Research:
Currently, I am working on modeling the dynamics of the electron transfer chain inside the cryptochrome, which is used for magnetoreception in avian migration, using machine learning frameworks.

Background:
2021: Postgraduate Diploma in Quantitative Life Sciences at the Abdus Salam International Center for Theoretical Physics in Trieste, Italy Research: Olfactory search with reinforcement learning using Long-Short-Term Memory (LSTM) network 2018: BS Applied Physics at the University of the Philippines Diliman Research: Modeling complex systems such as granular materials and earthquakes using cellular automata. Using recurrence network analysis to model causal events in avalanches and earthquakes.

Experience:
Data Scientist at GCash in the Philippines Machine Learning Engineer at Pointwest in the Philippines

Publications:
D.C. Biton, A. B. Tarun, and R.C. Batac, “Comparing spatio-temporal networks of intermittent avalanche events: Experiment, model, and empirical data,”Chaos, Solitons and Fractals 20, pp 1009519, 2020.
D.C. Biton, and R.C. Batac, “Comparing the sandpile model with targeted triggering and the Olami-Feder-Christensen model as models of seismicity using recurrence network analysis,” Journal of Physics: Conference Series 1298 (1), pp 012007, 2019.
C.D. Janer, D.C. Biton, and R.C. Batac, “Incorporating space, time, and magnitude measures in a network characterization of earthquake events,” Acta Geophysica 65 (6), pp 1153-1166, 2017.