Events

  • Tue
    22
    Jan
    2019
    11:30 amEhrlicher Room

    MISC will kick off the winter term with lightning talks from our faculty on campus. Nia Dowell, Mustafa Naseem, Audrey Bennett, and Nikola Banovic will be giving a brief introduction of their research.

  • Tue
    05
    Feb
    2019
    11:30 amSpace 2435

     

    When and where: 2/5 @11:30 AM, North Quad, Space 2435 (add to calendar)

    Please help forward this announcement to anyone who might be interested! Light lunch will be served.

    Abstract: Teaching programming as a way to express ideas, communicate with others, and understand our world is one of the oldest goals for computing education. The inventor of the term "computer science'' saw it as the third leg of STEM literacy. In this talk, I lay out the history of the idea of universal computational literacy and describe what it will take to get there.

    Bio: Mark Guzdial is a first-year Professor in CSE and in Engineering Education Research. He studies how people come to understand computing and how we can make that process more effective. He is an ACM Fellow and will be receiving the 2019 ACM SIGCSE Outstanding Contribution to CS Education Award.

  • Tue
    12
    Feb
    2019

     

    On Tuesday 2/12, Samuel Carton, a PhD Candidate from the School of Information will present his work on “The Design and Evaluation of Algorithms for Explaining Text Classifiers”

    Please help forward this announcement to anyone who might be interested! Light lunch will be provided.

    Please RSVP by 12 PM on 2/10 if you will be there.

    Abstract

    The machine learning community has recently begun to recognize the need for interpretable predictive models. While such models can be trained to be very accurate, sometimes even more accurate than their human counterparts on average, they have a tendency to fail unexpectedly and are ill-equipped to deal with nuance and outliers. One of the biggest challenges in this area is in defining what it means for an explanation to be effective in the first place, and then in designing algorithms optimized for this quality. In this talk I discuss two papers: the first is an algorithm for explaining text classifier decisions by producing high-recall attention masks, and the second is a crowdsourced experiment exploring the impact of this type of explanation on human performance in a model-assisted decision task.

    Bio

    Sam is a PhD candidate in the school of information, advised by Paul Resnick and Qiaozhu Mei. He received a BS in computer science from Northwestern University. Sam's current research interests are in explainable machine learning, where he is interested both in engineering new explanation methods as well as understanding the human factors that determine what explanations are effective in real-world settings. His past work includes projects on tracking and visualizing the spread of rumors over social media as well as predictive modeling of police misconduct. His professional experience includes an internship with Microsoft Research as well as the Data Science for Social Good Fellowship at the University of Chicago.

  • Tue
    19
    Feb
    2019

    When and where:

    February 19, 11:30 AM, North Quad, Ehrlicher Room (room 3100) (add to calendar)

    Light lunch will be provided at 11:30 AM. The talk will begin at noon.

    Please RSVP by 12 PM on 2/17 if you will be there.

    Abstract: Many students in large survey courses are reluctant to pose verbal questions during class. Entreating students with “Any questions?” more often than not fails to produce a response and, when it does, comes from a small subset of all students. This presentation reports on the use of a backchannel in a blended course and how the backchannel affected student participation based on a priori comfort level with verbal questioning.

    The use of a backchannel increased student inquiry in class dramatically but, more importantly, its use virtually eliminated the gender bias in student inquiry often seen in science courses. It was found that the use of a backchannel had a significant positive effect on the level of participation by female students who had professed a greater discomfort with verbal questioning in the initial course survey. Additionally, a longitudinal study was conducted to identify students’ perceived value of the backchannel to improving verbal participation in subsequent courses. The longitudinal survey showed that a majority felt strongly that the availability of the backchannel was highly valuable and its availability in the first-year course changed their willingness to ask verbal questions in subsequent courses.

    Bio: Perry Samson is an Arthur Thurnau Professor at the University of Michigan with appointments in the College of Engineering and the School of Information. Prof. Samson teaches courses in extreme weather and climate and air pollution modeling. Perry is also an entrepreneur as a co-founder of The Weather Underground and LectureTools and serves as a mentor for education technology internships.

     

  • Tue
    26
    Feb
    2019

     

    When and where: 2/26 @11: 30 AM, Ehrlicher Room (North Quad room 3100) (add to calendar)

    Please help forward this announcement to anyone who might be interested! Light lunch will be provided. Please RSVP by 12 PM on 2/24 if you will be there.

     

    Abstract

    After a brief introduction to her collaborative research, Prophet will focus on one current project, Pocket Penjing. Cultivating public engagement in environmental issues is not simply a matter of educating and presenting factual data to citizens, it necessitates encouraging people to actively engage with, and articulate, these concerns to others in their own localities in a socially meaningful way.  We developed an app, Pocket Penjing, to grow simulated 3D trees from live environmental data displayed using augmented reality (AR). We tested the app via two studies with over 70 Chinese participants. The first, a user evaluation and design study, recommended new features. In the second, a focus group responded to the redesigned app which was delivered by a wizard-of-oz demonstration. Our findings point to the importance of 1) modeling local variants and 2) sharing AR trees with friends and family. Based on these findings, we argue that AR cultural artefacts that encourage citizen construction of culturally-relevant social spaces and interactions support richer, situated sense-making of data.

    Bio

    Visual artist, Jane Prophet, works across media and disciplines to produce apps, objects and installations, frequently combining traditional and computational media. Prophet’s papers position art in relation to contemporary debates about new media and mainstream art, feminist technoscience, artificial life and ubiquitous computing. Professor Prophet received a PhD in arts education from Warwick University in 1995. She has contributed widely to debates about art and computation, in particular, interdisciplinary collaboration. Her current research spans augmented reality, 3D print and projection mapping. She joined Stamps School of Arts & Design in July 2018 as their inaugural associate dean for Research

  • Tue
    12
    Mar
    2019

    When and where: 3/12 @11: 30 AM, Ehrlicher Room (North Quad room 3100) (add to calendar)

    Please help forward this announcement to anyone who might be interested! Light lunch will be provided. Please RSVP by 12 PM on 3/10 if you will be there.

     

    Abstract: Modern-day programming is incredibly complex, and people from all sorts of backgrounds are now learning it. It is no longer sufficient just to learn how to code: one must also learn to work effectively with data and with the underlying software environment. In this talk, I will present three systems that I have developed to support learning of code, data, and environment, respectively: 1) Python Tutor is a run-time code visualization and peer tutoring system that has been used by over five million people in over 180 countries to form mental models and to help one another in real time, 2) DS.js uses the web as a nearly-infinite source of motivating real-world data to scaffold data science learning (UIST 2017 Honorable Mention Award). 3) Porta helps experts create technical software tutorials that involve intricate environmental interactions (UIST 2018 Best Paper Award). These systems collectively point toward a future where anyone around the world can gain the skills required to become a productive modern-day programmer.

    Bio: Philip Guo is an assistant professor of Cognitive Science and an affiliate assistant professor of Computer Science and Engineering at UC San Diego. His research spans human-computer interaction, programming tools, and online learning. He now focuses on building scalable systems that help people learn computer programming and data science. He is the creator of Python Tutor (http://pythontutor.com/), a widely-used code visualization and collaborative learning platform. So far, over five million people in over 180 countries have used it to visualize over 75 million pieces of Python, Java, JavaScript, C, C++, and Ruby code. Philip's research has won Best Paper and Honorable Mention awards at the CHI, UIST, ICSE, and ISSTA conferences, and an NSF CAREER award.

    Philip received S.B. and M.Eng. degrees in Electrical Engineering and Computer Science from MIT and a Ph.D. in Computer Science from Stanford. His Ph.D. dissertation was one of the first to create programming tools for data scientists. Before becoming a professor, he built online learning tools as a software engineer at Google, a research scientist at edX, and a postdoc at MIT. Philip's website http://pgbovine.net/ contains over 500 articles, videos, and podcast episodes and gets over 750,000 page views per year.

  • Tue
    19
    Mar
    2019

    When and where:

    March 19th, 11:30 AM, North Quad, Ehrlicher Room (room 3100) (add to calendar)

    Light lunch will be provided at 11:30 AM. The talk will begin at noon.

    Please RSVP by 12 PM on 3/17 so we know how much food to order.

     

    Abstract: Charts, graphs, and other information visualizations amplify cognition by enabling users to visually perceive trends and differences in quantitative data. While guidelines dictate how to choose visual encodings and metaphors to support accurate perception, it is less obvious how to design visualizations that encourage rational decisions and inference. I'll motivate several challenges that must be overcome to support effective reasoning with visualizations. First, people's intuitions about uncertainty often conflict with statistical definitions. I'll describe how visualization techniques for conveying uncertainty through discrete samples can improve non-experts' ability to understand and make decisions from distributional information. Second, people often bring prior beliefs and expectations about data-driven phenomena to their interactions with data (e.g., I suspect support for candidate A is higher than reported) which influence their interpretations. Most design and evaluation techniques do not account for these influences. I'll describe what we've learned by developing visualization interfaces that encourage users to reflect on their expectations and comparing elicited prior and posterior expectations to normative accounts of belief updating.
    Bio: Jessica Hullman is an Assistant Professor in Computer Science and Journalism at Northwestern. The goal of her research is to develop computational tools that improve how people reason with data. She is particularly inspired by how science and data are presented to non-expert audiences in data and science journalism, where the goal of conveying a clear story often conflicts with goals of transparency and faithful presentation of uncertainties. Her current research aims to develop uncertainty techniques and interactive visualizations that enable users to articulate prior beliefs and make more informed decisions. Jessica's research has been supported by the NSF (CRII, CAREER), Navy, Google, Tableau, and Adobe. Prior to joining Northwestern in 2018, she spent three years as an Assistant Professor at the University of Washington Information School. She completed her Ph.D. at the University of Michigan and spent a year as the inaugural Tableau Software Postdoctoral Scholar in Computer Science at the University of California Berkeley in 2014.
  • Tue
    26
    Mar
    2019
  • Tue
    02
    Apr
    2019

    When and where:

    April 2nd, 11:30 AM, North Quad, Ehrlicher Room (room 3100) (add to calendar)

    Light lunch will be provided at 11:30 AM. The talk will begin at noon.

    Please RSVP by 12 PM on 3/31 so we know how much food to order.

    Abstract: Access to healthcare and health information is of major global concern. The stark inequality in the availability of health data by country, demographic groups, and socioeconomic status impedes the identification of major public health concerns and implementation of effective interventions. This data gap ranges from basic disease statistics, such as disease prevalence rates, to more nuanced information, such as public attitudes. A key challenge is understanding health information needs of under-served and marginalized communities. Without understanding people's everyday needs, concerns, and misconceptions, health organizations lack the ability to effectively target education and programming efforts.

    In this presentation, we focus on the lack of comprehensive, high-quality data about information needs of individuals in developing nations. We propose an approach that uses search data to uncover health information needs of individuals in all 54 nations in Africa. We analyze Bing searches related to HIV/AIDS, malaria, and tuberculosis; these searches reveal diverse health information needs that vary by demographic groups and geographic regions. We also shed light on discrepancies in the quality of content returned by search engines.

    We conclude with a discussion on computationally-informed interventions both on- and off-line in health and related domains and the Mechanism Design for Social Good research initiative.

    This talk is based on joint work with Shawndra Hill, H. Andrew Schwartz, Peter M. Small, and Jennifer Wortman Vaughan.

    Bio: Rediet Abebe is a Ph.D. candidate in computer science at Cornell University, advised by Professor Jon Kleinberg. Her research focuses on algorithms, AI, and their applications to social good. She uses computational insights to improve access to opportunity, with a focus on under-served and marginalized communities. As part of this research mission, she co-founded and co-organizes the Mechanism Design for Social Good (MD4SG) initiative, an interdisciplinary, multi-institutional research group. She is also a co-founder and co-organizer of Black in AI, a transcontinental group aimed at increasing the presence and inclusion of Black researchers and practitioners in the field of AI. Her research is deeply influenced by her upbringing in her hometown of Addis Ababa, Ethiopia, where she lived until moving to the U.S. in 2009. Her work has been generously supported by fellowships and scholarships through Facebook, Google, the Cornell Graduate School, and the Harvard-Cambridge Fellowship.

  • Tue
    09
    Apr
    2019

    When and where:

    April 9th, 11:30 AM, North Quad, Ehrlicher Room (room 3100) (add to calendar)

    Light lunch will be provided at 11:30 AM. The talk will begin at noon.

    Please RSVP by 12 PM on 4/7 so we know how much food to order.

    Abstract: The proliferation of information and communication technologies (ICTs) and the increased use of ICTs across the life course yields ample opportunities to use ICTs to improve health and quality of life. Shelia Cotten, an MSU Foundation Professor in the Department of Media and Information at Michigan State University, provides an overview of some of her recent research focused on ways individuals use ICTs and the impacts of this use on their health and quality of life — from projects focused on wearables, mobile phones, to autonomous vehicles. She also provides results of a randomized controlled trial designed to use technology to improve quality of life among older adults.

    Bio Shelia Cotten, a sociologist, is an MSU Foundation Professor and the Associate Chair for Research in the Department of Media and Information at Michigan State University. She studies technology use across the life course, and the health, quality of life, workforce, and educational impacts of this use. Her work has been funded by the National Science Foundation and the National Institutes of Health, among others. She is a former Chair of the Communication, Information Technologies, and Media Sociology section of the American Sociological Association.

     

    Please help forward this announcement to anyone who might be interested!

  • Tue
    16
    Apr
    2019
    11:30 amEhrlicher Room

    When and where:

    April 16th, 11:30 AM, North Quad, Ehrlicher Room (room 3100) (add to calendar)

    Light lunch will be provided at 11:30 AM. The talk will begin at noon.

    Please RSVP by 12 PM on 4/14 so we know how much food to order.

    Abstract: People increasingly turn to digital tools to help make sense of and improve various aspects of their lives, especially health. However, many encounter many barriers to collecting, reflecting, and acting on their data. They also turn to others, such as peers and experts, for help, but these collaborations bring additional barriers and challenges. In this talk, I will describe current practices and breakdowns, using food tracking as an example. Designs that focus on people's goals can help narrow and focus the tracking process, reducing burdens and improving people's understanding. Inclusion of contextual data can support empathetic collaboration and help patients and health experts develop personalized plans. Designing for collaboration from the start of tracking can help people more efficiently and effectively manage their health while avoiding misunderstandings and mis-aligned goals.

    BioSean Munson is an Associate Professor at the University of Washington's Department of Human Centered Design and Engineering and a member of the DUB group. He studies how people interpret their personal data to understand the relationship between their behaviors, contexts, and outcomes, and also to make sense of the world around them. He research focuses on health and wellness as well as diversity of news and information access. Sean completed a BS in Engineering at Olin College in 2006 and his PhD at UMSI in 2012. He is a 2016 recipient of an NSF Faculty Early Career Development Award. Previously, he has been a political blogger and, while working at Boeing, designed concepts for future passenger airplane interiors.

     

    Please help forward this announcement to anyone who might be interested!

  • Tue
    23
    Apr
    2019
    11:30 amEhrlicher Room

    When and where:

    April 23rd, 11:30 AM, North Quad, Ehrlicher Room (room 3100) (add to calendar)

    Light lunch will be provided at 11:30 AM. The talk will begin at noon.

    Please RSVP by 12 PM on 4/21 so we know how much food to order.

    Abstract:  We often equate keeping teens safe online to shielding them from experiencing online risks – such as information breaches, cyberbullying, sexual solicitations, and exposure to explicit content. However, this abstinence-only approach tends to be very parent-centric and does not take into account the developmental needs and experiences of our youth. For instance, parental control apps operate by monitoring and restricting teens’ mobile activities, instead of helping teens self-regulate their online behavior. On one hand, we tell teens they need to care about their online privacy in order to stay safe, and on the other, we are take their privacy away. On all accounts, we assume teens have no personal agency when it comes to their own online safety, and that they cannot effectively manage online risks by themselves. Meanwhile, developmental psychologists have shown that some level of autonomy and risk-seeking behaviors are a natural and necessary part of adolescent developmental growth. In fact, shielding teens from any and all online risks may actually be detrimental to this process. Therefore, my research takes a more teen-centric approach to understanding adolescent online risk experiences, how teens cope with these risks, and ultimately challenges the assumptions that have been made about how to protect teens online. Further, my research shows that parents are often not authoritative figures when it comes to the risks their teens are experiencing online; thus, an over-reliance on parental mediation to ensure teen online safety may be problematic. Thus, my research suggests new approaches that empower teens online by enhancing their risk-coping, resilience, and self-regulatory behaviors, so that they can learn to more effectively protect themselves from online risks.

    BioDr. Wisniewski is an Assistant Professor in the Department of Computer Science at the University of Central Florida. Previously, she was a Post-Doctoral Scholar at the Pennsylvania State University in the College of Information Sciences and Technology. She is a Human-Computer Interaction researcher whose work lies at the intersection of Social Computing and Privacy. She is particularly interested in the interplay between social media, privacy, and online safety for adolescents. She has authored over 50 peer-reviewed publications and has won multiple best papers (top 1%) and best paper honorable mentions (top 5%) at ACM SIGCHI conferences. She has been awarded over $1.96 million in external grant funding as a principal investigator or Co-PI, and her research has been featured by popular news media outlets, including ABC News, NPR, Psychology Today, and U.S. News and World Report. She is an inaugural member of the ACM Future Computing Academy and the first computer scientist to ever be selected as a William T. Grant Scholar.

    Please help forward this announcement to anyone who might be interested!