My research expertise is in computational mechanics, materials modeling & design, and machine learning. In my master's study at NTU, I worked on problems in the area of solid mechanics, structural dynamics, and signal processing. In my Ph.D. study at MIT, I focused on understanding the mechanics of deformation and failure of materials at the atomic level. More specifically, I investigated the structure-property relationships of various types of nanomaterials and biomaterials using atomistic modeling tools including molecular dynamics (MD) and density functional theory (DFT).


In 2016, I was deeply inspired by the success of Google DeepMind's AlphaGo program and started to develop machine learning approaches for solving computational mechanics problems. I have published 5 peer-reviewed papers on materials discovery and design using machine learning. I envision that rapid advances in machine learning and artificial intelligence will help solve inverse design problems as well as reduce the computational cost of multiscale modeling and overcome its time-scale and length-scale barriers.


I greatly appreciate the financial support that I have received for my study and research. For my Ph.D. study at MIT, I received financial support via a fellowship from the Taiwanese Government and funding from CRP Henri Tudor in the framework of the BioNanotechnology project. For my postdoctoral training at MIT, I received research funding from the Office of Naval Research (ONR) and the Multidisciplinary University Research Initiative (MURI). For my postdoctoral training at UC Berkeley, I was fully funded by the Department of Mechanical Engineering at UC Berkeley.

May 23, 2014

Abstract: Eumelanin is a ubiquitous biological pigment, and the origin of its broadband absorption spectrum has long been a topic of scientific debate. Here, we report a first-principles computational investigation to explain its broadband absorption feature. These computations are complemented by experimental results showing a broadening of the absorption spectra of dopamine solutions upon their oxidation. We consider a variety of eumelanin molecular structures supported by experiments or theoretical studies, and calculate the absorption spectra with proper account of the excitonic couplings based on the Frenkel exciton model. The interplay of geometric order and disorder of eumelanin aggregate structures broadens the absorption spectrum and gives rise to a relative enhancement of absorpt...

Please reload

© 2017 by Chun-Teh Chen

  • LinkedIn Social Icon