Development Team Lead / Accenture Inc.

Jun 2024 -Present

Lead developers, providing mentorship and fostering a collaborative environment to enhance team performance and skill development. Oversee the design, development, and deployment of AI-driven solutions, ensuring adherence to best practices in technical architecture and coding standards. Drive the technical strategy and architecture for scalable and efficient database design and cloud infrastructure, leveraging advanced tools and methodologies. Coordinate cross-functional requirements, working closely with stakeholders to align technical objectives with business goals.

AI Developer / Accenture Inc.

Aug 2023 - Jun 2024

Developed a web app solution with integrated chat functionality, leveraging Retrieval-Augmented Generation (RAG) for advanced knowledge querying from user-uploaded databases. Responsible for coding, testing, and deploying code in the MS Azure Cloud environment under the Serverless architecture framework. Successfully transitioned the solution from company internal use to client projects, securing paying customers.

Researcher/Instructor / Institute of Mathematics, University of the Philippines Diliman

Aug 2014 - Jun 2023

Co-authored 5 peer-reviewed academic publications and presented research findings at international conferences. Mentored over 1000 students, receiving an average to strongly positive feedback from 98% of mentees. Organized talks and meetings with faculty members, fostering collaborations with external institutions.

QR Code Generative Imaging: Exploring ControlNet with Stable Diffusion

QR Code Generative Imaging explores the innovative combination of functional QR codes with artistic image generation using the Stable Diffusion neural network model and ControlNet. This project aims to create visually compelling images conditioned on QR code inputs, balancing aesthetics with functionality. By employing the AUTOMATIC1111 Stable Diffusion GUI and leveraging various checkpoints like Dreamshaper and RevAnimated, diverse styles and outputs were tested. Despite initial challenges, including significant processing times, the project successfully generated scannable QR codes embedded within intricate designs. These outputs have potential applications in enhancing the visual appeal of digital and physical presentations, adding a decorative element while maintaining QR code functionality.

NBASeriesML: Predicting Game 7 Outcomes in NBA Playoffs

NBASeriesML utilizes machine learning to predict the outcome of NBA Game 7 matchups, focusing on the Boston Celtics vs. Miami Heat 2023 Playoffs East Finals series. The model, trained using gradient descent for linear regression on point differences from 147 previous Game 7s, converged after 150 iterations with a prediction favoring Miami at 55%. This approach highlights the power of data-driven sports analytics in forecasting game outcomes. The project demonstrates how machine learning can enhance understanding and strategy formulation in professional basketball.