UPISC Research Grants
Cycle 2: FY 2025-2026

Digital information ecosystems are reshaping the production, dissemination, and consumption of information in the digital age. These vast networks comprise digital platforms that facilitate both rapid communication and the widespread distribution of content. This new digital landscape offers unprecedented access to information and supports innovative forms of data journalism. Advanced data science and AI techniques provide the potential to monitor information flows, identify patterns, and support informed decision-making across society. At the same time, these ecosystems are prone to the spread of misinformation. Challenges include managing the virality of false narratives, countering algorithmic biases, and safeguarding public discourse in the face of rapid, often unfiltered, information exchange. How can advanced data science and AI techniques be deployed to monitor and counteract misinformation in real time? What would be the impact of mapping misinformation flows using network analysis and predictive modeling? To what extent can data journalism and computational tools restore trust and clarity within digital ecosystems? How might insights from complexity science lead to innovative strategies for balancing information accuracy with freedom of expression?

Education, as a foundational pillar of society, is undergoing a profound transformation through the integration of data science, AI, and complex systems theory. These technological advances are reshaping learning environments and redefining how we understand teaching and learning processes. Innovations such as personalized learning platforms, adaptive learning technologies, and intelligent tutoring systems are emerging from this integration. Educators now have access to real-time analytics that help tailor instruction to individual student needs and support evidence-based curriculum development and resource allocation. However, despite these advances, challenges remain in ensuring accessibility and equity. Persistent educational gaps and the complex interplay among students, teachers, curricula, policies, and technology require careful examination. Balancing rapid technological innovation with the need for sustainable and adaptable educational systems remains a significant challenge. How can data science, AI, and complexity science uncover hidden dynamics within classroom interactions? What would happen if every classroom leveraged real-time analytics to fully personalize instruction? To what extent can these technologies close persistent educational gaps while ensuring equity? How might complex systems analysis reveal interdependencies among educational components to inform resilient interventions?

Personalized and human-centered technologies are emerging at the intersection of data science, AI, and complex systems analysis. They aim to design intelligent systems that adapt to individual needs, preferences, and behaviors, making technology more responsive and effective in daily life. Such technologies, including ever-attentive AI assistants, are transforming domains ranging from healthcare to everyday decision-making. They offer the promise of enhanced efficiency, tailored recommendations, and dynamic support that adapts over time—empowering users to engage with technology on a more personal level. However, as these systems become more ingrained in daily routines, ethical challenges related to data privacy, algorithmic transparency, and fairness come to the forefront. There is a risk that personalization might compromise user autonomy or exacerbate biases if not carefully managed. How can data science, AI, and complexity research be harnessed to create systems that learn from and adapt to individual user behaviors over time? What would be the impact if AI assistants could anticipate needs and evolve alongside long-term behavioral patterns? To what extent can ethical safeguards be integrated without compromising personalization? How might principles from complexity theory guide the design of technologies that are both deeply personalized and socially equitable?