Wednesday, September 26th, 2018

3:00 p.m.

DeBartolo Hall Room 101

 

Dr. Sekou Lionel Remy

Research Scientist at IBM Research - Africa

 

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Novel Exploration Techniques (NETs) for Malaria Policy Interventions

The task of decision-making under uncertainty is daunting, especially for problems which have significant complexity. Healthcare policy makers across the globe are facing problems under challenging constraints, with limited tools to help them make data driven decisions. In this work we frame the process of finding an optimal malaria policy as a stochastic multi-armed bandit problem, and implement three agent based strategies to explore the policy space. We apply a Gaussian Process regression to the findings of each agent, both for comparison and to account for stochastic results from simulating the spread of malaria in a fixed population. The generated policy spaces are compared with published results to give a direct reference with human expert decisions for the same simulated population. Our novel approach provides a powerful resource for policy makers, and a platform which can be readily extended to capture future more nuanced policy spaces.

About Dr. Remy

Sekou L. Remy is a Research Scientist at IBM Research – Africa. A member of the healthcare team, he is excited about developing appropriate technologies which will transform Africa, and the world. Sekou loves learning, and is trained both in the Liberal Arts and Engineering. An proud alum of the Georgia Institute of Technology, and of Morehouse College (both in Atlanta, GA USA), Sekou has spent time learning and teaching at Clemson University, the University of Notre Dame, Spelman College, and at the University of Washington.

Tuesday, December 18th, 2018

3:00 p.m.

DeBartolo Hall Room 140

 

Robert H. (Bo) Ewald

President of D-Wave International

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An Introduction to Quantum Computing, D-Wave Style

This talk will briefly introduce the ideas and principles that have enabled us to create quantum computers. We’ll review the technologies and two major quantum architectures, then dive a little more deeply into how D-Wave’s quantum annealing computer works. Finally, we’ll survey the “proto-applications” that customers have been developing in areas of optimization, machine learning and material science that point the way to production use of quantum computers in the next few years.

About Bo Ewald

Bo Ewald has lengthy experience in the technology industry, as a user, engineer, customer and executive with some of the leading high performance computer systems and graphics companies. He is currently the President of D-Wave International, the world’s first commercial quantum computing company. Prior to that he was Executive Chairman of Perceptive Pixel, the touch sensitive display company, CEO of computer graphics pioneer Silicon Graphics, and President/COO of Cray Research, the first supercomputer company. Bo began his management career at the Los Alamos National Laboratory as the head of its Computing and Communications Division. He has been the CEO/Chairman of several start-up companies including Linux Networx, EStamp and Scale8. He is involved in various industry organizations and was appointed to the President's Information Technology Advisory Committee by Presidents Clinton and Bush. He has also served on the Boards of several public and private companies.

Friday, September 14th, 2018

3:00 p.m.

DeBartolo Hall Room 101

 

Dr. Alun Preece

Professor of Intelligent at Cardiff University

 

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SHERLOCK: Simple Human Experiments Regarding Locally Observed Collective Knowledge

This talk will set out the motivation behind SHERLOCK in the context of obtaining situational awareness and tactical intelligence in policing and security operations, with real-world examples from our field exercises including the 2014 NATO Summit which was the largest peacetime security operation in UK history. I will explain how these exercises scoped our requirements for a conversational knowledge-based agent capable of operating in offline settings as well as online, leading to the implementation of the open source CENode software and the design of the SHERLOCK games which to date have been played by over 200 people, working in teams to collaboratively build a crowdsourced situational knowledge base. The talk will also briefly cover other applications of the same underlying technology, including work done by colleagues at IBM UK. Finally, I will point to current directions of our work, looking at explainable machine learning services, in the context of the Distributed Analytics and Information Sciences International Technology Alliance (DAIS ITA) led by IBM.

About Dr. Preece

Alun Preece is Professor of Intelligent Systems at Cardiff University where he Co-Directs the interdisciplinary Crime & Security Research Institute and is deputy head of the School of Computer Science and Informatics. Prof Preece is UK Academic Technical Area Lead for the $80M US/UK Distributed Analytics and Information Sciences International Technology Alliance (DAIS ITA, 2016-2026) funded by the US & UK Governments and led by IBM, in which he also leads the project "Anticipatory Situational Understanding" involving a team from Airbus, BAE Systems, IBM, UCL, and UCLA. Previously, he served in the same role for the Network and Information Sciences International Technology Alliance (NIS ITA, 2006-2016).

Friday, August 3rd, 2018

1:00 p.m.

DeBartolo Hall Room 102

 

Skyler Speakman

Research Scientist at IBM Research - Africa

 

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Pattern Detection on Hidden Layers of Neural Networks

The motivating theme for this work is to view neural nets as data-generating systems and then detect patterns in that generated data with the overall goal of increasing the explainability of the models . One approach to this problem is to identify anomalous subsets of neurons that have higher-than-expected activations. The subset scanning approach to anomalous pattern detection has been applied in multiple domains including disease outbreak detection, crime prediction, detecting the spread of water contaminants, customs monitoring, network intrusion detection, and bias detection in criminal sentencing. [Event & Pattern Detection Lab https://epdlab.heinz.cmu.edu/]. This is the first work to apply subset scanning techniques to data generated within neural networks. A majority of work in deep learning has focused on identifying and encouraging a highly-activated single neuron in the ‘output layer’ of neural networks (usually denoting a class probability). Pattern detection through subset scanning identifies groups of highly-activated neurons in the hidden layers in order to detect and identify patterns not visible from any individual neuron activity alone. A promising application of this methodology is detecting and characterizing adversarial noise that has been added to images in order to 'trick' neural networks into misclassification. We will present early results in this domain and then follow up with many exciting extensions to continue the work.

About Skyler Speakman

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.

Date: Wednesday, July 25th

Time: 9:30 - 11:45 AM

Location: Jordan Hall of Science Galleria

Click Here for Further Details

Published: July 23rd, 2018

Author: Brandi Klingerman

Click Here for Full Article

 

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.