Pooriya Jamie

Hello, I’m Pooriya Jamie, a first-year PhD student in Communication (Research Methodology and Quantitative Methods) at the University of California, Los Angeles (UCLA) and a member of the OASIS Lab. I’m advised by Homa Hosseinmardi and co-advised by Amir Ghasemian. My research examines how algorithmic curation shapes social media experiences and influences user well-being, at the intersection of human-computer interaction, data science, and socio-technical systems.

Previously, I explored AI’s transformative potential in education, including developing AI-assisted tools to analyze student learning behaviors, studying the effects of large language models on problem-solving, and designing adaptive systems for personalized learning. These experiences shaped my broader interest in leveraging computational and human-centered methods to understand and improve experiences in digital environments.

I am particularly interested in projects at the intersection of AI, communication, and human-centered technology, and I welcome collaborations that investigate the social and behavioral impacts of digital systems.

news

Apr 15, 2026	I am honored to share that I received the UCLA Graduate Summer Research Mentorship Program award.
Apr 14, 2026	I am pleased to share that my submission, “Seeking Help, Facing Harm: Auditing TikTok’s Mental Health Recommendations”, has been accepted as a parallel talk at IC2S2 2026.
Mar 24, 2026	My first PhD paper, “Seeking Help, Facing Harm: Auditing TikTok’s Mental Health Recommendations,” has been accepted to the International AAAI Conference on Web and Social Media (ICWSM) 2026.
Feb 01, 2026	I will be serving as a reviewer for CHI 2026, DIS 2026, IUI 2026, ICWSM 2026, and EICS 2026.
Sep 23, 2025	Thrilled to announce that I’ve started my PhD journey at UCLA in the Department of Communication!

selected publications

Utilizing ChatGPT in a Data Structures and Algorithms Course: A Teaching Assistant’s Perspective

Pooriya Jamie, Reyhaneh HajiHashemi , and Sharareh Alipour

In Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems , 2025

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Integrating large language models (LLMs) like ChatGPT into computer science education offers transformative potential for complex courses such as data structures and algorithms (DSA). This study examines ChatGPT as a supplementary tool for teaching assistants (TAs), guided by structured prompts and human oversight, to enhance instruction and student outcomes. A controlled experiment compared traditional TA-led instruction with a hybrid approach where TAs used ChatGPT-4o and ChatGPT o1 to generate exercises, clarify concepts, and provide feedback. Structured prompts emphasized problem decomposition, real-world context, and code examples, enabling tailored support while mitigating over-reliance on AI. Results demonstrated the hybrid approach’s efficacy, with students in the ChatGPT-assisted group scoring 16.50 points higher on average and excelling in advanced topics. However, ChatGPT’s limitations necessitated TA verification. This framework highlights the dual role of LLMs: augmenting TA efficiency while ensuring accuracy through human oversight, offering a scalable solution for human-AI collaboration in education.
Seeking Help, Facing Harm: Auditing TikTok’s Mental Health Recommendations

Pooriya Jamie, Amir Ghasemian , and Homa Hosseinmardi

2026

Accepted at ICWSM 2026

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