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Pooja Sarin
Assistant Professor (Data Science) School of Computer Science, UPES
Profile Summary
Dr. Pooja Sarin is an Assistant Professor in Data Science at the School of Computer Science, University of Petroleum and Energy Studies (UPES), Dehradun. She holds a PhD in Information Systems and Analytics from the Indian Institute of Technology Delhi.
Her research lies at the intersection of Artificial Intelligence, Computational Social Science, and Digital Behavioral Analytics, with a particular focus on understanding the “dark side” of digital platforms, including social media addiction, misinformation, and digital well-being. Her doctoral work involved large-scale analysis of social media interactions across India and the United States, and the development of novel behavioral frameworks for understanding user engagement and platform-driven reinforcement mechanisms.
She combines rigorous data-driven methods with theoretical grounding to contribute to both academic research and real-world digital policy discussions.
Work Experience
Assistant Professor (Data Science)
School of Computer Science, UPES, Dehradun
(Jan 2024 – Present)
Research Experience
- Doctoral Researcher, Indian Institute of Technology Delhi
- Research exposure in Computer Vision and AI applications in intelligent transportation systems
- R&D experience at CSIR–Central Scientific Instruments Organisation involving applied data analytics and signal processing
Industry & Academic Collaborations
Initiated industry-academia collaboration with Siemens Energy in the energy analytics domain
Research Interests
Artificial Intelligence (including Generative AI) | Computational Social Science | Digital Behavior and Social Media Analytics | Dark Side of Digital Technologies | Digital Health and Well-being | Big Data Analytics | Platform Governance and Innovation | Sustainability Analytics | Blockchain and Emerging Technologies
Teaching Philosophy
Dr. Pooja Sarin adopts a research-driven and application-oriented teaching approach that emphasizes conceptual clarity, critical thinking, and real-world relevance. She integrates case-based learning, data-driven assignments, and interdisciplinary perspectives to bridge theory with practice. Her pedagogy focuses on equipping students with strong analytical capabilities, problem-solving skills, and ethical awareness in the design and deployment of AI and data-driven systems.
Courses Taught
- Artificial Intelligence and Machine Learning
- Big Data and Large-Scale Computing
- Statistics and Data Analysis
- Database Management Systems (DBMS)
- Pattern Recognition and Anomaly Detection
- Software Engineering and Project Management
- Research Methodologies in Computer Science
- Human-Computer Interaction
Awards and Grants
- Principal Investigator – Institutional Shodh Research Grant (Explainable AI applications)
- Co-Principal Investigator – Industry-funded research project with Siemens Energy
- UPES Faculty Travel Grant (International Conference Participation)
- AIS Membership Scholarship (Association for Information Systems)
- Institute Fellowship, IIT Delhi
- GATE Scholarship (AICTE)
Scholarly Activities
- Published in peer-reviewed journals and international conferences in the areas of AI, analytics, and digital systems
- Active reviewer for leading journals including Decision Support Systems, Technological Forecasting & Social Change, and Technology in Society
- Reviewer and contributor to major international conferences such as ICIS, ACM, and IEEE venues
- Speaker and session chair at national and international academic forums
- Engaged in interdisciplinary research on digital ecosystems, user behavior, and responsible AI
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