Nitin Verma

Associate Editor, ACM Journal on Responsible Computing

Trust, belief-formation, and the science of science.

• Honorable mention for the ALISE Eugene Garfield Doctoral Dissertation Competition 2024, for my dissertation Deepfake Technology and the Future of Public Trust in Video
• iSchools, Inc. Research Grant, December 2021
• iConference 2021 Best Short Research Paper Award

Nitin Verma is a teaching assistant professor in the School of Information Sciences at the University of Illinois Urbana-Champaign. Prior to joining the iSchool, he served as a postdoctoral research associate in the area of AI and society at Arizona State University's School for the Future of Innovation in Society (SFIS) and the New York Academy of Sciences. He obtained his PhD in information science from the School of Information at UT-Austin in 2023 where his research was focused on studying trust, misinformation, AI ethics, and human values. Prior to that, he earned an MS in Information Studies at the UT-Austin iSchool in 2017. He has taught undergraduates and graduates at both UT-Austin and ASU. He also has nearly a decade of industry experience as a software engineer and programmer. 

Shiroma, K., Zimmerman, T., Xie, B., Fleischmann, K.R., Rich, K., Lee, M.K., Verma, N., & Jia, C. (2023). Older adults' trust and distrust in COVID-19 public health information: A qualitative critical incident study. JMIR Aging. [DOI]

Verma, N., Fleischmann, K., & Koltai, K. (2023). Designing adaptive, mixed-mode HCI research for resilience. Interacting with Computers. [DOI]

Zimmerman, T., Shiroma, K., Fleischmann, K. R., Xie, B., Jia, C., Verma, N., & Lee, M. K. (2023). Misinformation and COVID-19 Vaccine Hesitancy. Vaccine. [DOI]

Verma, N., Fleischmann, K. R., Zhou, L., Xie, B., Lee, M. K., Rich, K., Shiroma, K., Jia, C., & Zimmerman, T. (2022). Trust in COVID-19 public health information. Journal of the Association for Information Science and Technology (JASIST). [DOI]

Slota, S. C., Fleischmann, K. R., Greenberg, S. R., Verma, N., Cummings, B., Li, L., & Shenefiel, C. (2022). Locating the work of AI ethics. Journal of the Association for Information Science and Technology (JASIST). [DOI]

Slota, S. C., Fleischmann, K. R., Greenberg, S. R., Verma, N., Cummings, B., Li, L., & Shenefiel, C. (2021). Many hands make many fingers to point: Challenges in creating accountable AI. AI & Society. [DOI]

Verma, N., Landrum, A. R. (2025). AI in Peer-Review: The Future of Human-Machine Communication in Scientific Knowledge Production. The 75th Annual Conference of the International Communication Association, Denver, CO. June, 2025

Verma, N. (2025). Deepfake technology and public trust in video. In A. R. Landrum (Organizer) & K. Roschke (Moderator), Trusting AI solutions for pressing societal challenges [Conference session]. Annual Meeting of the American Association for the Advancement of Science (AAAS), Boston, MA.

Landrum, A. R., Verma, N., & Kehrberg, A. (2025). Trusting health advice from ChatGPT. In A. R. Landrum (Organizer) & K. Roschke (Moderator), Trusting AI solutions for pressing societal challenges [Conference session]. Annual Meeting of the American Association for the Advancement of Science (AAAS), Boston, MA.

Verma, N. (2024). “One video could start a war”: A qualitative interview study of public perceptions of deepfake technology. Proceedings of the Association for Information Science and Technology (ASIS&T). [DOI]

Hatfield, K., Ezenyilimba, A., Verma, N., Mesa, J. J., Moon, S.E., Tibbetts, E., Turaga, P., Pavlic, T.P. (2024). Fine-tuned thin-plate spline motion model for manipulating social information in paper-wasp colonies. IEEE/CVF Workshop on CV4Animals (in conjunction with IEEE CVPR).

Stangl, A., Verma, N., Fleischmann, K. R., Morris, M. R., & Gurari, D. (2021). Going beyond one-size-fits-all image descriptions to satisfy the information wants of people who are blind or have low vision. Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ’21). [DOI]

Verma, N., Shiroma K., Rich K., Fleischmann K. R., Xie B., & Lee M. K. (2021). Conducting quantitative research with hard-to-reach-online populations: Using prime panels to rapidly survey older adults during a pandemic. iConference 2021. [DOI]

Slota, S. C., Fleischmann, K. R., Greenberg, S., Verma, N.,Cummings, B., Li, L., & Shenefiel, C. (2021). Something new versus tried and true: Ensuring ‘innovative’ AI is ‘good’ AI. iConference 2021. [DOI]

Slota, S. C., Fleischmann, K. R., Greenberg, S., Verma, N., Cummings, B., Li, L., & Shenefiel, C. (2020). Good systems, bad data? Interpretations of AI hype and failures. Proceedings of the Association for Information Science and Technology (ASIS&T). [DOI]

Verma, N., Fleischmann, K. R., & Koltai, K. S. (2019). Understanding online trust and information behavior using demographics and human values. iConference 2019. [DOI]