Research & Projects

Generative AI systems such as ChatGPT and Midjourney have been increasingly used to produce music, text, art, and videos that approach the quality people can create. While these AI systems can be used to enhance people's own creative work, a widely voiced concern is how generative AI might replace human creative workforces and lead to significant ethical, legal, and social risks. 

In this work, I focus on independent, or indie, game developers. This community faces unique challenges due to the small-scale and solo nature of their development practices. With this work, I aim to get a deeper picture of both opportunities and challenges generative AI brings to indie game developers and other creative workforces. Through both quantitative (quantitaive social media analysis) and qualitative research (qualitative social media analysis, user interviews), I explore how generative AI can be designed to support creators rather than marginalizing them or harming their creative practices and careers.

Publications

Ruchi Panchanadikar, Guo Freeman (2024). “I’m a Solo Developer but AI is My New Ill‑Informed Co‑Worker”: Envisioning and Designing Generative AI to Support Indie Game Development. In ACM SIGCHI Conference on Computer‑Human Interaction in Play (CHI PLAY 2024 ), Oct 14‑17 2024, Tampere, Finland [Best Paper Honorable Mention Award: Top 5%] [PDF]

Ruchi Panchanadikar, Guo Freeman, Kelsea Schulenberg, Lingyuan Li, & Yang Hu (2024). ”A New Golden Era” or ”Slap Comps”: How Non‑Profit Driven Indie Game Developers Perceive the Emerging Role of Generative AI in Game Development. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’24), May 11–16, 2024, Honolulu, HI, USA. (Acceptance rate: 33.88%) [PDF]

| Poster CHI 2024 | Presentation CHI PLAY 2024 |

Social Virtual Reality (VR) platforms (e.g., VRChat, Meta’s Horizon Worlds, and RecRoom) are spaces where multiple users can interact with one another typically through VR head-mounted displays and immersive 360-degree virtual content in 3D virtual spaces. There has been a steady growth of streamed VR content on popular streaming platforms like YouTube and Twitch.

In this project, with comprehensive user interviews with 17 social VR streamers, we explore their unique strategies to engage with their audiences and their perceived potential limitations of these strategies.

Publications

Yang Hu*, Ruchi Panchanadikar*, Guo Freeman (2025). Beyond Traditional Gaming: Understanding How Social VR Streaming Creates New Forms of Play. In Companion Proceedings of the Annual Symposium on Computer-Human Interaction in Play (CHI Play Companion 2025) [PDF]

Yang Hu, Guo Freeman & Ruchi Panchanadikar (2025). "Grab the Chat and Stick It to My Wall": Understanding How Social VR Streamers Bridge Immersive VR Experiences with Streaming Audiences Outside VR. In The 2025 ACM Conference on Human Factors in Computing Systems (CHI'25) [PDF].

Guo Freeman, Yang Hu, Ruchi Panchanadikar, Amelia L Hall, Kelsea Schulenberg, & Lingyuan Li (2024). "My Audience Gets to Know Me on a More Realistic Level": Exploring Social VR Streamers’ Unique Strategies to Engage with Their Audiences. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’24), May 11–16, 2024, Honolulu, HI, USA. (Acceptance rate: 33.88%) [PDF]

| Poster CHI 2024 | Poster CHI Play 2025 |

Large Language Models (LLMs) have rapidly become a significant part of various everyday applications, from customer support to content generation. However, their widespread use has highlighted issues of bias and fairness, particularly in sensitive tasks like resume evaluation. In this project, we investigate these concerns by focusing on nationality bias in LLMs, specifically examining how GPT-2 may exhibit such biases.

Publications

Venkit, P., Gautam, S., Panchanadikar, R., Huang, K., Wilson, S. (2023). Unmasking Nationality Bias: A Study of Human Perception of Nationalities in AI‑Generated Articles. AAAI/ACM Conference on AI, Ethics, and Society‑ AIES ’23 [PDF]

Venkit, P., Gautam, S., Panchanadikar, R., Huang, K., Wilson, S. (2023).Nationality Bias in Text Generation. Conference of the European Chapter of the Association for Computational Linguistics‑ EACL ’23 [PDF]

The Creativity Assessment Platform (CAP) is a free, web-based tool for designing, administering, and scoring creativity assessments (cap.ist.psu.edu). With multilingual support, machine learning–based scoring, and an easy point-and-click interface, CAP makes creativity measurement accessible to educators, researchers, and beyond. The design and development of the initial design and development of the website was a part of my Master's scholarly paper.

Publications

John D Patterson, Jimmy Pronchick, Ruchi Panchanadikar, Mark Fuge, Janet G van Hell, Scarlett R Miller, Dan R Johnson, Roger E Beaty (2025). CAP: The creativity assessment platform for online testing and automated scoring. Behavior Research Methods, 57(9), 264 [PDF].