UPISC Research Grants Cycle 2: 2025-2026

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Overview

The call for proposals for the UPISC Research Grants (FY 2025-2026) is now open. The grant aims to support pluridisciplinary, high-impact research across the constituent universities of the UP System, focusing on the application of complex systems, data science, and artificial intelligence on important areas related to sustainable socio-economic development. 

The grant funds Regular and High-Impact projects. 

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Regular Projects

Regular projects can receive up to PHP 1.5 million per year. Regular projects must satisfy the following criteria:


Preference is given to applied research.

High-Impact Projects

High-Impact projects are eligible for up to PHP 5 million per year and  must meet the following criteria:

While the project funding cap is PHP 5 million, exceptional projects with significant potential may be considered for additional funding.

Application areas for FY 2025-2026

While we encourage and will consider applications for research funding in all these areas, for FY 2025-2026, funding will prioritize three areas in particular.

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Digital information ecosystems and misinformation dynamics

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

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 human-centered technologies

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?

Important dates

See section B (Registering your application for advance review) below.
See section C (Submitting your application for CU endorsement) below.

Information sessions

Throughout the month of May, UPISC will be visiting each CU to dialogue regarding UPISC-related opportunities such as this research grant scheme, and the infrastructural support provided by UPISC facilities such as the Data Commons. 

Downloads

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Guidelines

Please download the Guidelines for UP ISC Research Grants Application (FY 2024-2025) document (PDF).

The Guidelines contain the following information:

Information you need to prepare your application

We encourage you to prepare your application by drafting your answers offline in a document. You can use the UPCIS Research Funding Application Preview file provided on this page for this purpose. This file describes all the fields thta you will be asked to fill in the web form.

Line item budget (LIB) template

Use the Excel template on this page to format your line item budget. 

Application procedure

To apply for a grant, you will need to: prepare your grant application; register your application for advance review of the UP ISC; and submit your application for CU endorsement.  The application process is summarized by the following flowchart:

A. Preparing your grant application

We recommend that CVs include the following information:
  • Educational Background
  • Field of Specialization
  • Areas of Research Interest
  • Professional/Employment/Work History including significant scientific, technological and/or entrepreneurial activities undertaken
  • Significant achievements (up to 3) related to your expertise or profession
  • Publications in international peer-reviewed journals, books, etc. and creative work (Indicate 3 most important outputs.)
  • Relevant training
  • Fellowships/Grants

B. Registering your application for advance review

You will need to register your application via the Airtable web form on this page. This will allow UP Intelligent Systems Center to do an advance review of your proposal while you submit your proposal to your CU for review and endorsement. Registering your application will also generate the documents you need to submit your proposal for CU review.

To register your proposal for advance review, follow these steps:

The form is displayed below. If you are having viewing or filling up the form, click here to open the form in a new window. You will need to log into Airtable with a @up.edu.ph email address to view the form. Create an account on Airtable if you do not have an account yet. 

C. Submitting your application for CU endorsement

Submit (via channels) your proposal for endorsement of your Chancellor after you have registered your application.

Include the following documents when you submit your application for CU endorsement:

Your CU should then forward your endorsed application to the UP ISC Executive Director.

Proposal evaluation

See Important dates on this page for when you should expect to receive a decision about your application.

UP ISC will invite its Affiliates and Fellows to review proposals. Reviewers are assigned based on expertise. Applications will be evaluated based on the following general criteria (click each to expand):

Soundness and validity of research design

The grant application clearly states the research problem, providing motivation for undertaking the research. The grant application presents a succinct, clear, and logically described set of objectives and a plan of action. The applicant will be applying or developing sound research methods or tools to address the defined problem; these methods or tools are effectively described. The application illustrates the potential value of the solution or contribution to the research problem, showcasing its impacts within and outside the area/field of study. The proposed project is within the remit of the UP ISC's focus on data science, artificial intelligence, and complexity science, with preference given to applied research. All parts of the application reinforce each other.  

Disciplinal expertise and research management competence

The applicant demonstrates a solid understanding of the literature in the area and previous work related to the research problem. The set of expertise of the project team is well-aligned with the requirements of and problems raised by the project; expertise is neither missing from the team nor are there unnecessary members in the project team. The background and prior experience of the project proponents (i.e., the PI and other project collaborators) suggest that the project will be carried out successfully. The project involves an appropriately curated mix of different disciplines as embodied by the different departments, colleges, faculties, and/or CUs involved in the project. 

Significance and impact of outcomes

The application shows promise for impact in terms of direct benefit to communities and individuals; novel outcomes, inventions, and other forms of intellectual property; publications in high-impact journals and indexed conference proceedings; and/or widely-visible public engagement and research extension events. The funding requested is commensurate with the projected significance and impact of the project. Wider public engagement is considered. Priority will be given to projects that address the priority areas for the call. 

For High-Impact projects, there is promise for continued, multi-year outcomes or follow-up initiatives. There is clear potential for significant impact on policy or industry, and there is a clearly defined target audience or partner. The project clearly addresses high-priority goals such as the UN SDGs, the 2023-2028 Philippine Development Plan strategies, and/or PAGTANAW 2050 facets. 


Institutional equity and growth within the UP ecosystem

Preference is given to projects that involve collaboration across the CUs. The project is likely to lead to continued and/or novel collaborations across different CUs, with pathways for mutual benefit and disciplinal growth.  Financing of the project would contribute to equitable development of intelligent systems research within the entire UP ecosystem and across multiple regions of the country. 

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