ALaM Project

1 month ago

The DOST-Advanced Science and Technology Institute-Automated Labeling Machine (ASTI-ALaM) Project is the DOST-ASTI component of the Philippine Sky Artificial Intelligence Program (SkAI-Pinas). The project aims to develop an optimized workflow in developing machine learning and artificial neural network-based models for different application domains, as well as to develop an online model store where the developed models of the project can be accessed for tasks such as mapping and computer vision using traditional remote sensing, machine learning, and deep learning.


About ALaM Project

The ASTI-ALaM Project’s primary objective is to maximize the utilization of the country's available remote sensing data, taking advantage of the huge volume of archived datasets that is already available in both raw and processed format to serve as base sets of training data which can be further augmented to train more accurate deep learning models.

The project involves (1) segmenting objects within satellite-captured RGB images, classifying them into natural or man-made features, and (2) estimating the structural strengths of buildings using satellite-captured images.

The current work of the ASTI-ALaM team includes (1) the full-scale training and optimization of AI models, (2) act as the interagency interface with UP Mindanao’s ALaM-Large-Scale Initiative (ALaM-LSI), and (3) support ALaM-LSI in AI design and Artificial Intelligence Programming Interface (AIPI) framework implementation.

By developing AI-based solutions that can be applied in different fields, such as road management, urban planning, and disaster management, the project aims to provide decision-makers with invaluable tools to enhance their decision-making process using AI.


ALaM Project



The ASTI-ALaM Project seeks to enhance the capacity of DOST-ASTI researchers and engineers in developing AI-based solutions using DOST-ASTI Computing and Archiving Research Environment’s (COARE) High-Performance Computing Facility and establish an optimized workflow for developing machine learning and artificial neural network-based models for different application domains. 

The Research Unit is involved in gathering best practices in Artificial Intelligence and Machine Learning such as the usage of remote sensing, as well as in analysis and processing of geospatial data using Geographic Information System (GIS) tools and techniques. The Unit is also responsible for model training process optimization, hyperparameter tuning, catastrophic forgetting prevention, and exploration of applicable neural network architectures. 

 The Software Engineering Unit, on the other hand, works on devising a web-based platform for efficient distribution of developed AI and ML models for public usage, while ensuring code integrity and anticipating the scale of needed resources for proper operation of these models. ASTI-ALaM software engineers also carry out the development of stable applications from the prototypes of the AI and Data Engineering team. 

 The AI and Data Engineering Unit develops AI and ML models using available satellite imagery captured within the Philippines using automated object identification and labeling image segmentation, land cover change detection, and prediction, among other applications. The team also performs web application prototyping to test the usability of the developed models in web-based settings. The models being developed are currently stored in a DOST-ASTI-hosted GitLab Community Edition (CE) client. 


Project Staff

Project Management Team

Joanna G. Syjuco - Division Chief, CSD

Vanesa O. Osiana - Project Manager, CSD

Mary Joy Daphne P. Padilla - Project Development Officer II

Nina S. Bacay - Project Assistant III 

Joanne Marie R. Sormillo - Project Assistant II

Kurt G. Valcorza - Science Research Specialist I (Technical Writer)


Technical Team

Franz A. De Leon, Ph.D. - Project Leader 

Jeffrey A. Aborot - Supervising Science Research Specialist 

Elmer C. Peramo - Senior Science Research Specialist 

Michelle P. Neverida - Science Research Specialist II 

John Kevin C. Abonita - Science Research Specialist II 

Eduardo T. Piedad Jr. - S&T Fellow I


Research Unit

Jonel Hong - Science Research
Specialist II (Researcher)

Adrian S. Remigio - Science Research
Specialist II (Researcher)

Software Engineering Unit

Jhon Rey T. Artuz – Science Research Specialist I (Back-end Developer)  

Daniela Nicole D. Rebatis – Science Research Specialist II (Front-end Developer)  

Jean Paul P. Jael – Science Research Specialist I (BA/UI-UX Designer)  

Carlo T. Barbadillo – Science Research Specialist I (Software QA)  

Carlo Nico P. Pielago – Science Research Specialist I (Software QA)  


AI Engineering Unit

Julius Noah H. Sempio - Senior Science Research Specialist (Senior AI Engineer) 

Jose Maria E. Braga - Science Research Specialist II (AI Engineer)

Samuel Harrison P. Cerrudo – Science Research Specialist II (AI Engineer)  

Dhon Xean S. Bobis – Science Research Specialist II (Data Engineer)