Academic Profile

Academic Profile

Assoc Prof Cheong Siew Ann

Associate Professor, School of Physical & Mathematical Sciences - Division of Physics & Applied Physics
Associate Professor, Complexity Institute
Assistant Chair (Academic), School of Physical and Mathematical Sciences (SPMS)
Deputy Director, Complexity Institute (CI)

Assoc Prof Cheong Siew Ann

Asst Prof CHEONG Siew Ann joined the Division of Physics and Applied Physics, School of Physical and Mathematical Sciences in August 2007. He received his B.Sc.(Hons) in physics from the National University of Singapore, M.Sc.'s from the National University of Singapore and Cornell University, and his Ph.D. from Cornell University. Prior to joining Nanyang Technological University, he was a postdoctoral associate at the Cornell Theory Center. He is a member of the American Physical Society and the Society for Industrial and Applied Mathematics.
Research Interests
Asst Prof CHEONG Siew Ann's areas of expertise are in computational physics, complex system dynamics, and bioinformatics. He is currently working on the development of self-consistent stochastic boundary conditions for ab initio and molecular dynamics simulations, methods to accelerate Monte Carlo simulations and high-dimensional optimization. He is also interested in developing automatic coarse-graining algorithms to perform data-driven identification of effective degrees of freedom in financial markets, very-large-scale computer simulations. He is also working on applying ideas from the Renormalization Group in statistical physics to the mining of very-large-scale databases.
Current Projects
  • Accelerating the Knowledge Turn from Graphene Research to Innovative Technology
  • Agent-Based Housing Market Models to Inform Singapore Housing Policies
  • Augmenting Bing Search through Automatic Narratives in the Interactive Global Histories
  • Data Consolidation for Interactive Global Histories (1205-1533) within the NTU National and International Research Network: Towards an NTU Interdisciplinary Laboratory for Data-Driven Agent-Based Modelling and Simulations for Historical Sciences.
  • Developing and Applying Stochastic Boundary Conditions to Molecular Dynamics Simulations
  • Diffusion and Activation of Dopants and Impurities in InGaAs
  • Diffusion and Activation of Dopants and Impurities in InGaAs
  • Maritime Silk Road. Past, Present and Future. A projection mapping concept design project
  • Modelling Levels of Consciousness for Language Development in Infants
  • Pricing Financial Instruments by Combining Time Series Segmentation with Sentiment Analysis of Market News
  • Renormalization-Group Computer Integration of Large Multiscale Dynamical Systems
  • Self-Consistent Stochastic Boundary Conditions in the Computer Simulation of Infinitely Large Systems
  • Youth Delinquency and Violence in Singapore: A Data-Driven Simulation Study
Selected Publications
  • Tsung-Wen Yen, Mikhail Filippov, and Siew Ann Cheong.(2019). Network Theory and Agent-Based Modeling in Economics and Finance. In Anindya S. Chakrabarti • Lukáš Pichl • Taisei Kaizoji(Ed), Network Theory and Agent-Based Modeling in Economics and Finance(pp. 227-246). Springer Nature.
  • NANETTI, A. and CHEONG, S. A. (2019). Proceedings of Yonsei University and NTU Singapore Joint Faculty Symposium on “Humanities in Society” (Singapore, NTU, School of Humanities, 11-13 January 2018): 전산 연사학: 빅 데이터에서 빅 시뮬레이션까지 [Computational History: From Big Data to Big Simulations]. Humanities in Society (pp. 131-175)서울 [Seoul, South Korea]: 연세대학교 [Yonsei University Press].
  • NANETTI, A. and CHEONG, S.A.(2018). Computational History: From Big Data to Big Simulations. Shu-Heng CHEN (Ed.), Big Data in Computational Social Science and Humanities, Springer Series on “Computational Social Sciences”(337-363). Cham (Switzerland): Springer International Publishing AG.
  • Woon Peng Goh; Kang Kwong Luke; Siew Ann Cheong. (2018). Functional shortcuts in language co-occurrence networks. PLoS ONE, 13(9), 1-18.
  • Liu W.Y, A. Nanetti, S.A. Cheong. (2017). Knowledge Evolution in Physics Research: An Analysis of Bibliographic Coupling Networks. PLoS ONE, 12(9), e0184821.

« Back to Category Write-up