Chi-Ta Yang

Experience

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  Ministry of National Defense, Taiwan

  Oct 2005 - Jan 2007

  Army Reserve Corporal

  • Encouraged and effectively communicated with soldiers of different personalities; Led 30 soldiers to complete various tasks; Organization of the supply of military staffs in a battalion.

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  Lam Research

  Jan 2008 - Nov 2008

  Field Process Engineer

  • Co-worked with customers to tackle productivity issues (process shooting) and for the recipe tuning of 40/45nm production application; Developed mutual trust and clear/quick communications with customers to work efficiently (laid off due to economic recession).

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  University of South Florida

  Aug 2010 - May 2015

  Research/Teaching Assistant

  • Utilized DFT to evaluate “subnano cluster/TiO2“ catalyst for CO2 adsorption, offering design guidelines for better materials: developed cluster binding mechanism to assist experimental characterization, proposed indicator for catalysis phenomena (sintering), proposed cluster encapsulation pathway using NEB method.• NSF Proposal developing/writing entitled “Plasmon Enhanced Photocatalytic Reduction of CO2 to Produce Hydrocarbon Fuels”.

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  The University of Iowa

  Oct 2015 - Jun 2016

  Postdoctoral Research Fellow

  Postdoctoral Research – Cathode materials, aqueous phase DFT modeling (Explicit & Implicit methods), Ab Initio thermodynamics • Developed a computational plan to correlate and explain the experiment observations, and started up NMC model building. Building explicit water models of LiCoO2 and NMC to incorporate water effects. • Using Ab Initio approaches to explain the incongruent metal dissolution of NMC in aqueous environment. • Molecular level investigation of phosphate ions adsorption on LiCoO2 using self-consistent continuum solvation calculation. Show less

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  The Ohio State University

  Sept 2016 - Aug 2018

  Postdoctoral Researcher

  Nanoporous materials (MOF and Zeolite), Alkane Cracking, CO2 capture and storage, Gas Separation, Fortran/BASH/Matlab, ab initio calculations (DFT), Monte Carlo, Molecular dynamicsOutcome: 6 publicationsProject 1: Stimulus-responsive MOFs (azo-benzene functionalized, azo-MOFs) as potential materials for CO2 capture and storage using Monte Carlo Simulation and ab initio calculations. • Developed BASH/MATLAB scripts for data manipulation and set up calculations on a daily basis. • Successfully found the root cause behind the experimentally observed CO2 uptake difference in stimulus-responsive MOFs to improve the material design.• Applied Molecular dynamics to study the diffusion of CO2 in stimulus-responsive MOFs to explain the experimental results. • Wrote scientific paper and meeting with collaborator.Project 2: Alkane cracking using Brønsted-acid zeolites is of central importance to the petroleum industry. For the development of novel zeolites for cracking, discovering structures with desirable adsorption and selectivity properties are essential. • Developed BASH/MATLAB/Fortran codes for input file preparations and result analysis.• Studied the effects of Si/Al ratios and Al distributions on adsorption selectivity and gain molecular-level understandings using MC simulations for better material design. • Wrote scientific paper.• Development of an “Entropy estimation algorithm” for large scale screening of potential Brønsted-acid zeolites (~1500 times faster than MC)Project 3: Utilizing the deformation capability of Pillared-bilayer MOF for gas separation. • Set up DFT and MC calculations motivated by experimental results to study the deformation of the Pillared-bilayer MOF in order to explain the experimental XRD results.• Obtaining energy profiles (MC) and diffusion coefficients (MD) to explain the experimental results • Discussing the results with experimental collaborator to guide/suggest experiments. Show less

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  Michigan State University

  Oct 2018 - Sept 2020

  Research Associate

  Li ion battery design, focusing on the interface of Li anode coupled with different SEIs with the goal to mitigate Li dendrite growth so as to prevent short circuit. DFT, KMC, MD simulations as well as FORTRAN/BASH programming. Outcomes: 3 publications• Designed and developed a multiscale modelling approach (DFT & KMC with FORTRAN) to enable the study of a challenge in Li ion battery, void evolution at Li anode/coatings interfaces for Li dendrite mitigation. • Developed an approach to effectively estimate polymer/Li metal adhesion based on DFT and regression.• Used MD to study the 1st solvation shells of liquid electrolytes and successfully explain experimental results. Show less

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  The Ohio State University

  Jan 2021 - Dec 2021

  Postdoctoral Researcher

  • Leveraged machine learning in developing first-principles force field models for molecule adsorption in MOF materials (Regression) using ANN, CNN (LeNet-5 w/o Inception module), RF, SVM, and KNN (Python), 50 times more accurate and 60 times faster than existing methods; Designed features based on physics. (1 publications)• Computer vision (CNN) to successfully identify favorable and unfavorable adsorption configurations; developed python code to transfer atomic structures into 3D grid graphs for computer vision.• Developed ML framework by combining DNN and computer vision (CNN) for regression (mixed image and numerical inputs and multiple outputs). Show less

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  Eaton

  Apr 2022 - now

  Lead Engineer

  1. AI/ML powered Digital Product Design & Industry 4.0 Reduce product design time from “months to days” utilizing workflow Automation, Machine Learning, Algorithm development, Programming, and Optimization. One trade secret & one conference talk.• Lead a project team to achieve goals and management (plan on what to do, next steps…etc)• Developed active learning algorithm to develop high-fidelity ANN models based on FEA simulations• Working with business sector to develop fast and reliable AI/ML powered design workflow combining FEA, ML models, selection algorithm, saving Bellows and Seal design time by ~90% (weeks to hours)• Developed a selection algorithm and python code to smartly select the potential design points.• Worked with business unit to developed a Gear assembly algorithm (Python, 2000 + lines) to verbalize sophisticated engineering experience and enable process automation.2. In-Situ & Ex-Situ Defect Detection utilizing Convolution Neural Network in Additive Manufacturing• Managing external collaborators to achieve project goals. • Technology transfer to bring the research into production benefit; modify codes and develop document for implementation.• Working experiences of Autoencoder, combined Autoencoder & CNN, Dimension Reduction (PCA, UMAP), and Clustering analysis upon 2D and 3D images (Pytorch).I. Surrogate models that predict 2D image upon In-Situ signals II. Surrogate model that predicts 3D image upon Ex-Situ dataIII. Clustering analysis for mechanical properties upon Ex-Situ data• Developed codes for segmentation of CT scan images. 3. Project Development • Develop transferable AI/ML design methodology that incorporates Manufacturing concerns for robust product design. • Less expert involved transferable methodology to automatically update AI/ML product design tools for longevity and On-the-Fly AI/ML design. Show less