PESU Research Foundation
PESURF
"Cultivating Thought. Igniting Impact."
About PESURF
Modern global challenges do not fit perfectly into academic silos. Traditional research often stays trapped in publications, failing to reach the communities and industries that need it most. PESU Research Foundation (PESURF) serves as a pivotal anchor within the university, bridging this gap and nurturing a vibrant research culture. Fostering innovative, yet frugal solutions to address pressing real-world challenges is central to our engagement with student and faculty researchers within the university and external collaborators. Our core pillars that translate academic theory into practical applications are : Cultivate - We foster deep, analytical thought. We provide our researchers with the intellectual space and resources needed to question the status quo. Ignite - We fuel continuous innovation. By providing cutting-edge infrastructure and strategic funding, we accelerate the journey from spark to solution. Converge - We unite interdisciplinary minds. We bring together engineers, scientists, humanists, and industry experts to solve problems from every angle. Impact - We deliver transformative outcomes. Success for us is not measured by only publications, but by scalable, tangible changes in society and industry.
Areas of Research
4Research in this domain is led by an interdisciplinary team of researchers to understand and solve multiple healthcare related problems through advanced technology
Research in this area explores recent advancement in AI for breakthroughs in various fields
Research in this domain is focused on the impact and predictive capabilities of noncognitive skills in academic success
Research in this domain explores innovative systems and tools for solving environmental problems, aligning with UN SDG goals
Our Objectives
2Create an ecosystem that empower the students and faculty in high-impact research. Develop innovative, frugal solutions for societal challenges in multidisciplinary domains.
Bridge the academia - industry gaps through mutually beneficial collaborative research. We onboard organizations and research advisors to work along with our faculty and students in these projects.
Active & Completed Projects
21. Students - join us as Interns to work on an exciting healthtech project.
We welcome student interns from departments of CSE, CSE/AIML and Nursing to join our project.
2. Faculty - collaborate with us to expand the scope of the project
3. External Researchers - join us to bring impactful research outcomes
4. Entrepreneurs - commercialize some of our research findings
Contact for more details: sudeepar@pes.edu
1. The AgeWell Index: An RF-Seeded Adaptive Genetic Algorithm for Explainable Aging Assessment in Mid-Life Adults – Doi: 10.1109/IITCEE67948.2026.11394091.
2. “Unsupervised Learning for Successful Ageing: Integrating PCA And Autoencoders in the Construction of a Multi-Domain Composite ageing index”, presented at the 10th International Conference on Information System Design and Intelligent Applications (ISDIA-2026) Organized by University of Wollongong in Dubai
D. Suryaprasad, S. Jayadevappa and B. Shah, "Learnability Index – a Composite Measure for Non-Cognitive Skills Relevant in Academics," 2020 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), Takamatsu, Japan, 2020, pp. 349-354, doi: 10.1109/TALE48869.2020.9368476.
Product:
Learnability Index Scale: An assessment tool based on self-reported Likert Scale based instrument for measuring non-cognitive skills relevant in the academic environment.
Our Researchers
6
Research Funding
1 funding source
1 funding source
Partners & Collaborators
Tools & Technologies
IBM SPSS Statistics is a comprehensive, user-friendly software platform for advanced statistical analysis, data management, and data visualization.
"IBM SPSS Statistics is a comprehensive statistical analysis platform designed to help organizations and individuals extract reliable insights from data. It combines robust statistical testing, predictive modeling, regression, and forecasting with streamlined data preparation and automated analysis. With built-in extensibility for Python and R, scalable licensing, and deployment flexibility, it empowers its users across levels to move confidently from data to defensible, data-driven decisions." For more details: https://www.ibm.com/products/spss-statistics
Add-on module for IBM SPSS Statistics for regression models studies.
"IBM® SPSS® Regression enables you to predict categorical outcomes, create regression models, analyze model summaries and apply various nonlinear regression procedures to datasets when studying consumer buying habits, treatment responses, efficacy of diagnostic measures, credit risk analysis and other situations where ordinary regression and data analysis techniques are limiting or inappropriate."
More details available at https://www.ibm.com/products/spss-statistics/regression
