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Associate Professor

Ho Ki FUNG

Associate Professor
PhD (Chemical Engineering), Princeton University, United States
Cluster:
Food, Chemical and Biotechnology
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SIT Appointments

  • Associate Professor
    – Present
  • Deputy Programme Director, SIT BEng (Hons) Pharmaceutical Engineering
    –
  • Assistant Professor
    –

Education

  • PhD (Chemical Engineering)
    Princeton University , United States
  • Master of Philosophy (Bio-engineering)
    Hong Kong University of Science & Technology , Hong Kong SAR China
  • Master of Science (Chemical Engineering)
    Hong Kong University of Science & Technology , Hong Kong SAR China
  • Bachelor of Science (Chemical Engineering)
    University of California, Berkeley , United States

Achievements

  • Singapore Food Story R&D Programme Industry Alignment Fund Pre-Positioning (IAF-PP) – Advanced Biotech-Based Protein Production (Co-PI)
    –
  • Academic Supervisor of Industrial Masters Thesis Project (with SATS Catering Pte Ltd.)
    –
  • SIT Ignition and Innovation Grant
    –

Professional Memberships

  • Exco member (faculty advisor) of the International Society for Pharmaceutical Engineering (ISPE) Singapore Affiliate

Corporate Experience

  • Procter & Gamble Far East Inc. (Japan)
  • He-Ro Chemicals Ltd. (Hong Kong)

Research Interests

  • Computational Peptide and Protein Design
  • Process Modeling, Simulation and Optimisation
  • Data analytics and Machine Learning

Journal Papers

  • Zhang, L., Fung, K. Y., Zhang, X., Fung, H. K., and K. M. Ng. An integrated framework for designing formulated products. Comput. Chem. Eng., 107: 61-76 (2017). (2017 Best Paper Award)

  • Pan, S. J., Cheung, W. L., Fung, H. K., Floudas, C. A., and A. J. Link. Computational design of functional variants of the antimicrobial peptide microcin j25. Protein Eng. Des. Sel., 24:275-282 (2011).

  • Bellows, M. L., Taylor, M. S., Cole, P. A., Shen, L., Siliciano, R. F., Fung, H. K., and C. A. Floudas. Discovery of entry inhibitors for HIV-1 via a novel de novo protein design framework. Biophys. J., 99:3445-3453 (2010).

  • Bellows, M. L., Fung, H. K., Taylor, M. S., Floudas, C. A., Lopez de Victoria, A., and D. Morikis. New compstatin variants through two de novo protein design frameworks. Biophys. J., 98:2337-2346 (2010).

  • Fung, H. K., Floudas, C. A., Taylor, M. S., Zhang, L., and D. Morikis. Toward full-sequence de novo protein design with flexible templates for human beta-defensin-2. Biophys. J., 94:584-599 (2008).

  • Taylor, M. S., Fung, H. K., Rajgaria, R., Filizola, M., Weinsein, H., and C. A. Floudas. Mutations affecting the oligomerization interface of G-protein-coupled receptors revealed by a novel de novo protein design framework. Biophys. J., 94:2470-2481 (2008).

  • Fung, H. K., and C. A. Floudas. Computational de novo peptide and protein design: rigid templates versus flexible templates. Ind. Eng. Chem. Res., 47:993-1001 (2008).

  • Fung, H. K., Taylor, M. S., and C. A. Floudas. Novel formulations for the sequence selection problem in de novo protein design with flexible templates. Optim. Methods & Software, 22:51-71(2007).

  • Floudas, C. A., Fung, H. K., McAllister, S. R., Mönnigmann, M., and R. Rajgaria. Advances in protein structure prediction and de novo protein design: a review. Chem. Eng. Sci., 61:966-988 (2006).

  • Fung, H. K., Rao, S., Floudas, C. A., Prokopyev, O., Pardalos, P. M., and F. Rendl. Computational comparison studies of quadratic assignment like formulations for the in silico sequence selection problem in de novo protein design. J. Comb. Optim., 10:41-60 (2005).

Books

  • Bellows, M. L., Fung, H. K., and C. A. Floudas. Recent Advances In De Novo Protein Design. In Process Systems Engineering Vol. 6 Molecular Systems Engineering; Adjiman, C. S., Galindo, A., Eds.; Wiley-VCH, pp 207-232 (2010).

  • Fung, H. K., Wibowo, C., and K. M. Ng. Product-centered process synthesis and development: detergents. In Chemical Product Design: Towards a Perspective through Case Studies. K.M. Ng, R. Gani, and K. Dam-Johansen, Eds.; Elsevier (2007).

  • Floudas, C. A., Fung, H. K., Morikis, D., Taylor, M. S., and L. Zhang. Overcoming the Key Challenges in De Novo Protein Design: Enhancing Computational Efficiency and Incorporating True Backbone Flexibility. In BIOMAT 2006: International Symposium on Mathematical and Computational Biology; Mondaini, R. P., Ed.; Springer, pp 133-183 (2007).

  • Floudas, C. A., and H. K. Fung. Mathematical Modeling and Optimization Methods for De Novo Protein Design. In Systems Biology; Rigoutsos, I., Stephanopoulos, G., Eds.; Oxford University Press, pp 42-66 (2007).

Teaching Modules

Pharmaceutical Engineering, BEng (Hons)

  • PHE1012 - Statistics
  • PHE1021 - Engineering Mathematics II