SWTs

This symposium provides a forum for brainstorming and problem solving by bringing world–leading researchers in the areas that span energy efficiency and computing together with researchers interested in investigating solutions to the problems that include, but are not limited to: power–aware algorithm and software design, power–efficient hardware and system design, power–awareness characterization, metrics, and modeling, thermal behavior and control, life–cycle analysis of computing infrastructures, pervasive sustainability, and smart grid and energy supply and demand matching.

SWT Leaders:

Behrooz Shirazi (Primary Contact)
Washington State University
shirazi@wsu.edu

Adolfy Hoisie
Brookhaven National Laboratory
ahoisie@bnl.gov

This workshop invites researchers and practitioners to reflect on ecological, social, cultural, political and economic dimensions of sustainability and the question of how sustainable systems can be developed.

The workshop will start with presentations and panel discussion on the concepts, methods and implementation challenges when shaping a sustainable and resilient system. Participants will then be broken into groups to discuss specific project cases.

SWT Leader:

Rüdiger Goldschmidt
University of Stuttgart
ruediger.goldschmidt@zirius.uni-stuttgart.de

This tutorial will discuss in detail attack detection through unsupervised anomaly detection. It will review the construction of an evaluation campaign through i) the identification of the attack models and datasets, ii) the selection and discussion of unsupervised algorithms, even when iii) adopting meta-learning, iv) the identification of target metrics, v) the execution of the algorithms and vi) their comparison.

Attendees will also be involved in an hands-on session where algorithms will be executed on public attack datasets thanks to RELOAD, a tool for the Rapid EvaLuation Of Anomaly Detection algorithms. The tool is primarily meant to be used by non-experts that start approaching binary classification using ML algorithms, and hides details which may be misleading for beginners, executing analyses through a simple UI.

SWT Leaders:

Tommaso Zoppi (Primary Contact)
University of Florence
tommaso.zoppi@unifi.it

Andrea Ceccarelli
University of Florence
andrea.ceccarelli@unifi.it

Andrea Bondavalli
University of Florence
bondavalli@unifi.it

The goals of this tutorial are to inform and guide researchers in the practice of netnographic research. The half-day session introduces netnography and explains its recent evolution in the systems science field with an emphasis on specific hands-on methods for conducting this style of research and examples of its successful completion. The tutorial will provide participants with a solid introduction to the operations, opportunities, and challenges of netnography within the broader context of qualitative social media research. The session will be led by a researcher who authored five books covering the method and its applications.

At the end of this hands-on half-day session (bring your own computers and social media research topics!), participants will be able to:

• Discern and develop appropriate topics and questions for netnographic research;
• Articulate the main movements and procedures that distinguish a netnography project from other approaches;
• Discuss the ethical challenges in netnography and how they can be addressed;
• Describe the conceptual bases of new and emerging forms of netnography such as the auto-netnography, transformative netnography, and more-than-human netnography;
• Explain the opportunities and challenges of incorporating AI and natural language processing procedures into netnographic research.

SWT Leaders:

Robert Kozinets (Primary Contact)
University of Southern California
rkozinets@usc.edu

Ulrike Gretzel
Netnografica LLC
gretzel@usc.edu

This panel will discuss the conceptual and practical implications of computing technologies enhancing our work, decision-making, and cognitive process. Invited panelists from areas of artificial intelligence, augmented intelligence, robotics, and augmented cognition will share their findings and thoughts on how to better understand and harness the power of such technologies in future human work.

The panel discussion will encompass the wide range of topics including, but not limited to:

• Algorithms and the large-scale behavioral data enhancing decision-making in firms
• The potential impacts of humanizing artificial intelligence embodied in physical forms (i.e., robots) in workspaces
• Psychological and emotional impacts of interacting with intelligent agents
• The use of AI and IA beyond individuals and its consequences in organizations
• The augmentation of human cognition, emotion, and creativity with artificial intelligence

SWT Leaders:

Souren Paul (Primary Contact)
Northern Kentucky University
Souren.paul@gmail.com

Lina Zhou
University of North Carolina at Charlotte
lzhou8@uncc.edu

This symposium intends to address the most pressing legal and societal issues created by rapid advances in information technology and by the emergence of new giant platform technology companies. It will create a forum where scholars, elected officials, regulators, corporate executives, and other individuals can assemble to discuss how digital transformation can be implemented in a way that minimizes the unanticipated negative impacts and maximizes value creation, balance value sharing, and achieve a joyous society.

SWT Leaders:

Eric K. Clemons (Primary Contact)
University of Pennsylvania
clemons@wharton.upenn.edu

Helmut Krcmar
Technical University of Munich
krcmar@in.tum.de

Tung Bui
University of Hawaii at Manoa
tungb@hawaii.edu

1pm – 4pm, January 7, 2020

Building on recent research of efforts by organizations to reach various audiences using automated technology (e.g., chatbots), this workshop seeks to develop a forward-looking research agenda for scholars studying the role of emerging technology in engaging consumers and other stakeholders. This research examines a broader turn toward social bots, which are designed to facilitate conversational interactions between humans and machines, and which have existed in various forms since the early days of computers.

We are especially interested in intrapreneurship and experimentation within organizations, and in patterns of deployment (or aborted deployment) of such technologies. Although our own research in this area has focused on communication and news media, we welcome participants from related disciplines and fields, with the hope that our discussions—and the resulting research agenda—will explore chatbots and other automated tools in a variety of organizational contexts.

SWT Leaders:

Colin Agur (Primary Contact)
University of Minnesota – Twin Cities
cpagur@umn.edu

Valerie Belair-Gagnon
University of Minnesota – Twin Citie
vbg@umn.edu

Seth Lewis
University of Oregon
sclewis@uoregon.edu

9am – 12pm, January 7, 2020

QUANTUM IS HERE– AND IT’S REAL!

No previous knowledge or experience necessary for this session.  

What will you learn?

• How to program for Quantum computing without a PhD in quantum physics
• How Quantum is different – REALLY different – from classic computing. Qiskit and IBM Q Experience (IQX) resources can help you make the leap.Get your mindset in shape for the future!
• How early applications of Quantum computing for business and science.
• How Quantum is relevant to faculty and students in business schools, I/T programs, as well as computer science. The HICSS Keynote Speaker, Dr. Itoh, from Keio University in Japan, will be describing corporate/ academic partnerships happening today. Get ready for the discussion on Wednesday.
• How the field of quantum computing is emerging and how the workforce for the quantum economy needs to be prepared.  Also how students, educators, and society will benefit.

Quantum is here, and it’s real!  How will it affect you?  What is here now, and what is coming soon?  IBM Q is an industry first initiative to build universal quantum computers for business and science. IBM has built the world first integrated quantum computer. IBM’s cross-disciplinary team is developing scalable quantum systems and potential applications for the technology made available today.

IBM Q quantum devices are accessed using Qiskit, a modular, open-source programming framework.  A worldwide network of Fortune 500 companies, academic institutions, and startups use IBM Q technology and collaborate with IBM Research to advance quantum computing.

In addition, IBM Q offers a variety of educational content at all levels. We are committed to maintaining our leadership in quantum computing and driving a roadmap of innovation for through the IBM Q Network, and the extended IBM Q community, including academics worldwide.

Tentative Agenda

NOTE: The Master of Ceremonies for this unique session will be Dr. Bob Sutor, Vice President, IBM Q Ecosystem Development. He will ensure that your questions are answered and that you derive real value from this session. Join us!

9:00 – 10:15
Bob Sutor: Quantum is Really Here!  What is this new technology?  How does it work?  Why does it require a completely different way of thinking?  Where are some of the early applications?  Practical examples provided, as well as available, no charge resources for all academics.

10:45 – 12:00
Andrew Wack: Qiskit and Aqua are the keys to leveraging Quantum in research and in the classroom –   an open-source quantum computing framework enabling users from quantum scientists through domain experts in chemistry, AI and finance as well as students at any level to easily utilize quantum systems. Learn how to use to tools to enable students at any level to begin building their quantum computing journey.

SWT Leaders:

JoAnn Winson (Primary Contact)
Global University Program, IBM Corporation
jwinson@us.ibm.com

Bob Sutor
Vice President, IBM Q Ecosystem Development
sutor@us.ibm.com

Andrew Wack
IBM Q System Software Architect
awack@us.ibm.com

The LF AI & Data Foundation is a project of The Linux Foundation that supports open source innovation in artificial intelligence, machine learning, deep learning and data open source projects. OpenDS4All (Open Data Science 4 All) is one of the projects that is being sponsored by Linux AI & Data.

OpenDS4All is an open source project built to accelerate the creation of data science curricula at academic institutions. Starting a Data Science program from scratch is incredibly difficult, as building a curriculum requires significant resources. By making a “starter set” of training materials, IBM, ODPi and the University of Pennsylvania, working together with cross-industry partners and educators, can help accelerate the availability of skills building programs around the world.

The aim of the workshop is to introduce OpenDS4All, an Open Education project that was launched during 2020 to accelerate the development of Data Science curricula (at undergraduate or graduate level) for academic institutions. During the workshop, we will review the content of one or two of the modules (hosted on GitHub) and show how to construct various curricula from the educational modules that covers the core of Data Science. Each educational module contains a set of PowerPoint slides and most modules have an accompanying Jupyter notebook with Python code showing how the discussed theory can be applied in practice. The workshop will include a hands-on component showing how the notebooks can be executed in several environments, such as Binder and Watson Studio.

SWT Leaders:

Andre de Waal (Primary Contact)
IBM and Chair of Technical Steering Committee, OpenDS4All project at Linux Data & AI
Andre.dewaal@ibm.com

Haluk Demirkan
University of Washington Tacoma
haluk@uw.edu

Open and premium quantum computing systems have been available on the cloud since 2016. Since then, over 300,000 people have registered to use quantum systems via the online IBM Quantum Experience. They have run over 750 billion circuits on real quantum hardware. Software developers have downloaded the open-source Qiskit quantum software development kit over 500,000 times. Thousands of students have learned to code with Python and Qiskit through events like the Qiskit Global Summer School.

Researchers and technologists are working on algorithms and approaches for industries as diverse as aerospace, automotive, banking, capital markets, chemicals, energy, insurance, and manufacturing. Quantum computing intersects disciplines like AI, engineering, computer science, physics, mathematics, chemistry, and quantitative finance.

In this interactive tutorial, we’ll give you an update on the technology, the road map ahead, and how you should start integrating quantum computing into your teaching and work. It is open to all, and attendees of the 2020 event will learn of the many exciting developments that have since taken place.

Agenda

• Introduction and Welcome
• The “What” and “Why” of Quantum Computing
• An Introduction to Python Coding with Qiskit
• Quantum Computing: Roadmap for the Future
• Preparing the Quantum Computing Workforce of the Future

SWT Leaders:

JoAnn Winson (Primary Contact)
IBM Global University Programs
jwinson@us.ibm.com

Bob Sutor
IBM Research
sutor@us.ibm.com

Andrew Wack
IBM
awack@us.ibm.com

Robert Loredo
IBM

The combination of Edge, low cost IoT devices, accurate and efficient Artificial Intelligence algorithms, automated toolchains to train Machine Learning models, and Cloud-Native techniques to manage distributed workloads at Internet scale make the intersection of these maturing technologies very rich for innovation.

This workshop will explore Edge Computing topics around deploying and managing AI models on the edge, IoT / Edge security / data privacy best practices, production scale distributed container management, designing AI workloads for constrained systems, and industrial / retail / consumer / 5G / Automotive spatial mapping use cases for edge computing.

SWT Leaders:

JoAnn Winson (Primary Contact)
IBM Global University Programs
jwinson@us.ibm.com

John Walicki
Developer Ecosystem Group, IBM Corporation
walicki@us.ibm.com

Grady Booch
IBM Research
gbooch@us.ibm.com

Jim Spohrer
Cognitive OpenTech, IBM Corporation
spohrer@us.ibm.com

This tutorial will provide an overview of the key aspects that an organization should have in place to build an enterprise level BDA program. The workshop will provide very specific and hands-on material to help organizational and educational institutions embrace BDA in an organized manner, following best practices. It is organized into these main areas:

• BDA Overview – We will start with key definitions and differentiation of various BDA approaches and terminology.
• Analytical Modeling – Selected key topics pertaining model selection and model specification will be discussed. BDA has evolved rapidly and there is a wide variety of methods and approaches. We divide the related decisions into two categories: (a) model selection – overview of various modeling methods and approaches, depending on the specific analytic problems and goals; and (b) model specification – overview of how to select the most effective set of predictors and the data pre-processing that may be required. In this section we will also describe in depth the concept of machine learning and discuss various modern approaches. We will provide a detailed handout with a summary of predictive modeling approaches.
• Analytics Capabilities – We will provide an overview of popular body of knowledge and analytic frameworks. We will also provide an overview of the most popular BDA tools, both commercial and open source. We will also provide a summary of R scripts to fit and evaluate some of the most popular machine learning and predictive models and introduce the concept of cross-validation for model fitting and evaluation and parameter tuning.
• BDA Management – We will address issues related to the alignment of business needs with organizational structures, rules, compliance, governance and life cycle models.

SWT Leaders:

Frank Armour (Primary Contact)
American University
farmour@american.edu

J. Alberto Espinosa
American University
alberto@american.edu

Which researcher has not wished, when a key lab member graduates, that they could avoid consuming precious time and resources in training new people about seemingly mundane data and tool issues?  Good data and software management ensures preservation of knowledge and smooth continuation in the context of staff and student turn-over.  Researchers who do not or cannot share data still benefit from good data and software stewardship practices, inspired by the FAIR guiding principles.

Good stewardship practices are required to ensure that data is properly described for re-use, stored in medium and formats accessible to future users, and simply not lost in the lab. Establishing good data and software management practices provide researchers from all disciplines with the following benefits:

• Data, software, and knowledge preservation throughout the life cycle of a project and beyond
• Improved training and communication through tools and protocols
• Systematic training practices that can be tailored to individual labs or projects
  Improved collaboration within teams through well-established data and software development practices
• Ease of re-use for future users, from future students, lab members, external collaborators, and stakeholders
• Compliance with funding agency requirements
• Interoperability with publishing platforms and fulfillment of publishers’ requirements
• Data and software re-use embedded in current and future practices

In this tutorial, participants will learn state-of-the-art stewardship practices to support preservation and reproducibility. The tutorial will be organized around three mini-sessions, each with a short demo or presentation of tools, and the bulk of time devoted to a hands-on participatory activities. The tutorial will conclude with a panel of open questions, including suggestions for future areas of emphasis for this tutorial.

For more information about the tutorial, please visit https://sites.google.com/view/data-stewardship-and-reuse/home

SWT Leaders:

Line Pouchard (Primary Contact)
Brookhaven National Laboratory
pouchard@bnl.gov

Natalie Meyers
University of Notre Dame
natalie.meyers@nd.edu

[Presentation Slides from HICSS-52]

The volume and complexity of available data is increasing at an unprecedented rate. However, the human ability to analyze and comprehend data remains constant. Visual Analytics is the science of analytical reasoning facilitated by interactive visual interfaces. It combines scientific investigation of information processing in human-computer cognitive systems with the design and implementation of interactive visualization that support this processing, building upon research methods and theories from computer science, management information systems, and the cognitive, perceptual, and social sciences.

The goals of this tutorial are to inform and guide researchers and practitioners in the practice of interdisciplinary visual analytics research and development, and to discuss the far-reaching and practical applications of visual analytics technologies.

Talks will focus on the perceptual, cognitive, and communication theories that can inform VA interaction design and on practical approaches for building, customizing and deploying visual analytics in organizations. The half-day session introduces VA with an emphasis on existing methods for research and methods and visual analytics at large scale.

Agenda

• Introduction to Visual Analytics: Current Research and Practices
• Applications and Issues in Large-scale Visualization and Visual Analytics
• An interactive panel discussion of the future directions for visual analytics as a field

SWT Leaders:

Kelly Gaither (Primary Contact)
University of Texas at Austin
kelly@tacc.utexas.edu

David Ebert
Purdue University
ebertd@ecn.purdue.edu

A personal AI agent (PAIA) belonging to each of us could maximize the value of our personal data by fully utilizing the data to enhance the quality of our life and work, while disclosing the data to others in limited cases. The whole value created thereof could exceed 30% of GDP. The production and operation of such PAIAs therefore would be by far the most profitable business. This PAIA business is likely to prosper within a decade, aggregating our personal data to each of us to let our PAIAs utilize our data to assist or perhaps control us. Most of our actions of selecting and purchasing something would then follow our PAIAs’ decisions because we are all lazy without exception. Governance of PAIAs is hence an essential issue concerning our privacy, human rights, welfare, economy, politics, culture, and so forth.

This symposium will shed lights on such risks and benefits of PAIA from diverse viewpoints encompassing computer science, marketing science, ethics, legal science, sociology, among others. Below are some topics to be addressed.

• Technical foundation of PAIA
• Social acceptability of PAIA and PAIA business
• Governance of personal data using PAIA
• Governance of PAIA for both personal and societal values
• Role of PAIA in Society 5.0

For more information about this symposium, please visit http://www.sict.i.u-tokyo.ac.jp/members/hasida/pai/

SWT Leaders

Koiti Hasida (Primary Contact)
The University of Tokyo and RIKEN
hasida.koiti@i.u-tokyo.ac.jp

Keiko Toya
Meiji University
i.ktoya@gmail.com

Ayako Kato
Toyo University

Hiroshi Nakagawa
RIKEN
hiroshi.nakagawa@riken.jp

This tutorial will provide participants with a solid introduction to the opportunities and challenges of text mining, using both commercial and open-source tools, and help to situate these approaches within the broader context of big data analytics.

At the end of this tutorial, participants will be able to:

• discuss the role of text mining in big data analytics;
• understand the main opportunities and challenges in text analysis;
• articulate several conceptual approaches to text analytics;
• explain how to automate the process of collecting textual data;
• describe commercial and open source software appropriate for text mining.

There will be a hands-on session, please bring computer and data!

SWT Leaders

Derrick Cogburn (Primary Contact)
American University
dcogburn@american.edu

Normand Peladeau
Provalis Research Corp
peladeau@provalisresearch.com

Michael Hine
Carleton University
mhine@sprott.carleton.ca