Sambayan, Rachelle
Kernel matrix completion. Mathematics of finance. Kernel methods. Data fusion. Machine learning.
 Numerical Analysis and Scientific Computing (member)
 Modelling and Applications (affiliate)

Education

Ph.D. in Science and Technology (2018)
Gunma University, JapanDissertation: Kernel Matrix Completion
Adviser: Assoc. Prof. Tsuyoshi Kato 
M.S. Applied Mathematics (Mathematics of Finance) (2012)
University of the Philippines, DilimanThesis: GARCH Approach to Modeling Structural Breaks of Stock Volatility
Adviser: Prof. Fredegusto Guido P. David 
B.S. Mathematics (2007)
University of the Philippines, DilimanThesis: Moore Graphs of Diameter 2
Adviser: Prof. Jose Maria P. Balmaceda

Ph.D. in Science and Technology (2018)

Research
As Project Leader
 Analyzing Genetic Admixture on Marmoset Genomic Data Using Persistent Homology
Research Grants Under the Computational Research Laboratory Program of the Institute of Mathematics, University of the Philippines – Diliman
Duration: 01 Aug 2022 – 31 July 2023.
 Temperature and Precipitation Impacts on MultiStrain Dengue Transmission Dynamics in the Philippines (Project No. 22225 PhDIA YEAR 1)
Office of the Vice Chancellor for Research and Development, University of the Philippines – Diliman
Duration: 01 Jun 2022 – 31 May 2023 (Extended to 31 Dec 2023)
 Estimating the Resultant Efficacy of the Administration of Two or More Vaccines in a Single Community
Bayanihan to Recover as One Act: Grant for Research on COVID19 in the Philippines
Funded by: Philippine Government
Duration: 01 Jun 2021 – 31 May 2022 (Extended to 31 July 2022).
 Modeling Structural Breakpoints in Volatility of Philippine PesoUS Dollar Currency Exchange Rate
(MAT19101 Pending Publication)
Natural Sciences Research Institute, University of the Philippines – Diliman
Duration: 01 Jan 2019 – 31 Dec 2019.
As CoProject Leader
 Computational Laboratory for Covid19 Modeling and Forecasting
Republic Act 11494 Bayanihan to Recover as One Act
Funded by: Philippine Government
Duration: 01 Jan 2021 – 30 Jun 2021
 Allocation of Different COVID19 Vaccines to a Heterogeneous Population: Exploring Various Scenarios
Bayanihan to Recover as One Act: Grant for Research on COVID19 in the Philippines
Funded by: Philippine Government
Duration: 14 Dec 2020 – 30 Jun 2021

Teaching
Teaching
 Math 20: Precalculus: Functions and their Graphs
 Math 21: Elementary Analysis I
 Math 22: Elementary Analysis II
 Math 23: Elementary Analysis III
 Math 171: Introduction to Numerical Analysis
 Math 180.1: Operations Research I
 Math 271.1: Numerical Analysis I
Mentoring
Current Student Advisees:
 Nicole Angela D. Sajo: B.S. Mathematics. Undergraduate research topic: Kernel Methods, optimization.
 Aidan Raphael R. Prieto: B.S. Mathematics. Undergraduate thesis topic: Mathematical finance, optimization.
 A C Bernadette M. Ducusin: M.S. Applied Mathematics (Mathematical Finance). Graduate thesis topic: Optimal Investment with Transaction Cost. Coadvising with Dr. Jose Maria Escaner IV.
 Sheena M. Escordial: M.S. Applied Mathematics (Optimization and Approximation). Graduate thesis topic: Combined Simulated Annealing, Genetic Algorithm, Bus Network Design. Coadvising with Dr. Maria Brenda Rayco.
 Maikel Roi M. Aguilar: M.S. Applied Mathematics (Optimization and Approximation). Graduate thesis topic: Genetic Algorithm Solution to an Evacuation Planning Model.
 Michael E. Subido: Ph.D. Mathematics. Dissertation topic: Temperature and Precipitation Impacts on MultiStrain Dengue Transmission Dynamics in the Philippines. Coadvising with Dr. Aurelio de los Reyes V.
(2 BS Mathematics students, 4 MS Applied Mathematics students, 1 PhD Mathematics students)
Former Student Advisees:
 Al Bien Christian R. Aculan: M.S. Applied Mathematics Graduate thesis Analyzing Genomic Admixture on Marmoset Genetic Data Using Persistent Homology, Aug 2023. Coadvising with Dr. Maria Vivien Visaya (University of Johannesburg).
 Mark Jayson A. Labaclado: B.S. Mathematics. Undergraduate thesis Technical Analysis Prediction of Philippine Stock Prices Using Support Vector Regression, July 2023.
 Alfonso Gregorio M. Lava: B.S. Mathematics. Undergraduate thesis Stock Market Prediction: A Hidden Markov Model Based Approach, July 2023.
 Mark Lexter D. De Lara: Ph.D. Mathematics. Dissertation Persistent Homology Classification Algorithm, January 2023. Coadvising with Dr. Clarisson Rizzie Canlubo (UP Los Baños).
 Ela Mae A. Riñon: B.S. Mathematics. Undergraduate thesis Topological Data Analysis on Stock Market, January 2023.
 Hanna Rhae Lyssa D. Improso: M.S. Applied Mathematics. Graduate thesis Forecasting Philippine Financial Time Series Data Using Weighted Support Vector Regression Based on Quantum Finance Model, June 2021.
 Rodney B. Pino: M.S. Applied Mathematics, Most Outstanding MS Graduate. Graduate thesis Baybayin Optical Recognition System using Support Vector Machine, June 2021. Coadvising with Dr. Renier Mendoza.
 Donald Jay M. Bertulfo: M.S. Applied Mathematics. Graduate thesis A Machine Learning Approach to Narrative Retrieval in Economic News: The Case of Oil Price Uncertainty, August 2020. Coadvising with Dr. Guido David.
 Adrian M. Villareal: B.S. Mathematics. Undergraduate thesis A Comparative Study on ARCH and GARCH Models in Forecasting Stock Price Volatility of Globe Telecom Inc. Under Varying Historical Data, June 2019.
 Rolando H. Labuguen, Jr.: B.S. Mathematics. Undergraduate thesis Option Pricing Using GARCHForecasted Volatility, April 2014. Coadvising with Dr. Guido David.

Publications
(* denotes graduate student coauthor)
Refereed Journal Papers
 Pino R*, Mendoza R, Sambayan R. 2022. Blocklevel Optical Character Recognition System for Automatic Transliterations of Baybayin Texts Using Support Vector Machine. Philippine Journal of Science 151(1), pp. 303—315, ISSN 0031 – 7683, Feb 2022.
 Pino R*, Mendoza R, Sambayan R. 2021. A Baybayin word recognition system. PeerJ Computer Science 7:e596 https://doi.org/10.7717/peerjcs.596
 Pino R*., Mendoza R., Sambayan R. 2021. 1.Optical character recognition system for Baybayin scripts using support vector machine. PeerJ Computer Science 7:e360 https://doi.org/10.7717/peerjcs.360
 R. Rivero*, Y. Onuma*, and T. Kato. (2018) “Threshold AutoTuning Metric Learning.” IEICE Transactions on Information and Systems, vol.E102D, no.6, pp.1163–1170, June 2019. Preprint: arXiv
 R. Rivero* and T. Kato. (2018) “Parametric Models for Mutual Kernel Matrix Completion.” IEICE Transactions on Information and Systems, vol.E101D, no.12, pp.2976—2983, Dec. 2018. Preprint: arXiv
 R. Rivero*, R. Lemence, and T. Kato. (2017). “Mutual Kernel Matrix Completion.” IEICE Transactions on Information and Systems, vol.E100D, no.8, pp.1844—1851, Aug. 2017. Preprint: arXiv
Conference Proceedings
 R. Rivero and G. David. (2019). “Modeling Structural Breakpoints in Volatility of Philippine PesoUS Dollar Currency Exchange Rate.” Rahmawati, Y. (Ed.), Taylor, P. C. (Ed.). (June 2019). Empowering Science and Mathematics for Global Competitiveness. London: CRC Press.