal Elections Commission.
Commenting on this event, ComputerWorld Sharon Machlis notes:
One key, he says, is making sure that people who want to know who’s financing the various candidates have easy access to that data. That constituency includes voters, the media and political enthusiasts, as well as candidates and their organizations.
What’s the most interesting thing he and his team are working on? Data visualization, Grimes said, so it’s easier for people to understand trends in where money is coming from to back various politicians and policies. It’s one thing to get a whole series of reports back on who’s contributed to a politician or political committee, he noted.
November 10 2014 from BU today
BU plans to hire up to six data scientists—the intellectual miners extracting applicable information from the mountains of Big Data—over the next three years
Data scientists use mathematical models to analyze voluminous data and draw knowledge from it that can be used in a variety of applications, from health care and business to design and communications. The University provost’s faculty hiring initiative aims to bolster BU’s ranks in a burgeoning field and also to advance the University’s focus on interdisciplinary research.
“It’s not like we don’t do data science. But we don’t have enough data science scholars to address the need for data science by lots of other disciplines,” says Azer Bestavros, director of BU’s Rafik B. Hariri Institute for Computing and Computational Science & Engineering. Current data science is done by handfuls of professors in “small islands of collaborations,” he says, “two or three faculty working together.…We need to do a lot more.”