ML-based IPV Risk Factors among Homeless in the US (JIV'24)
Predicting Intimate Partner Violence Perpetration among Young Adults Experiencing Homelessness in Seven U.S. Cities Using Interpretable Machine Learning .
Bridging the gaps in multidisciplinary research
My research focuses on building robust, goal-centric intelligent systems that can learn and reason from complex, messy, real-world data on the Web. I am particularly interested in applying these systems to high-impact domains such as privacy, public health (including addictions, dietetics, and maternal health), and finance (with an emphasis on crowdfunding).
Within this broader scope, I also study how generative AI is actively shaping user behavior online. The rise of generative systems has introduced new privacy concerns, altered patterns of interactions both online and offline, and its impact on mental health. Understanding and integrating these behavioral, ethical, and psychological dimensions into metacognitive tasks is a central aspect of my work, ensuring that frameworks remain both effective and adaptable in dynamic environments. In the context of higher education, I study how generative AI is transforming learning, assessment, self-efficacy, and critical thinking. My goal is to help design AI-integrated educational frameworks that enhance learning outcomes while safeguarding student autonomy, psychological well-being, and ethical engagement. This includes developing interpretable AI systems that support metacognition rather than replace it.
Methodologically, my research tackles core challenges such as handling unstructured and messy data, and integrating diverse sources of information to uncover important insights, as well as design interpretable explanations. Ultimately, I aim to advance intelligent models that not only provide actionable insights, but also account for the broader societal implications of AI in particular, its impact on privacy, human behavior, mental health, and the future of higher education.
For full details of my research and publications, you can find them here. You can find my CV here. I received my Ph.D. in Computer Science from Arizona State University (ASU) under the supervision of Prof. Subbarao Kambhampati. Before ASU, I pursued M.S by thesis and B.Tech (Honours) in Computer Science and Engineering from IIIT-Hyderabad.
Latest News
| Our team received the Outstanding Performance Award at the ICIS 2025 Paper-a-thon. |
| Received the RPI Trustees' Celebration of Faculty Achievement Award 2025. |
| Deeply humbled and honored to share that I've received Dean R. Wellington '83 '84 Teaching Professorship in Management (Wellington Developmental Teaching Chair) at the Lally School of Management. |
| Truly honored to receive the best SPCs award at ICWSM-25. |
| Organizing a workshop on "Human-GenAI Interactions: Shaping the Future of Web Science" at WebScience 2025 conference. |
| Launched an AI/ML reading group at RPI. More details on the papers we read this year can be found on our reading group website. |
Recently Pulished Work
AI and the Future of Health (ACMS'24)
Keynote address on AI and the future of health in the context of faith.
COVID-19 and Diet Change (ICWSM'23)
Comfort Foods and Community Connectedness: Investigating Diet Change during COVID-19 using YouTube Videos on Twitter.
Privacy Paradox and AI Systems (AMCIS'22)
Investigating Privacy Paradox in the Context of Voice-based AI Systems.
User Disclosures and Addictions (ICWSM Data Challenge'22)
Linguistic Analysis of User Disclosures about Smoking Addiction during COVID-19 via Reddit.
Anti-Asian Hate and COVID-19 (WebScience'22)
Shift of User Attitudes about Anti-Asian Hate on Reddit Before and During COVID-19.
Reasoning behind Fake News Assessments (AIS THCI'22)
The Reasoning behind Fake News Assessments: A Linguistic Analysis.
Get In Touch
For students who are seeking recommendation letters, I would prefer email communication.