Date/Location: Thursday, May 24th @ 3:30 PM - 356A Fitzpatrick Hall 

Title: Forming Dream Teams
Abstract: Team Formation, or “finding a group of individuals who can communicate effectively as a team to accomplish a specific task” is an interesting problem, especially as communities and collaborations are increasingly virtualised.  In this talk I look at team formation using the scientific collaboration networks - and as part of this project our experiences in  building a new, large, rich, Comprehensive Scholarly Corpus as a platform and data source for research. Our corpus contains records of 1,044,454 papers, 472,365 unique authors, and substantial publication meta-data for each record. We have integrated the data we collected from 276 publishers using a uniform and consistent XML data format within the corpus. The corpus is designed to be compatible with DBLP enabling existing research to utilise our new corpus directly.  Prior work in online team formation algorithms  has focused on reducing the communication costs within teams, in contrast however, our new team formation algorithm builds teams by looking at interpersonal chemistry as well as expertise.   
 
Bio: My homepage:  https://ecs.victoria.ac.nz/Main/KrisBubendorfer
Kris Bubendorfer is an Associate Professor in Engineering at Victoria University of Wellington. His research interests include cloud related areas of distributed computing, including, services and service oriented architectures, cloud computing markets, resource allocation, cyber security, high performance computing, scientific computation, eResearch and the associated topics of social computing and reputation systems.

Published: April 4th, 2018

Author: Brandi Klingerman

Click Here for Full Article

About the Award

This award recognizes outstanding contributions in the areas of computational sciences and visualization. Such contributions may include, but are not limited to: 1) applications of high performance computation and/or visualization technology; 2) development of algorithms, codes, software environments or other tools for better using high performance computing and/or visualization. The nominated work need not have been done using CRC hardware or software.

Previous Winners

2018 Sponsored by Center for Research Computing

  • Prateek Mehta, College of Engineering
    advisor: Prof. Willaim F. Schneider
  • Anna Elizabeth McCoy, College of Science
    advisor: Prof. Mark A. Caprio
  • James Kapaldo, College of Science
    advisor: Prof. Sylwia Ptasinska

2017 Sponsored by Center for Research Computing

  • Douglas Duhaime, College of Arts and Letters
    advisor: Prof. Matthew Wilkens
  • Lei Li, College of Engineering
    advisor: Prof. Kapil Khandelwal
  • Xufei Wu, College of Engineering
    advisor: Prof. Tengfei Lou
  • Triet Nguyen-Beck, College of Science
    advisor: Prof. John Parkhill

2016 Sponsored by Center for Research Computing

  • Eric Hansen, Chemistry and Biochemistry 
    advisor: Prof. Olaf Wiest
  • Brian S. Yoo, Chemical and Biomolecular Engineering 
    advisor: Prof. Edward Maginn
  • Teng Zhang, Aerospace and Mechanical Engineering 
    advisor: Prof. Tengfei Luo

2015 Sponsored by Center for Research Computing

  • Christopher Paolucci, Chemical and Biomolecular Engineering
    advisor: Prof. William Schneider
  • Aparna Bhattacharya, Physics
    advisor: Prof. David Bennett
  • Matthias Wolf and Anna Woodard, Physics
    advisors: Prof. Mike Hildreth and Prof. Kevin Lannon

2014 Sponsored by Center for Research Computing

  • Xin (Cynthia) Tong, Psychology
    advisor: Prof. Zhiyong Zhang
  • Geoffrey Siwo, Biological Sciences
    advisor: Prof. Michael Ferdig
  • Aaron Donahue, Civil and Environmental Engineering and Earth Sciences
    advisor: Prof. Joannes Westerink

2013 Sponsored by Center for Research Computing

  • Jason Bray, Chemical and Biomolecular Engineering
    advisor: Prof. William Schneider
  • Patrick Kerr, Civil and Environmental Engineering and Earth Sciences
    advisor: Prof. Joannes Westerink
  • Zachary Terranova, Chemistry and Biochemistry
    advisor: Prof. Steven Corcelli

2012 Sponsored by Center for Research Computing

  • Chad D. Meyer, Physics
    advisor: Prof. Dinshaw Balsara
  • Ryan Lichtenwalter, Computer Science and Engineering
    advisor: Prof. Nitesh Chawla
  • Gianluca Puliti, Aerospace and Mechanical Engineering
    advisor: Prof. Samual Paolucci

2011 Sponsored by Center for Research Computing

  • Prashant Deshlahra, Chemical and Biomolecular Engineering
    advisors: Prof. Eduardo Wolf and Prof. William Schneider
  • Qi Lao, Computer Science and Engineering
    advisor: Prof. Aaron Striegel
  • Yao Shen, Chemistry and Biochemistry
    advisor: Prof. Olaf Wiest

2010 Sponsored by Center for Research Computing

  • Joshua Enszer, Chemical and Biomolecular Engineering
    advisor: Prof. Mark Stadtherr
  • Karsten Steinhaeuser, Computer Science and Engineering
    advisor: Prof. Nitesh Chawla
  • Xinghai Zhao, Physics
    advisor: Prof. Grant Mathews

2009 Sponsored by Center for Research Computing

  • Saivenkataraman Jayaraman, Chemical and Biomolecular Engineering
    advisor: Prof. Edward Maginn
  • Drew Johnson, Chemistry and Biochemistry
    advisory: Prof. Olaf Wiest
  • Luke Simoni, Chemical and Biomolecular Engineering
    advisors: Prof. Joan Brennecke and Prof. Mark Stadtherr

2008 Sponsored by Center for Research Computing

  • Cesar A. Hidalgo, Physics
    advisor: Prof. Laslo Barabasi
  • Rachel B. Getman, Chemical and Biomolecular Engineering
    advisor: Prof. William F. Schneider
  • Charles F. Vardeman II, Chemistry and Biochemistry
    advisor: Prof. J. Daniel Gezelter

2007 Sponsored by Center for Research Computing

  • Robert Bruggner, Biological Sciences
    advisor: Prof. Frank Collins
  • Manish Kelkar, Chemical and Biomolecular Engineering
    advisor: Prof. Edward Maginn

2006 Sponsored by SGI, a leader in high performance computing and visualization technology

  • Christopher B. Harrison, Chemistry and Biochemistry
    advisor: Prof. Olaf Wiest
  • Ethan J. Kubatko, Civil Engineering and Geological Sciences
    advisor: Prof. Joannes Westerink
  • James P. Larentzos, Chemical and Biomolecular Engineering
    advisor: Prof. Edward Maginn

2005 Sponsored by SGI, a leader in high performance computing and visualization technology

  • Christopher J. Fennel, Chemistry and Biochemistry
    advisor: Prof. Daniel Gezelter
  • David M. Eike, Chemical and Biomolecular Engineering
    advisor: Prof. Edward Maginn
  • Jeffrey R. Spies, Psychology
    advisor: Prof. Steven Boker

2004 Sponsored by SGI, a leader in high performance computing and visualization technology

2003 Sponsored by SGI, a leader in high performance computing and visualization technology

  • Matthew Meineke, Chemistry and Biochemistry
    advisor: Prof. Daniel Gezelter
  • Jesse Feyen, Civil Engineering and Geological Sciences
    advisor: Prof. Joannes Westerink
  • Eric Covey, Psychology
    advisor: Prof. Steven Boker

2002 Sponsored by SGI, a leader in high performance computing and visualization technology

  • Gaurav Arya, Chemical Engineering
    advisor: Prof. Edward Maginn
  • Jonas Oxgaard, Chemistry and Biochemistry
    advisor: Prof. Olaf Wiest

2001 Sponsored by SGI, a leader in high performance computing and visualization technology

  • Chris Monico, Mathematics
  • Jeff Squyres, CSE

2000 Sponsored by SGI, a leader in high performance computing and visualization technology

  • Timothy Gallant, Arts and Letters
    advisor: Prof. Paul Down
  • Marianna Safronova, Physics
    advisor: Prof. Walter Johnson
  • Yiannis Kaznessis, Chemical Engineering
    advisors: Prof. Edward Maginn and Prof. Davide Hill

February 9th, 2018

101 DeBartolo Hall

1:00 PM - 2:00 PM

Decentralized Workflows Using Vector Symbolic Architectures

Abstract:

Decentralized analytics require a means of specifying distributed data and computing control dependencies amongst services without the centralized coordination of the workflow. The distributed nature of such workflows puts far more emphasis on discovery mechanisms to ensure that each node can operate completely autonomously and cooperate with each other when needed. Consequently, the workflow must be capable of discovering the node(s) it needs to interact with at any specific time and in the most resource efficient way possible. To this end, a scheme for distributing the coordination information is needed that can minimize communication overhead, whilst providing comprehensive information surrounding the workflow being executed. In this talk, we explore the use of structured associative memory models called vector symbolic architectures for representing and orchestrating complex decentralized workflows. Such an approach offers a number of desirable features: it can encode workflows containing multiple coordinated sub-workflows in a way that allows the workflow logic to be unbound on-the-fly and executed in a completely decentralized way; the workflow and associated complex metadata can be embedded into a single vector; this vector representation is extremely compact; and is completely self-contained and can be passed around using standard group transport protocols. We describe the approach applied to multi-level complex workflows.

Bios:

Dr. Graham Bent was formally a Senior Technical Staff Member in the IBM Emerging Technology Services (ETS) group at IBM Hursley and is an IBM Master Inventor. He retired from IBM in January 2016. He now works for IBM Research as a contractor and is director of his own company called Neurosynapse Limited. Over the past 10 years Graham has been involved in a UK MoD/US DoD research program - the International Technology Alliance in Network and Information Sciences (NIS ITA) undertaking research on large scale distributed databases; new encryption techniques for distributed secure computing using fully homomorphic encryption; and neuromorphic processing using the SyNapse technology (TrueNorth). He is currently involved in a new International Technology Alliance program on Distributed Analytics and Information Science (DAIS ITA). His current research is in the development of intelligent agents for distributed analytics using brain inspired neuromorphic computation.

 

Mr. Chris Simpkin graduated with honours in Electronics in 1983 and MSc in Computer Science in 1990. He worked as a design engineer on high speed control systems including design of analogue control loops, dedicated digital computer control systems and programming in both assembler and high-level languages. Chris worked for IBM for 10 years in various areas including stress testing of IBM’s flagship S/390 G5 Parallel main frames, IBM CICS and IBM Message Queuing products. In 1998 Mr Simpkin qualified as an Optometrist, gaining his third degree, and spending 10 years managing an Optometry business, before returning to computing, working on artificial intelligence, genetic computing, neural networks. Chris is currently doing a PHD at Cardiff University, UK, focusing in the use of machine learning algorithms for distributed data analytics applications.

 

Presentation Slides: 

Learn Cloud Computing with GSU

Location: 121 Information Technology Center

Time: Tuesday 11/28, 1pm

 

Are you tired of waiting hours for a simulation in your research or coursework? Do you want to learn how to leverage the power of the high-performance computing resource at Notre Dame? Join our in-depth workshop with ND’s experts at the Center for Research Computing (CRC). Learn the fundamentals of the CRC cluster with hands-on examples for your next perfect job script. Pizza provided. Please RSVP at: https://goo.gl/forms/57sSGpguP5BT6ulD3.

September 28th, 2017

Debartolo Hall Room 140

3:30 - 4:30 PM

Software Citation and Software Reproducibility 

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Abstract:

 

Software is a critical part of modern research and yet there is little support across the scholarly ecosystem for its citation. Inspired by the activities of the FORCE11 working group focused on data citation, the FORCE11 Software Citation Working Group has published a set Software Citation Principles (https://doi.org/10.7717/peerj-cs.86) in September 2016. This has the goal of encouraging broad adoption of a consistent policy for software citation across disciplines and venues. This presentation will discuss the principles (in brief, importance, credit and attribution, unique identification, persistence, accessibility, and specificity), how they will impact the practice of research, and they can be implemented by researchers, publishers, librarians and others who build and maintain repositories, scholars of science, university administrators, and research funders.  In addition, reproducibility of software intensive projects has a set of challenges and obstacles that are different than other projects, and this talk with also discuss the aspects of software that make reproducibility challenging.

Bio:


Daniel S. Katz has co-led the FORCE11 Software Citation Working Group and is a founding topic editor of the Journal of Open Source Software. At the University of Illinois Urbana-Champaign, he is Assistant Director for Scientific Software and Applications at the National Center for Supercomputing Applications (NCSA) and Research Associate Professor in Computer Science, Electrical and Computer Engineering, and the School of Information Sciences (iSchool). He formerly led the Software Cluster in the Division of Advanced Cyberinfrastructure as a National Science Foundation program officer. He is interested in promoting the development and use of cyberintrastructure, focused on software, to solve challenging research problems.  For more information about Daniel S. Katz, see http://danielskatz.org 

 

Presentation Slides: Click Here

July 26th, 2017

102 DeBartolo Hall

1:00 PM - 2:00 PM

Mobile Phone-Credit Scoring in Africa

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Abstract:

Mobile Money platforms are gaining traction across developing markets as a convenient way of sending and receiving money over mobile phones.  These systems operate on low-cost feature phones and do not require users to have a bank account.  These low barriers-to-entry make mobile money platforms excellent tools for financial inclusion of the poor.  Additional financial services, such as saving and lending products, are now being offered over these mobile money channels.  In this work, we demonstrate how boosted decision trees (Adaboost) may be used to create credit scores (probability of repaying a low-value, short-term loan) for under-banked populations, allowing them to access credit that was previously unavailable due to a lack of financial data.  The boosted tree model demonstrated significant results over the original model used by the bank.  We show a 55% reduction in default rates while simultaneously offering credit opportunities to a million customers that were given a 0 credit limit in the bank’s original model.

Bio:

Skyler Speakman is a Research Scientist at IBM Research -- Africa.  His projects use data science to impact the lives of millions of people on the continent.  He believes that data collected through phones and drones will fundamentally change service delivery and African development in the next decade.  Skyler completed a Ph.D. in Information Systems at Carnegie Mellon University as well as a M.S. in Machine Learning.  He also holds masters in Mathematics, Statistics, and Public Policy.  He lives in Nairobi, Kenya with his wife and two young sons.

 

Presentation Slides: Click Here

Published: April 12, 2017

Author: Brandi Klingerman

Click for Full Article

April 20th, 2017

101 DeBartolo Hall

1:00 PM - 2:30 PM

 

What We Have Learned About Using Software Engineering Practices in Scientific Software

 

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Abstract: 

 

The increase in the importance of Scientific Software motivates the need to identify and understand which software engineering (SE) practices are appropriate. Because of the uniqueness of the scientific software domain, existing SE tools and techniques developed for the business/IT community are often not efficient or effective. Appropriate SE solutions must account for the salient characteristics of the scientific software development environment. To identify these solutions, members of the SE community must interact with members of the scientific software community. This presentation will discuss the findings from a series of case studies of scientific software projects, an ongoing workshop series, and the results of interactions between my research group and scientific software projects.

 

Bio:

 

Dr. Jeffrey Carver is an Associate Professor in the Department of Computer Science at the University of Alabama. He earned his PhD in Computer Science from the University of Maryland. His main research interests include empirical software engineering, software engineering for science, software quality, human factors in software engineering, and software process improvement. He has been the primary organizer of the SE4Science workshop series (http://www.SE4Science.org) focused on Software Engineering and Computational Science. He is a Senior Member of the IEEE Computer Society and a Senior Member of the ACM. Contact him at This email address is being protected from spambots. You need JavaScript enabled to view it..

 

Presentation Slides: Click Here

 

Published: March 07, 2017

Author: Brandi Klingerman

Click for Full Article

Author: Tara O'Leary

Imls

The University of Notre Dame Hesburgh Libraries received a grant from the Institute of Museum and Library Services (IMLS) National Leadership Grants for Libraries Program to conduct a collaborative planning effort to develop an open source Research Data & Software Preservation Quality Tool that addresses a universal need for preserving data and software.

As computation is increasingly interwoven with science, today’s researchers can explore and analyze data and possible scenarios more quickly than ever before. The associated software, data, and platforms of these scientific endeavors can foster rapid progress when shared between scientists and information systems. However, preserving and sharing the massive volume of research has become an increasingly challenging effort, and existing solutions are disjointed and vary dramatically across institutions and disciplines. This collaborative project will garner broad institutional and researcher input toward creating a framework of new and existing tools that addresses the critical need for data and software preservation.

The Notre Dame research team is led by Zheng (John) Wang, Associate University Librarian for the Hesburgh Libraries. Wang will be supported by co-PIs Richard Johnson, Co-Director of Digital Initiatives and Scholarship, and Natalie K. Meyers, E-Research Librarian, of the Hesburgh Libraries as well as co-PI Sandra Gesing, Ph.D. Computational Scientist, of Notre Dame’s Center for Research Computing (CRC).

“The digital age presents significant challenges for libraries and their partners across the research enterprise when it comes to preserving and sharing data and related software in a timely and streamlined manner,” said Wang. “It is imperative that Libraries take a collaborative leadership role with research faculty to develop open source tools that integrate research workflows and library processes to preserve data, software, and methods throughout the research lifecycle.”

The proposed Research Data & Software Preservation Quality Tool will allow reuse of preserved software applications, improve technical infrastructure, and build upon existing data preservation services. Additional outcomes include: captured digital workflows and methods, improved data and software provenance, automatically enhanced metadata, and improved file format recognition and data integrity. The planning design allows for input, consensus building, and support from regional, domestic, and international stakeholders. This collaborative approach will ensure that the tool will be flexible to fit a wide range of existing preservation tools and workflow systems. It will also broaden the awareness and adoption of across user communities.

“The project promises to strengthen international opportunities for collaborative software development, help like-minded organizations develop solutions across national and disciplinary borders, and empower the research data repository.” said Sandra Gesing.

The Center for Open Science (COS) joins the project team as a dedicated partner organization. The center’s role will be focused on reproducibility and interoperable data sharing aspects of the project. COS will also provision and support the project’s use of the Open Science Framework (OSF) to store, share, and collaborate on project components. “Data sharing, access and collaboration among researchers are some of our most important priorities at COS," said Rusty Speidel, Marketing Director at COS. "We are pleased to be involved in developing these critical tools and in furthering the preservation and sharing of open and transparent research."

Several organizations are project participants, including: the Scientific Information Service at CERN, The Research Data Alliance (RDA) Interest Group on Virtual Research Environments (VRE IG), RDA Interest Group on Metadata (Metadata IG), the Science Automation Technology Laboratory at the USC Information Sciences Institute, as well as Cal Poly’s Project Jupyter. The project team is pleased to have pledges of participation from the Confederation of Open Access Repositories (COAR), SHARE, DataCite, re3data.org registry of research data repositories, the Digital Research and Curation Center at Johns Hopkins University, Yale Libraries, and NCSA’s Midwest Big Data Hub.

Information gathered during the grant-funded work and a detailed project development proposal will be shared transparently using the Open Science Framework (https://osf.io/d3jx7) DOI: 10.17605/OSF.IO/D3JX7 and be archived at project’s end at Notre Dame’s research repository, CurateND (curate.nd.edu).

Contact: Natalie Meyers, Hesburgh Libraries, 574-631-1546, This email address is being protected from spambots. You need JavaScript enabled to view it.


About the Hesburgh Libraries

The Hesburgh Libraries is a diverse system of libraries and specialty centers that supports teaching, learning and research at the University of Notre Dame. Digital library services include CurateND and the Hesburgh Libraries’ Center for Digital Scholarship (CDS). The Hesburgh Libraries is committed to the preservation and sharing of research data. Through research, development, and community collaboration the libraries create tools and services that can be reused by like-minded institutions and contribute to local and national efforts that advance open knowledge sharing. Efforts at Notre Dame integrates data management consultation, data curation, and the development of new technologies to serve all disciplines and streamline the research lifecycle.

About Center for Research Computing

The Center for Research Computing at the University of Notre Dame is an innovative and multidisciplinary research environment that supports collaboration to facilitate discoveries in science and engineering, the arts, humanities and social sciences, through advanced computation, data analysis and other digital research tools. The Center enhances the University’s cyberinfrastructure, provides support for interdisciplinary research and education, and conducts computational research.

About Center for Open Science

The Center for Open Science (COS) is a non-profit technology startup founded in 2013 with a mission to increase openness, integrity, and reproducibility of scientific research. COS pursues this mission by building communities around open science practices, supporting metascience research, and developing and maintaining free, open source software tools. The Open Science Framework (OSF), COS’s flagship product, is a web application that connects and supports the research workflow, enabling scientists to increase the efficiency and effectiveness of their research. Researchers use the OSF to collaborate, document, archive, share, and register research projects, materials, and data. Learn more at cos.io and osf.io.

About the Institute of Museum and Library Services

The Institute of Museum and Library Services is the primary source of federal support for the nation’s 123,000 libraries and 35,000 museums. The mission of IMLS is to inspire libraries and museums to advance innovation, lifelong learning, and cultural and civic engagement. National Leadership Grants for Libraries (NLG) support projects that address challenges faced by the library and archive fields. Successful projects have the potential to improve library services nationwide. Grantees generate results such as new tools, research findings, models, services, practices, or alliances that can be widely used, adapted, scaled, or replicated to extend the benefits of federal investment. For more information about IMLS, visit www.imls.gov

Originally published by Tara O’Leary at conductorshare.nd.edu on December 12, 2016.