Vivek K.
Singh
Associate Professor of Library and Information Science
- Office:
- RH 203
- PHONE:
- 848-932-7588
- FAX:
- 732-932-6916
- EMAIL:
- vivek.k.singh@rutgers.edu
- OFFICE HOURS:
- WEB LINKS:
- Google Scholar ResearchGate Personal Website
Vivek Singh is an Associate Professor in the School of Communication and Information and the Director of the Behavioral Informatics Lab at Rutgers University. His research lies at the intersection of Computational Social Science, Data Science, and Multimedia Information Systems. Before joining Rutgers, he was a post-doctoral researcher at the MIT Media Lab. He holds a Ph.D. in Computer Science from the University of California, Irvine. His work has appeared in leading disciplinary and interdisciplinary publication venues (e.g. Science, ACM CHI, JASIST) and has been covered by popular media (e.g. New York Times, BBC, Wall Street Journal). Singh's research is supported by the US National Science Foundation, National Institutes of Health, Department of Homeland Security, Google, and OpenAI.
Education
University of California, Irvine
Ph.D., Computer Science
National University of Singapore
Master of Computing, Computer Science
National University of Singapore
Bachelor of Engineering, Computer Engineering
Research
Vivek K. Singh directs the Behavioral Informatics Lab at Rutgers University. This lab works at the intersection of human behavior and information technology. The lab develops new algorithms, interfaces, and frameworks that aim to maximize the good of technology (e.g., predicting mental health issues) while minimizing the potential harms (e.g., privacy loss).
Two major themes of research are:
- AI for health and wellness: Developing theory-aware algorithms that use multimodal data (e.g., phone logs, social media) to model mental health, wellbeing, trust, etc. Projects: Rutgers Well-being Study (2015-2020); Rutgers Wellness Study (2021-ongoing).
- Reducing harm in digital environments: Developing algorithms, interfaces, and frameworks that reduce harm in digital environments (e.g., cyberbullying, privacy loss, misinformation, algorithmic bias).
Research Groups
- Behavioral Informatics Lab
- Computational Social Science Lab
- HCI Lab for Health and Sustainability
- Health Humanities, Communications, and Informatics
- Social Media & Society Cluster
Funded Projects
Department of Homeland Security (sub-award via Arizona State University): Streamlining Document Validation using Artificial Intelligence, Role: PI, Co-PI: Fred Roberts, 2024-2026.
National Institutes of Health (sub-award from Harvard University): NIH AIM-AHEAD Fellowship program mentor. Role: Single PI. 2024-2025.
OpenAI Researcher Access Program: Fairness Across Languages in OpenAI responses. Role: PI. Co-PI: Jaideep Vaidya. 2025.
National Science Foundation, RAPID: Countering Language Biases in COVID-19 Search Auto-Completes, Role: PI, Co-PI: Pamela Valera, 2020-2023
National Science Foundation, EAGER: SaTC: Early-Stage Interdisciplinary Collaboration: Fair and Accurate Information Quality Assessment Algorithm, Role: PI, Co-PI: Lauren Feldman, 2019-2023.
Selected Publications
De Montjoye, Y.-A., L. Radaelli, V. K. Singh, and A. Pentland. “Unique in the Shopping Mall: On the Reidentifiability of Credit Card Metadata.” Science 347, no. 6221 (January 29, 2015): 536–539.
Singh, V., Chayko, M., Inamjar, R., and Floegel, D. 2020. “Female Librarians and Male Computer Programmers? Gender Bias in Occupational Images on Digital Media Platforms.” 2020. Journal of the Association for Information Science and Technology, 71(11), 1281-1294.
Singh, V. K., Ghosh, I., & Sonagara, D. (2021). Detecting fake news stories via multimodal analysis. Journal of the Association for Information Science and Technology, 72(1), 3-17.
Almuzaini, A. A., Bhatt, C. A., Pennock, D. M., & Singh, V. K. (2022). ABCinML: Anticipatory bias correction in machine learning applications. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (pp. 1552-1560).
Almuzaini, A. A., Pennock, D. M., & Singh, V. K. (2024). Accuracy and fairness for web-based content analysis under temporal shifts and delayed labeling. In Proceedings of the 16th ACM Web Science Conference (pp. 268-278).
Awards & Recognitions
ASIS&T SIG-Social Media Senior Researcher Award, 2024. This award recognizes sustained and ongoing contributions of one senior researcher to the field of social media within information science.
Best Paper Award from the ACM Web Science Conference, 2024 for the paper “Accuracy and Fairness for Web-Based Content Analysis under Temporal Shifts and Delayed Labeling”. Awarded to one paper by the conference.
The iSchools Doctoral Dissertation Award (Runner Up) won by advisee, 2024 for dissertation titled “Design Intervention to Reduce Online Incivility”. Winner: Jinkyung Katie Park, Dissertation advisor: Vivek Singh. This award recognizes the best doctoral dissertations in the field of information science during 2022-2023.
Best Paper Award from IEEE Intelligent Systems, 2022 for the paper "Intelligent Pandemic Surveillance via Privacy-Preserving Crowdsensing". Awarded to one paper in a year by the journal.
ASIS&T SIG-Social Media Best Paper Award, 2022 for the article “’Not all my friends are friends’: Audience‐group‐based nudges for managing location privacy” published in JASIST. Award given to the best social media-related paper in information science in the 2021-2022 period.
Top cited article award for 2020-2021 (and again for 2021-2022), Journal of the Association for Information Science & Technology (JASIST), for article “Detecting fake news stories via multimodal analysis”. This award recognizes the papers from the journal with most citations in the preceding year.