Experience

VantAI

• United States
• Biotechnology
• 1 - 100 Employee

• Senior Principal Scientist, Head of Computational Chemistry

  • Apr 2021 - Present

  New York City Metropolitan Area • Leading R&D of a Computational Chemistry team • Structural-based modeling of target protein degradation (TPD) systems • Generating structural and cheminformatic data for AI-based models that predict protein-ligand affinities • Managing several drug-discovery projects with contracting clients, and providing computational chemistry support, including virtual screening, enhanced sampling, free-energy calculations, etc.

• Computational Chemist

  • Feb 2020 - Apr 2021

  New York City Metropolitan Area • Taking both AI and physic-based approaches for drug-target interaction, toxicity prediction, and drug repurposing. • Team-working with computational biologist, machine learning engineers, and data analysts



University of California, Riverside

• United States
• Higher Education
• 700 & Above Employee

• Postdoctoral Researcher

  • Sep 2018 - Jan 2020

  Riverside, CA • Applying an information maximizing variational auto-encoder(InfoVAE) to create artificial protein folding trajectories from a continuous latent space. • Investigating thermodynamics and kinetics of protein-ligand association/dissociation using a novel free energy algorithm - Milestoning Method. This powerful algorithm provides both free energy profile and rate constant of ligand binding/unbinding simultaneously. • Using unsupervised learning algorithms, e.g. PCA, ICA, Isomap, t-SNE, and… Show more • Applying an information maximizing variational auto-encoder(InfoVAE) to create artificial protein folding trajectories from a continuous latent space. • Investigating thermodynamics and kinetics of protein-ligand association/dissociation using a novel free energy algorithm - Milestoning Method. This powerful algorithm provides both free energy profile and rate constant of ligand binding/unbinding simultaneously. • Using unsupervised learning algorithms, e.g. PCA, ICA, Isomap, t-SNE, and autoencoder to reduce the dimensionality of all-atomic simulation trajectories (typically 1000 - 10,000 original dimensions). • Constructed QSAR and calssification prediction model for pharmacore search and ranking (Random Forest and Navie Bayes). • Clustering (K-means and DBSCAN) millions of protein structures using important features at the active pocket, including residue RMSD, Cartesian coordinates, or principal components. • Used SVM to extract the most dissimilar motions of an enzyme before and after binding by an inhibitor. Show less



The Ohio State University

• United States
• Higher Education
• 700 & Above Employee

• Graduate Teaching Associate

  • Sep 2012 - Aug 2018

  Columbus, Ohio Area • 2+ years of TA in graduate-level statistical thermodynamics, advanced quantum mechanics, and molecular dynamics simulations. • Wrote several tutorials and scripts for running simulations on supercomputers. • 2 years of TA in undergraduate physical chemistry • 1+ years of TA in general chemistry laboratory • Instructed and supervised 100+ undergraduates' lab skills and safety • Mentor of Ohio supercomputer center summer camp for high school students.

• Graduate Research Associate

  • Aug 2012 - Aug 2018

  Columbus, Ohio Area • Built Molecular Dynamics (MD) simulations on fluidics in nanopores, peptide adsorption on silica nanoparticles, and surface potential at interfaces. • Developed C++ programs to calculate second harmonic generation (SHG) signals at MD trajectories. • Implanted OpenMP and CUDA to in-house programs to achieve high-performance computing on supercomputers. • Performed nonlinear regression to partial differential equations, e.g. Poisson-Boltzmann, Navier-Stokes using Mathematica, Matlab… Show more • Built Molecular Dynamics (MD) simulations on fluidics in nanopores, peptide adsorption on silica nanoparticles, and surface potential at interfaces. • Developed C++ programs to calculate second harmonic generation (SHG) signals at MD trajectories. • Implanted OpenMP and CUDA to in-house programs to achieve high-performance computing on supercomputers. • Performed nonlinear regression to partial differential equations, e.g. Poisson-Boltzmann, Navier-Stokes using Mathematica, Matlab, and Python (numpy).



National Taiwan University

• Taiwan
• Higher Education
• 700 & Above Employee

• Research Assistant

  • Aug 2010 - Oct 2011

  Taipei City, Taiwan • Developed a nanoparticle-based biosensor to detect enzymatic activity of phospholipase A2 (PLA2). • Invented a protocol to synthesized lipid bilayer coated nanoparticles, with high stability in salted environments.



National Tsing Hua University

• Taiwan
• Research Services
• 700 & Above Employee

• Graduate Research Assistant

  • Aug 2007 - Oct 2010

  Hsinchu County/City, Taiwan • Invented a Surface-Enhanced Raman Scattering (SERS) nanoprobe, which amplifies the Raman scattering signals of naphthalenethiol molecules by 3 orders. • Cooperated with colleagues in National Central University in fabricating 2D waveguide as multiple spots sensor chips. • Performed nanoparticle characterizations using size exclusion chromatography (SEC), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and dynamic light scattering (DLS).