Difference between revisions of "Brown Bag Lunch Schedule"

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<b>Dancing Pigs or Security? Measuring the Rationality of End-User Security Behavior</b>
 
<b>Dancing Pigs or Security? Measuring the Rationality of End-User Security Behavior</b>

Revision as of 21:59, 6 February 2018

The HCIL has an open, semi-organized weekly "brown bag lunch (BBL)" every Thursday from 12:30-1:30pm in HCIL (2105 Hornbake, South Wing). The topics range from someone's work, current interests in the HCIL, software demos/reviews, study design, proposed research topics, introductions to new people, etc. The BBL is the one hour a week where we all come together--thus, it’s a unique time for HCIL members with unique opportunities to help build collaborations, increase awareness of each other’s activities, and generally just have a bit of fun together. There is no RSVP; simply show up!

If you would like to give or suggest a talk, presentation, workshop, etc., send an email to BBL student co-coordinators Sriram Karthik Badam (sbadam@umd.edu) or Pavithra Ramasamy (pavithra.ramasamy94@gmail.com). In the email, briefly describe the topic and preferred dates.

To be notified about upcoming events, please subscribe one of these mailing lists.




Spring 2018 Schedule

Date Leader Topic
01/25/2018

Kickoff to a new Semester!

Come, network, make introductions, and share what you are working on

Please come to our first BBL of the Spring 2018 semester to introduce yourself and share what you're working on in the coming semester. The first BBL will be for us to network with each other and kickoff a great new semester.

02/01/2018

Bahador Saket
Georgia Tech, Atlanta

Visualization by Demonstration

Abstract: A commonly used interaction paradigm in most visualization tools is manual view specification. Tools implementing manual view specification often require users to manually specify visual properties through GUI operations on collections of visual properties and data attributes that are presented visually on control panels. To interact with tools implementing manual view specification users need to understand the potentially complex system parameters being controlled. Additionally, in such tools, users need to constantly shift their attention from the visual features of interest when interacting.

In this talk, I present an alternative interaction paradigm for visualization construction and data exploration called visualization by demonstration. This paradigm advocates for a different process of visualization construction. I will also discuss the trade-offs between these interaction paradigms based on the data collected from an empirical study. I will then discuss applications of the "by demonstration’" paradigm in other areas in data visualization.

Bio: Bahador Saket is a third-year Ph.D. student at Georgia Tech, where he works with Dr. Alex Endert. His current research focuses on the design of interaction techniques for visualization construction and visual data exploration. Prior to joining Georgia Tech, Bahador worked at different research labs including Microsoft Research, CNS Research Center, and NUS-HCI Lab. He has published over 12 peer-reviewed articles in the leading journals and conferences in the field of human-computer interaction and data visualization such as IEEE Transactions on Visualization and Computer Graphics (TVCG), Computer Graphics Forum, CSCW, UIST, and MobileHCI.

02/08/2018

Elissa Redmiles
University of Maryland, College Park

Dancing Pigs or Security? Measuring the Rationality of End-User Security Behavior

Abstract: Accurately modeling human decision-making in security is critical to think about when, why, and how to recommend that users adopt certain secure behaviors. We used behavioral economics experiments to model the rationality of end-user security decision-making in a realistic online experimental system simulating a bank account. We ask participants to make a financially impactful security choice, in the face of transparent risks of account compromise and benefits offered by an optional security behavior (two-factor authentication). We find that more than 50% of our participants made rational (e.g., utility optimal) decisions, and we find that participants are more likely to behave rationally in the face of higher risk. Additionally, we confirm that users are boundedly rational: they make decisions based on some risks and context, but not others, and we can model their behavior well as a function of these factors. Finally, we show that a “one-size-fits-all” emphasis on security can lead to market losses, but that adoption by a subset of users with higher risks or lower costs can lead to market gains.
Bio: Elissa Redmiles is a Ph.D. student at the University of Maryland in Computer Science. Her research focuses on using computational and social science methodologies to understand and improve users' privacy and security learning processes, behavior, and perceptions. She is the recipient of an NSF Graduate Research Fellowship, a National Science Defense and Engineering Graduate Fellowship, and a Facebook Fellowship. Prior to pursuing her Ph.D., Elissa held Marketing Management and Software Engineering roles at IBM and was a Data Science for Social Good Fellow at the University of Chicago.


02/15/2018

Erin Peters-Burton
George Mason University, Fairfax, VA

TBD

TBD


02/22/2018

Norman Su
Indiana University

TBD

TBD

03/01/2018

Ya-Wei Li
Center for Conservation Innovation, Defenders of Wildlife

TBD

TBD

03/08/2018

Deok Gun Park
University of Maryland, College Park

TBD

TBD

03/15/2018

TBA

TBD

TBD

03/22/2017 No Brown Bag, Spring Break.
03/29/2018

Eun-Kyoung Choe
University of Maryland, College Park

TBD

TBD


04/05/2018

TBA

TBD

TBD

04/12/2018

CHI practice talks

TBD

TBD

04/19/2018

TBA

TBD

TBD


04/26/2018

Hernisa Kacorri
University of Maryland, College Park

TBD

TBD


05/03/2018

Amanda Lazar
University of Maryland, College Park

TBD

TBD


05/10/2018

Joel Chan
University of Maryland, College Park

TBD

TBD


05/17/2018

TBA

TBD

TBD

Past Brown Bags

View the Past Brown Bag Lunch Schedules to learn more about prior talks.