About Me

Anthony Val C. Camposano

• PhD Physics
  University of Oslo, Oct 2021 - Present
  Sem Sælands vei 24, 0371 Oslo
  Research Focus: Machine learning + MD/MC for nanoscale geological processes.
  
• MS Physics
  University of San Carlos - TC, June 2017 - July 2020
  Nasipit, Talamban, Cebu City 6000
  Research Focus: Buot's lattice of Weyl-Wigner formalism for quantum transport in nanostructures.

Publications:

1. Genetic Algorithm Workflow for Parameterization of a Water Model Using the Vashishta Force Field, The Journal of Physical Chemistry B. (2025)
2. An Extended Energy-Biased Aggregation-Volume-Bias Monte Carlo (EB-AVBMC) Method for Nucleation Simulation of a Reactive Water Potential Journal of Chemical Theory and Computation. (2025)
3. Vertical and rotational motion of mahogany seed, 1st Int. Conf. in Applied Physics and Materials Science (2015)

Workshops/Schools:

1. Flowing matter in porous media, (Feb 2025)
2. Summer CINECA School: dive into the World of HPC, (July 2024)
3. Machine Learning Interatomic Potentials: Theory and Practice - School for Young and Early-Career Researchers, (Nov 2023)
4. Methods in Molecular Simulations and Machine Learning, (July 2022)
5. MolSim2022 - Winterschool on Molecular Simulations, (Jan 2022)
6. Asian Network School and Workshop on Complex Condensed Matter Systems (Nov 2019): Non-equilibrium quantum transport using Lattice Weyl-Wigner Formalism

Conferences:

1. Machine Learning an All-Atom Empirical Force Field for a Water-Silica System, European Geoscience Conference (EGU), Vienna, Austria (April 2024)
2. Extraction of Waterfalls from DTM using OBIA: A Case Study of Mantayupan Falls in Barili, Cebu, 36th Asian Conf. on Remote Sensing (2015)
3. Wetland Extraction Using Random Trees Classifier, 37th Asian Conf. on Remote Sensing (2016)
4. IR Spectrum of Water Cluster Using Density Functional Theory, ASEAN-CAFMN (2017)

Online Courses Completed:

Deep Learning Specialization (Completed: Oct. 2017)
1. Structuring Machine Learning
2. Neural Network and Deep Learning
3. Improving Deep Neural Networks
4. Convolutional Neural Networks
5. Sequence Models
Web Design for Everybody (Completed: Aug. 2017)
1. Intro to HTML
2. Intro to CSS
3. Javascript
4. Responsive Design
Applied Data Science with Python (Completed: Nov. 2017)
1. Data Analysis
2. Machine Learning
3. Plotting
4. Social Network Analysis
5. Text Mining