Expertise

  • Complexity Science, Neural Networks, Computational and Statistical Physics, Social Networks, Biological Physics, Predictive Analytics, Project Management, Data Analytics, Machine Learning, Forecasting

Research Interests

  • Complex systems, Neural networks, Network science, Computational and statistical physics
Back to Faculty

Christopher P. Monterola, PhD

Professor
Aboitiz Chair in Data Science
Head, Aboitiz School of Innovation, Technology, and Entrepreneurship
Executive Managing Director, ACCeSs@AIM

Academic Background

  • Ph.D. in Physics, (Most Outstanding PhD Student (College of Science), Edgardo Gomez Award for Excellence in Dissertation Research, Batch Valedictorian), University of the Philippines Diliman (UPD)
  • Master of Science in Physics, (Most outstanding MS student (College of Science), Batch Valedictorian), University of the Philippines Diliman (UPD)
  • Bachelor of Science in Applied Physics, (Magna cum Laude, Dean’s medallion, Best Thesis), University of the Philippines Diliman (UPD)

Professional and Academic Experience

  • Senior Scientist and Capability Group Manager (CGM) of the Complex Systems (CxSy) Capability Group, Computing Science Department, Institute of High Performance Computing, A*STAR, Singapore (founding CGM, August 2013-present)
  • Adjunct Senior Research Fellow, Complexity Institute, Nanyang Technological University, Singapore. (October 2015-present)
  • Principal Investigator, Complex Systems Programme, A*STAR Urban Systems Initiative (2012-present)

Affiliations, Awards, and Honors

  • 2020 Academician by the National Academy of Science and Technology 
  • 2016, Country Prize Winner (Singapore), United Nation Global Pulse's The Big IDEAS Competition for Sustainable Cities and Urban Communities, June 2016. EF Legara, C Monterola, JF Valenzuela.
  • 2016, SMRT Most Innovative Solution Award, IHPC (from CxSy MA Ramli, V Jayaraman, G Lee, C Monterola), SMRT Vendors'; Day, 30 March 2016.
  • 2014, ICCS Best Workshop Paper. N Othman, EF Legara, V Selvam, C Monterola, "Simulating Congestion Dynamics of Train Rapid Transit using Smart Card Data," International Conference on Computational Science, Cairns, Australia, 9-12 June 2014.
  • 2013, IEEE SCALE Challenge. First Prize Winner. H Kasim, T Hung, EF Legara, C Monterola, G Lee, X Li, BS Lee, S Lu, L Wang, and V Jayaraman, "Scalable Complex System Modeling for Sustainable City," Sixth IEEE International Scalable Computing Challenge (SCALE 2013), Delft, Netherlands, 14-16 May 2013.
  • 2009-present, Conferred the scientist rank 1 by the University of the Philippines System
  • 2008-2012, University of the Philippines Centennial Professorial Chair

Publications

  • Yang, B., Ren, S., Legara, E., Li, Z., Ong, E. Y., Lin, L., & Monterola, C. (2020). Phase Transition in Taxi Dynamics and Impact of Ridesharing. Transportation Science. doi:https://pubsonline.informs.org/doi/abs/10.1287/trsc.2019.0915
  • Huynh, H. N., Makarov, E., Legara, E. F., Monterola, C., & Chew, L. Y. (2018). Characterisation and comparison of spatial patterns in urban systems: A case study of U.S. cities. Journal of Computational Science, 24, 34-43. doi:10.1016/j.jocs.2017.12.001
  • Hu, N., Zhong, J., Zhou, J. T., Zhou, S., Cai, W., & Monterola, C. (2018). Guide them through: An automatic crowd control framework using multi-objective genetic programming. Applied Soft Computing, 66, 90-103. doi:10.1016/j.asoc.2018.01.037
  • Ramli, M. A., Jayaraman, V., Kwek, H. C., Tan, K. H., Khoon, G. L., & Monterola, C. (2018). Improved estimation of commuter waiting times using headway and commuter boarding information. Physica A: Statistical Mechanics and Its Applications, 501, 217-226. doi:10.1016/j.physa.2017.12.022
  • Presbitero, A., & Monterola, C. (2018). Challenging the evolution of social cooperation in a community governed by central control. Physica A: Statistical Mechanics and Its Applications, 511, 378-388. doi:10.1016/j.physa.2018.08.008
  • Ma, S., Feng, L., Monterola, C. P., & Lai, C. H. (2017). Importance of small-degree nodes in assortative networks with degree-weight correlations. Physical Review E, 96(4). doi:10.1103/physreve.96.042308
  • Valenzuela, J., Monterola, C. T., Tong, V., Ng, T., & Larbi, A. (2017). Health and disease phenotyping in old age using a cluster network analysis. Nature Scientific Reports. doi:https://www.nature.com/articles/s41598-017-15753-3
  • Legara, E. F., & Monterola, C. P. (2017). Inferring passenger types from commuter eigentravel matrices. Transportmetrica B: Transport Dynamics, 6(3), 230-250. doi:10.1080/21680566.2017.1291377

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