2024 Foley Scholar Award Winners - Research Presentations

April 17, 2025
12:00 p.m. Lunch; 12:30 p.m. talk starts
Location: TSRB 1st Floor Ballroom, 85 Fifth St NW, Atlanta, GA 30308

2024 Foley Scholar Award Winners (MS) Momin Siddiqui and (PhDs) Vanessa Oguamanam, Charles Ramey & Jiawei Zhou to present their research.
 

"Behavior and activity recognition systems for destructive users in harsh environments" - Charles Ramey

Abstract: The enhancement of animal well-being is a primary goal for animal caretakers. As an animal-centered computing practitioner, I aim to use digital technologies to extend the ability of caretakers to monitor the health of animals under their care and the effectiveness of the animals’ enrichment programs over time. Due to their users' unique behaviors and environments, however, these systems are subject to numerous design constraints. We must create each new system with a high level of physical ruggedness in mind to survive animal interactions while preserving the safety of our users. In this talk, I will present an ongoing project that utilizes two custom-designed instrumented enrichment objects to quantify animal interactions with the devices. I will address some of the key design constraints involved when creating the devices and present the results of a pilot study that compared the intensity and duration of animal-user interactions with the devices.

Short bio: Charles Ramey is a 5th year Computer Science Ph.D. Student advised by Professors Melody Jackson and Thad Starner. By utilizing his interdisciplinary skillset, Charles creates interactive computing systems for studying animal behavior, activities, and communications. During his nearly 14 years at Georgia Tech, Charles has been highly involved with makerspaces across campus, researched in three different labs (Precision Biosystems Lab, Planetary Habitability Lab, and Contextual Computing Group), and has spent over two years worth of time participating in field research.

"Contextualizing Writing Education for LLM Instigated Paradigm Shift" - Momin Siddiqui

Abstract: The ubiquity in generative AI through technologies like ChatGPT has led to growing concern among school personnel and parents. Students use these tools to do their homework for them, thereby circumventing crucial learning steps. Through this talk, I want to share how instead of rejected generative technologies in classroom, their thoughtful integration through tools like Script&Shift can support students to produce better writing while engaging in reflective processes.

Short bio: Momin Siddiqui is an MS CS student at Georgia Tech. His research is at the intersection of learning engineering and human-ai interaction. His paper was recently recognized as an honorable mention at CHI and he also has publications at learning science venues like AIED and Learning at Scale.

"Generative AI in Our Information Ecosystem: Assessing and Communicating the Risks" - Jiawei Zhou

Abstract: While technology has democratized information access, it also presents unique challenges for individuals in assessing information quality and reliability. These challenges have become more pronounced with the emergence of generative artificial intelligence (AI) technologies like large language models (LLMs), which can generate low-quality information — such as inaccurate or biased information — with high scalability and persuasiveness. Rather than approaching harm in a vacuum by measuring text alone, my research adopts a human-centered approach to understanding and contextualizing the perceived harms of using AI to meet informational needs. In this talk, I will first discuss what risks AI-generated information can bring, by presenting empirical evidence on its differences and challenges compared to human writing, as well as a risk taxonomy consolidated from professional and public voices. I will then share ongoing and future efforts to investigate how such risks are currently communicated, by characterizing the public discourse and investigating the effects of risk communication on public trust.

Short bio: Jiawei Zhou is a PhD student in Human-Centered Computing at Georgia Tech, advised by Munmun De Choudhury. Her research lies in Human-AI Interaction, Social Computing, and Health & Wellbeing, with an emphasis on the impacts of AI in the information ecosystem and high-stakes health domain. Her research has been published at premier computing venues like CHI, CSCW, UbiComp, and ACL, and has been recognized by a Best Paper Honorable Mention at CHI and the Foley Scholar Award. She works closely with experts in public health and informatics, mass communication, natural language processing, and psychology. Her research has made practical and policy implications through invited talks and workshops at the UK Government Department for Science, Innovation and Technology (DSIT), CSIRO Australian National Science Agency, Amazon, Mayo Clinic, and UT Southwestern Medical Center.

"Maternal Ease: A Tailored Approach to Supporting Perinatal Mental Health Through Digital Innovation" - Vanessa Oguamanam

Abstract: Perinatal mental health is a growing concern in the U.S., particularly for Black women who face higher rates of perinatal mood and anxiety disorders (PMADs) and chronic stress. Despite this reality, Black women reportedly use formal mental health support tools less frequently than their White counterparts due to barriers such as cost, access, and a lack of culturally competent resources. Digital platforms offer a promising solution to address these barriers. While the use of digital platforms for supporting perinatal mental health has been explored in HCI and CSCW, most evaluations focus on White and Asian women. My work addresses this gap by examining perinatal Black women’s use of, perspectives on, and engagement with digital platforms for managing stress and well-being. In this talk, I present empirical studies exploring how socio-cultural factors shape their preferences for digital mental health platforms. I will also discuss future directions for integrating a culturally tailored framework into digital mental health interventions aiming to improve engagement within this population.

Short bio: Vanessa Oguamanam is currently a Ph.D. candidate in Computer Science working in the Wellness Technology Lab under the supervision of Dr. Andrea Parker. She holds a M.S. in Human-Computer Interaction (HCI) and a B.S. in Computer Science from the University of Maryland, College Park. Vanessa’s research sits at the intersection of human-centered AI, digital health equity, and maternal mental health. Specifically, her dissertation focuses on the design, development, and evaluation of an AI-powered digital health tool tailored to support stress management in perinatal Black women. Her research trajectory has been shaped by her prior experiences conducting digital health research at the University of Maryland’s HCI Lab, Microsoft Research, and Google.

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IPaT: GVU Lunch Lecture Series