CSRC Hosts CoMaDS 2025 in Boracay​

CSRC Hosts CoMaDS 2025 in Boracay

The Computational Science Research Center (CSRC), in partnership with the Numerical Analysis and Scientific Computing (NASC) Academic Group, the University of the Philippines Intelligent Systems Center (UP ISC), and the UP Diliman Mathematics Foundation Inc. (UPDMFI), successfully organized the CoMaDS 2025: International Workshop on Computational and Mathematical Methods in Data Science, held at Boracay Tropics Resort Hotel, Aklan, Philippines from April 3-5, 2025.

CoMaDS 2025 was also supported by Kanazawa University, Japan, and Institut Teknologi Bandung, Indonesia. Additionally, it was financially supported by the UP Office of International Linkages (OIL) through the OIL Hosting and WELS grants, as well as the UPD Extension Grant of the UP Diliman Office of the Vice Chancellor for Research and Development (OVCRD) through the Office of Extension Coordination (OEC).

This workshop gathered researchers and experts from the Philippines and abroad to showcase cutting-edge methodologies in data science and artificial intelligence, focusing on innovative approaches in data-driven research, modeling, and optimization.

Participants took part in the 3-day workshop, which featured lectures, hands-on computational exercises, scientific talks, and poster presentations. On the first day of the program, selected poster presenters showcased their research to fellow participants and invited speakers during a dedicated poster session. Topics covered a broad spectrum, including machine learning, scientific computing, mathematical modeling, artificial intelligence, and data science, reflecting the interdisciplinary nature of the workshop. The session encouraged active discussion and knowledge exchange, allowing presenters to receive valuable feedback and build academic connections. Toward the conclusion of the workshop, participants engaged in collaborative discussions and meaningful networking activities.

Dr. Renier G. Mendoza, CSRC Program Director and CoMaDS 2025 Workshop Chair, attended the event with key CSRC team members. Mr. Roberto Eugenio, Jr. and Mr. Reynaldo Yabut, Jr. handled registration and administrative support—Mr. Eugenio being the proponent of the OILS Hosting and WELS grants, and Mr. Yabut a project staff member for CSRC research grants. Mr. Ace Reario and Mr. Augusto Gayon managed technical support, while Ms. Kloudene Salazar, Mr. Rodney Pino, and Mr. Junel Isanan joined as participants.

Workshop Speakers

  • From Shapes to Insights: Examining Hidden Structures with Topological Data
    Dr. Paul Ignacio, University of the Philippines Baguio
  • Kernel Methods for Pattern Recognition
    Dr. Rachelle Sambayan, University of the Philippines Diliman
  • Physics-Informed Neural Networks: Fitting a Mathematical Model to Real Data
    Dr. Hyeontae Jo, Korea University, South Korea
  • Two-Stage Stochastic Programming: From the Newsvendor to Locations Problems
    Dr. Edoardo Fadda, Politecnico di Torino, Italy

Invited Speakers

  • The influence of data-driven mathematical modeling on public health policies during the COVID-19 pandemic and its future applications in this field
    Dr. Eunok Jung, Konkuk University, South Korea
  • Neural networks with ReLU powers need less depth
    Dr. Rhudaina Mohammad, University of the Philippines Diliman
  • Harnessing omnipresent oscillator networks as computational resource
    Dr. Hirofumi Notsu, Kanazawa University, Japan
  • Integrating Topological Data in Machine Learning
    Dr. Mark Lexter de Lara, University of the Philippines Los Baños
  • Modeling lesion transition dynamics to clinically characterize mpox patients in the Democratic Republic of the Congo
    Dr. Shingo Iwami, Nagoya University, Japan
  • Data Classification using phase-field methods and its efficient numerical scheme
    Dr. Seunggyu Lee, Korea University, South Korea
  • Modeling transportation network efficiency for typhoon relief delivery in Visayas
    Dr. Reinabelle Reyes, Philippine Space Agency
  • Incorporating Global Context through Cohomology-Based Persistent Landscapes in Transformer-Based Machine Translation
    Dr. Intan Muchtandi, Institut Teknologi Bandung, Indonesia

Ph.D. in Data Science Application for 1st Semester AY 2025-2026 now open!

Ph.D. in Data Science Application for 1st Semester AY 2025-2026 now open!

The Ph.D. in Data Science programs at the University of the Philippines Diliman are now accepting applications!
 
Interested in pursuing a Ph.D. in Data Science at the College of Science? The application deadline is on April 20, 2025. Qualified applicants for the Regular and Research tracks may also apply for the DOST-ASTHRDP scholarship.
 
Ready to start your journey as a Data Science scholar?  Apply here: bit.ly/UPD-PHDDS-2526S1-CS
 

Dissertation Proposal Presentation of Margaret Esther C. Cruz

Dissertation Proposal Presentation of Margaret Esther C. Cruz

Dissertation Proposal Topic: Image Reconstruction in Electrical Impedance Tomography using Physics-Informed Neural Networks with Differential Evolution

Date and Time: 4:00 PM, Monday, 3 March 2025

Place: CSRC Conference Room

Co-Advisers:

Renier Mendoza, Dr.rer.nat.
Rhudaina Mohammad, Ph.D.

Reader:

Karl Ezra Pilario, Ph.D.

About: This presentation will assess Margaret Esther C. Cruz’s dissertation proposal on Image Reconstruction in Electrical Impedance Tomography using Physics-Informed Neural Networks with Differential Evolution.


Contact Information:
csrc@science.upd.edu.ph

Thesis Proposal Presentation of Ricarido M. Saturay Jr.

Thesis Proposal Presentation of Ricarido M. Saturay Jr.

Thesis Proposal Topic: Estimating landscape evolution parameters from topography using machine learning models trained on numerical landscapes

Date and Time: 12:00 PM, Wednesday, 16 October 2024

Place: CSRC Conference Room

Thesis Co-Advisers:

Johnrob Y. Bantang, Ph.D.
Noelynna T. Ramos, D.Sc.

Thesis Reader:

John Dale B. Dianala, Ph.D.

Thesis Examiners:

Maricor N. Soriano, Ph.D.
Giovanni A. Tapang, Ph.D.

 

About: This presentation will assess Ricarido M. Saturay Jr.’s thesis proposal on Estimating landscape evolution parameters from topography using machine learning models trained on numerical landscapes.

 

 

Contact Information:
csrc@science.upd.edu.ph

Candidacy Examination of Margaret Esther Cruz

Candidacy Examination of Margaret Esther Cruz

Candidacy Examination Topic: Numerical Solutions of Partial Differential Equations using Physics-Informed Neural Networks

Date and Time: Thursday, 08 August 2024 at 3:00 PM

Place: CSRC Conference Room

Panel Members:

Dr. Rhudaina Mohammad
Dr. Renier G. Mendoza
Dr. Karl Ezra S. Pilario
Dr. Gil C. Claudio
Dr. Hyeontae Jo

About: This examination will assess Margaret Esther Cruz’s research on Numerical Solutions of Partial Differential Equations using Physics-Informed Neural Networks.

 

 

Contact Information:
csrc@science.upd.edu.ph

Candidacy Examination of Khristian G. Kikuchi

Candidacy Examination of Khristian G. Kikuchi

Candidacy Examination Topic: Handling Data Organization, Data Types, and Analytical Methods for Education and ZooArchaeology

Date and Time: Wednesday, 07 August 2024 at 3:00 PM

Place: CSRC Conference Room

Panel Members:

Dr. Giovanni A. Tapang
Dr. Juan C. Rofes
Dr. Rachelle R. Sambayan
Dr. Johnrob Y. Bantang
Dr. Maricor N. Soriano

About: This examination will assess Khristian G. Kikuchi’s research on Handling Data Organization, Data Types, and Analytical Methods for Education and ZooArchaeology.

 

 

Contact Information:
csrc@science.upd.edu.ph

Candidacy Examination of Ricarido M. Saturay, Jr.​

Candidacy Examination of Ricarido M. Saturay, Jr.​

Candidacy Examination Topic: Detecting Steady State Topography Using Machine Learning

Date and Time: Thursday, 13 June 2024 at 1:00 PM

Place: Dean’s Office Conference Room

Panel Members:

Co-Advisers: Dr. Johnrob Y. Bantang, Dr. Noelynna T. Ramos
Reader: Dr. John Dale B. Dianala
Examiners: Dr. Maricor N. Soriano, Dr. Giovanni A. Tapang

About: This examination will assess Ricarido M. Saturay, Jr.’s research on applying machine learning techniques to detect steady-state topography. The study aims to enhance geospatial analysis by leveraging AI to identify landforms that have reached equilibrium over time. The findings could provide valuable insights into geological processes and contribute to advancements in remote sensing and environmental monitoring.

 

 

Contact Information:
csrc@science.upd.edu.ph