Ramaravind K M



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About

Hello! I’m a Ph.D. student in the Faculty of Information, a graduate fellow of the Data Sciences Institute (DSI), and a graduate affiliate of the Schwartz Reisman Institute for Technology and Society (SRI) at the University of Toronto. I'm co-advised by Ishtiaque Ahmed and Shion Guha. I am also a member of the Department of Computer Science's Third Space research group, Dynamics Graphics Project lab, and iSchool's Human-Centred Data Science Lab.

Before starting my Ph.D., I worked as a Data Scientist at Everwell Health Solutions and a pre-doctoral AI Center Fellow at Microsoft Research India. I completed my M.Sc. in Artificial Intelligence from KU Leuven, Belgium, and my undergraduate in Instrumentation and Control Engineering from NIT Trichy, India.


Interests

I'm broadly interested in fairness questions about ML development and deployment in societally critical spaces. My current research centers on questions at the intersection of fairness, justice, and ML-based content moderation systems.

I'm particularly interested in (a) understanding various tensions, expectations, and subtle technical assumptions that go into developing ML-based information systems and (b) developing tools to support ML practitioners and other stakeholders in their fairness-related works in practice. My research is interdisciplinary and spans topics in FAccT, Machine Learning, and HCI.

In the years before starting my Ph.D., I have built dashboards for state organizations, developed optimal incentive schemes for spreading public awareness messages, created open-source software to explain ML models, and analyzed caste hierarchy and information flow within the online social networks of Indian politicians. Check out my publications for more information, and email me to collaborate!


Publications

  1. Arya, A., De, S., Mishra, D., Shekhawat, G., Sharma, A., Panda, A., Lalani, F., Singh, P., Kommiya Mothilal, R., Grover, R., Nishal, S., Dash, S., Shora, S., Akbar., S & Pal, J. (2022, May). DISMISS: Database of Indian Social Media Influencers on Twitter. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 16, pp. 1201-1207).
  2. Kommiya Mothilal, R., Mishra, D., Nishal, S., Lalani, F. M., & Pal, J. (2022). Voting with the Stars: Analyzing Partisan Engagement between Celebrities and Politicians in India. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW1), 1–29.
  3. Vaghela, P., Mothilal, R. K., Romero, D., & Pal, J. (2022). Caste Capital on Twitter: A Formal Network Analysis of Caste Relations among Indian Politicians. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW1), 1–29.
  4. Akbar, S. Z., Sharma, A., Mishra, D., Mothilal, R. K., Negi, H., Nishal, S., Panda, A., Pal, J. (2022). Devotees on an Astroturf: Media, Politics, and Outrage in the Suicide of a Popular FilmStar. ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies (COMPASS), 453–475.
  5. Kommiya Mothilal, R., Mahajan, D., Tan, C., & Sharma, A. (2021). Towards unifying feature attribution and counterfactual explanations: Different means to the same end. Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 652–663.
  6. Vaghela, P., K Mothilal, R., & Pal, J. (2021). Birds of a Caste-How Caste Hierarchies Manifest in Retweet Behavior of Indian Politicians. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW3), 1–24.
  7. Mothilal, Ramaravind K., Sharma, A., & Tan, C. (2020). Explaining machine learning classifiers through diverse counterfactual explanations. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 607–617.
  8. Mehta, D., Sharma, A., Kommiya Mothilal, R., Shukla, A., Prasad, V., Thies, W., Venkanna, U., Scott, C., Sharma, A. (2020). Facilitating Media Distribution with Monetary Incentives. Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 1–7.
  9. Panda, A., Kommiya Mothilal, R., Choudhury, M., Bali, K., & Pal, J. (2020). Topical Focus of Political Campaigns and its Impact: Findings from Politicians’ Hashtag Use during the 2019 Indian Elections. Proceedings of the ACM on Human-Computer Interaction, 4(CSCW1), 1–14.
  10. Mehta, D., Mothilal, R. K., Sharma, A., Thies, W., & Sharma, A. (2020). Using Mobile Airtime Credits to Incentivize Learning, Sharing and Survey Response: Experiences from the Field. Proceedings of the 3rd ACM SIGCAS Conference on Computing and Sustainable Societies, 254–264.
  11. Lalani, F. M., Kommiya Mothilal, R., & Pal, J. (2019). The Appeal of Influencers to the Social Media Outreach of Indian Politicians. Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing, 267–271.
  12. Kommiya Mothilal, R., Mehta, D., Sharma, A., Thies, W., & Sharma, A. (2019). Learnings from an Ongoing Deployment of an IVR-based Platform for Voter Awareness. Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing, 257–261.
  13. Mothilal, Ramaravind Kommiya, Yadav, A., & Sharma, A. (2019). Optimizing peer referrals for public awareness using contextual bandits. Proceedings of the 2nd ACM SIGCAS Conference on Computing and Sustainable Societies, 74–85.
  14. De Laet, T., Mothilal, R. K., Broos, T., & Pinxten, M. (2018). Predicting first-year engineering student success: from traditional statistics to machine learning. Proceedings of the 46th SEFI Annual Conference 2018, 46, 322–329. SEFI-Société Européenne pour la Formation des Ingénieurs.
  15. Mothilal, K. R. (2018). Statistical modeling of students’ performance in an open-admission bachelor program in Flanders. Leuven: KU Leuven. Faculteit Ingenieurswetenschappen.
  16. Ramaravind, K. M., Shravan, T. R., & Omkar, S. N. (2016). Scale adaptive object tracker with occlusion handling. International Journal of Image, Graphics and Signal Processing, 8(1), 27.
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