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Events for May 04, 2022
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PhD Defense - Sarah Cooney
Wed, May 04, 2022 @ 02:00 PM - 04:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Candidate: Sarah Cooney
Title: Toward Sustainable and Resilient Communities with HCI: Physical Structures and Socio-Cultural Factors
Committee:
Barath Raghavan (Chair), Ramesh Govindan, Bistra Dilkina, Heather Culbertson, Hajar Yazdiha (Outside Member, Sociology)
Abstract: Today more than ever we are faced with urgent, global-scale sustainability challenges. Scientists are urging everyone to contribute, and this includes the computing community. The Sustainable Human-Computer Interaction (SHCI) community has been working on these kinds of sustainability problems for almost two decades now. My research builds on the work of this community, in particular the use of Practice Theory to examine the external structures that act on individuals, often hampering their ability to make sustainable decisions. Using both qualitative and quantitative methods from human-computer interaction, my research aim is to find local solutions to global sustainability challenges while increasing community resilience and individual well-being.
First, I look at physical infrastructure through the lens of ``social infrastructure''. I build a prototype software, PatternPainter, to enable ordinary individuals to create 3D visualizations for designs of new social spaces on abandoned land in their communities. Evaluation shows this prototype allows individuals without design training to successfully create designs in 3D. I then turn to qualitative methods from HCI, specifically photo elicitation and surveys, to add context by examining how trained designers and untrained citizens view their physical environments differently in the CommYOUnity Data Study. The observations from this study can be used to inform building future technologies in the social infrastructure space. Finally, I turn to automation. I create a pipeline using the Pix2Pix style transfer algorithm and semantic segmentation to automate the process of revitalizing city streets for pedestrian use.
In parallel, I also examine religion as a socio-cultural factor impacting sustainable decision making. This builds on previous work in SHCI, which suggests that it is important to understand the social, cultural, and psychological motivations behind sustainable decision making, so that more effective technological solutions to facilitate these decisions can be built. To that end, I conducted an interview study with 14 individuals from Catholic organizations who are involved in sustainability work from a faith-based lens. I show how the insights from this study might be used to build future technology in this space.
WebCast Link: https://usc.zoom.us/j/97131163793?pwd=MXZ0NUNyd1BWK2F4U0lmUWJtNEVLdz09
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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PhD Defense - Victor Ardulov
Wed, May 04, 2022 @ 03:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Modeling and Regulating Human Interaction with Control Affine Dynamical Systems
Author: Victor Ardulov
Committee Members: Shrikanth Narayanan (chair), Maja MatariÄ, Thomas D Lyon
Date: May 5, 2022 3pm Pacific
Location (in-person): Ronald Tutor Hall 320
Virtual Link:
usc.zoom.us/j/98133481247?pwd=d2VqbmNhYWljcnp4d25PVEJvd3U5Zz09
Meeting ID: 981 3348 1247
Passcode: 882255
Abstract:
Human interaction is a vital component to a persons' development and well-being. These interactions enable us to over come obstacles and find resolutions that an individual might not be able to. This subject is particularly well studied in the domains of human psychology, where human behavior is diagnostically categorized and the interaction can be utilized in order to improve somebody's health.
Prior work has explored the use of computational models of human behavior to aide in the diagnostic assessment of behavioral patterns. Most recently, novel machine learning
methods and access data has invited the to study the dynamics of human interaction on a more granular time-resolution. These dynamics have been used to identify specific moments during interactions that are relevant to the over all assessment of a individuals behavior with respect to their interlocutor. By reformulating this system from the perspective of an operator that can be controlled, it invites the possibility to predict how an individual would react to a specific input from their partner, which itself lends the opportunity to plan out interventions and probes more effectively.
This dissertation presents a formulation of human interaction through a systems theoretic paradigm with a control affine element and demonstrates how these frameworks can be utilized to gain insight into improving desired outcomes and approaches towards optimizing interaction strategies. In support of the thesis, we will present the application of these techniques to the domains of forensic interviewing, psychotherapy, and neurodevelopmental diagnostics.
Bio:
Victor is a 5th year Computer Science PhD Candidate with SAIL at the University of Southern California, where his primary research is conducted in the space of modeling and guiding behavioral interactions between people. His work includes analyzing child speaking patterns to determine the truthfulness of their statements during high-stakes interviews, improving screening tools for diagnosing neuro-developmental disorders (e.g. Autism Spectrum Disorder), and building models to improve psychologists-client outcomes during therapy. Besides his work at USC, Victor has experience as a scientific advisor at Calypso AI distilling research to build AI testing software, a research engineer at Hughes Research, working on Human-AI collaborative teams, at NASA's Jet Propulsion Laboratory, working on VR tools for science and planning, and received his Bachelor's in Computer/Robotics Engineering at UC Santa Cruz, where he designed and developed assistive exoskeleton to help stroke patients.Location: 320
WebCast Link: usc.zoom.us/j/98133481247?pwd=d2VqbmNhYWljcnp4d25PVEJvd3U5Zz09
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
