Tianyu Huang

Integrated DEsign Automation Laboratory (IDEAL)
Department of Mechanical Engineering
Robert R. McCormick School of Engineering and Applied Science
Northwestern University

Office: AG10 Technological Institute
Email: thuang@u.northwestern.edu

I am a fourth year Ph.D. student advised by Prof. Wei Chen at Northwestern University. My study includes the applications of statistical machine/deep learning algorithms in the mathematical modeling process for engineering design and uncertainty quantification/propagation associated with these models. I am also pursuing a Master of Science in Statistics degree en route to my Ph.D.

Education

Ph.D. Mechanical Engineering, Northwestern University, expected 2020
M.S. Statistics, Northwestern University, expected 2020
M.S. Mechanical Engineering, Northwestern University, 2016
B.S. Materials Science and Engineering, Shanghai Jiao Tong University, China, 2015
B.A. Journalism and Communications, Shanghai Jiao Tong University, China, 2015

Research interests

Random process modeling
Machine/deep learning with application in engineering
Uncertainty quantification and propagation

Industry experience

Research and Innovation Center, Ford Motor Company, Dearborn, MI (July - September, 2018)

Curriculum

Applied statistics, random processes, optimization, machine/deep learning

Projects

Awards

2017 - 2018 Predictive Science & Engineering Design Interdisciplinary Cluster Fellowship

Teaching

2017 ME441 Engineering Optimization (TA, 1 quarter)
2016 ME220 Thermodynamics (grader, 2 quarters)
2015 ME220 Thermodynamics (grader, 1 quarter)
2015 ME340-1 Manufacturing Processes (grader, 1 quarter)

Presentations

Tianyu Huang, Hongyi Xu and Wei Chen, “Microstructure Reconstruction of Sheet Molding Composite Using a Random Chips Packing Algorithm,” WCX17: SAE World Congress Experience, April 6th, 2017, Detroit, US.

Publications

Hansoge, N. K., Huang, T., Sinko, R., Xia, W., Chen, W., & Keten, S. (2018). Materials by Design for Stiff and Tough Hairy Nanoparticle Assemblies. ACS nano. [site]

Chen, Z., Huang, T.(co-first author), Shao, Y., Li, Y., Xu, H., Avery, K., Zeng, D., Chen, W., Su, X. (2017). Multiscale Finite Element Modeling of Sheet Molding Compound (SMC) Composite Structure based on Stochastic Mesostructure Reconstruction. Composite Structures. [site]

Chen, Z., Li, Y., Shao, Y., Huang, T., Xu, H., Li, Y., … & Su, X. (2017). A Comparative Study of Two RVE Modelling Methods for Chopped Carbon Fiber SMC. SAE Technical Paper.(No. 2017-01-0224) [site] [pdf]

Huang, T. Y., Fan, L. W., Bao, Y. N., Shi, H., & Zhang, K. (2015). Multi-pass Route Planning for Thick Steel Plate Using Laser Welding with Filler Wire. In Robotic Welding, Intelligence and Automation (pp. 551-560). Springer International Publishing. [site]

Shi, H., Zhang, K., Xu, Z., Huang, T., Fan, L., & Bao, W. (2014). Applying statistical models optimize the process of multi-pass narrow-gap laser welding with filler wire. The International Journal of Advanced Manufacturing Technology, 75(1-4), 279-291. [site]

My LinkedIn
Lab website