Yang C.-H. Huck


Georgia Institute of Technology


Research Interests

​C.-H. Huck Yang is a visiting student from Georgia Institute of Technology. He is doing dynamic generative model research with machine learning techniques in Living Systems Laboratory. His interests focus on Statistical Machine Learning and its application.

Selected Publications

  • Controllability, multiplexing, and transfer learning in networks using evolutionary learning
    R. Ooi, C.-H. Huck Yang, P.-Y. Chen, V. Eguiluz, N. Kiani, H. Zenil, D. Gomez-Cabrero, J. Tegner
    arXiv, 2018
  • Synthesizing new retinal symptom images by multiple generative models
    Y.-C. Liu, H.-H. Yang, C.-H. Huck Yang, J.-H. Huang, M. Tian, H. Morikawa, J. Tegner
    ACCV Workshop of AI in Retina Image Analysis, 2018
  • Auto-classification of retinal diseases in the limit of sparse data using a two-streams machine learning model
    C.-H. Huck Yang, F. Liu, J.-H. Huang, M. Tian, H. Morikawa, I-H. Lin M.D., Y.C. Liu, H.-H. Yang, J. Tegner
    ACCV Workshop of AI in Retina Image Analysis, 2018
  • A novel hybrid machine learning model for auto-classification of retinal diseases
    Yang, C.-H. H.; Huang, J.-H.; Liu, F.; Chiu, F.-Y.; Gao, M.; Lyu,W.; Tegner, J.; et al.
    ICML Workshop of Computational Biology, 2018
  • Learning functions in large networks requires modularity and produces multi-agent dynamics
    C.H.H. Yang, R. Ooi, T. Hiscock, V. Eguiluz, J. Tegner
    ICML Workshop of Computational Biology, 2018
  • Vertically aligned carbon nanotubes forest based flexible strain sensor for Internet of Things applications
    C.H. Yang, C.C. Su, K.P. Hsieh, Y.R. Li, K.Y. Yeh and S.H. Chang
    19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS), Kaohsiung, pp. 1360-1363, 2017
  • A microfluidic device integrating dual CMOS polysilicon nanowire sensors for on-chip whole blood processing and simultaneous detection of multiple analytes
    D.-H. Kuan, I-S. Wang, J.-R. Lin, C.-H. Yang, C.-H. Huang, Y.-H. Lin, C.-T. Lina and N.-T. Huang
    Lab Chip., 3105-13, 2016​


  • ​M.Sc., Electrical and Computer Engineering, Georgia Institute of Technology, 2017-present
  • B.Sc., Engineering Science, National Taiwan University, 2016

Professional Profile

  • ​ 2016: ExchangeStudent, North Carolina State University, Raleigh, NC, U.S.A. 

Scientific and Professional Membership

  • IEEE student member


  • ​Wallace H. Coulter Scholarship 2017-2018

KAUST Affiliations

  • ​KAUST Environmental Epigenetics Program (KEEP)
  • Biological and Environmental Sciences and Engineering (BESE)

Non-KAUST Affiliations

Research Interests Keywords

Machine learning Bioscience Engineering

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