Skills

Computational Chemistry/Biology, Bioinformatics, Chemical Engineering, Battery Reaction Simulation, Theoretical Neuroscience, NGS, Gene Editing(e.g CRISPR), Organic Synthesis, Physical Chemistry, Protein Kinetic, Pharmacokinetics, Analytical Chemistry, Data Engineering, Machine Learning, Computer Vision, Statistics, Pattern/Academic Writing.

Programming: Python, SQL, Matlab, R, Git/GitHub, Linux, Tensorflow, AWS

Scientific Data Analysis: Schrödinger, PyMol, IGOR, Gaussian, GROMACs, RDkit, Prism, Imaris, Zeiss

Language: English, Mandarin, German

Experience

Computational/AI:

Research Scientist II, Bioinformatics Charles River Laboratory, South San Francisco, CA (2022-Present)

  • Developed and deployed generative AI models to construct novel VHH immune libraries, preserving native antibody conformations.

  • Built MySQL database on AWS containing over 100 antibody discovery sequences, with search interfaces for rapid data queries.

  • Automated Sanger sequencing and NGS analysis workflows using Python and R, enabling efficient sequence data processing for client projects. Used Tumbler and 3D structure visualization platform to support client programs.

AI Intern, InterX Inc, San Francisco (2021-Present)

  • Wrote molecular alignment code for RDkit generated data and using python and pacpype.

  • Conducted computer-aided drug discovery project: large scale molecular screening and docking target on protein kinase. Experienced in docking software such as Schrodinger and pyMOL.

  • Create monthly reports/presentations to communicate insights between company's groups. Edited the ForceField paper published in Nature Communication.

  • Designed and maintained company's research website.

AI Researcher, Deepwise Healthcare, Beijing (2019-2020)

  • Built universal lesion detection MP3D FPN from CT slice for comprehensive disease screening. Achieved state-of-the-art detection performance on the DeepLesion dataset (3.48% absolute improvement in the sensitivity of FPs@0.5). The result was published in MICCAI2020(Medical Image Computing and Computer Assisted Intervention).

  • Facilitated the design of Bipartite graph node mapping in mammogram mass detection. Performance on DDSM dataset(%): 95@4.4, 92@1.9, 89@1.2. The result was published in CVPR2020)Computer Vision and Pattern Recognition).

  • Assisted a client with MCMC Bayesian parameter estimation using PyMC and corresponding visualizations for experimental chemistry and clinical function data.

Data Analyst, IQVIA, Taipei (Contractor) (2017-2020)

  • Experienced in analyzing large-scale unstructured/unlabeled data: analyzed drug’s clinical performance through 1000+ doctors’ reports through statistical methods (SPSS and SQL).

  • Provided clients with go-to-market insights by performing data cleaning, exploratory analysis, and PCA with clustering. (companies include Johnson & Johnson, Pfizer, Sanofi, and many more.)

  • In charge of Simultaneous Interpreting in a medical conference. Edited document translations across global branches (English/Mandarin).

Neuroscience/Chemistry:

Graduate Researcher, Dr.Yang’s Group, USF, San Francisco (2020-2022)

  • Designed and executed experiments to define and test hypotheses for cell transport mechanisms for potential drug targeting. Mastered transmembrane protein purification and quantification using FPLC with UV detectors.

  • Discovered potential new ABC transportation mechanism through Anisotropy and ATP Assay. The result was published in ASBMB2022. Currently working on following up publication (grant from NIH).

  • Received Teaching&Research Scholarship for 2 years. Assisted 20+ university-level students in learning topics in general&bio-chemistry.

Graduate Researcher, Yi’s Group, Tsinghua University, Beijing (2016-2019)

  • Investigated protein interactions with the statistical Markov model (HMM). Trained and validated with 4,000+ data published since 2000 with 85% accuracy. Performed simulation and data analysis with Python, MATLAB, and R.

  • Inspected forgetting pathway and expert in the following research techniques: NGS, Brain Imaging, Virus Infections, Immunohistochemistry, Western blot, iDisco, Gene Sequencing, and Confocal Microscope Operation.

  • Designed and conducted animal paradigms in emotions and memory formation experiments.

  • Constructed neural circuits and neural computation models in drosophila/mice for early drug screening, especially in neurogenesis and CNS disorder profiles.

  • Associate project: Reduced smoothed level rescues A-β-induced memory deficits and neuronal inflammation animal models of Alzheimer’s disease. (Immunohistochemistry)

  • Improved documentation and training for lab protocols, and maintained the internal lab wiki and Unix server.

Battery Engineer, Audi China, Beijing (Internship) (2017-2019)

This is an internship in Tsinghua University Student Formula E.

  • Managed performance, lifecycle and specialty battery testing programs.

  • Assembled high voltage battery packs and managed battery simulation using ANSYS. Used air-cooling system for thermal management

  • Built battery model and parameterize equivalent circuit that reflects the battery’s behavior on temperature, SOC, SOH, and current with Simulink.

Educations/Certificates

//Educations:

Micro M.S. in Data Science, Massachusetts Institute of Technology, EdX (2021-2022)

M.S. in Chemistry, University of San Francisco, San Francisco (2020- 2022) 3.7/4.0 GPA

M.S. in Neuroscience, Tsinghua University, Beijing (2016-2019) 3.8/4.0 GPA

B.S. in Agricultural Chemistry, National Taiwan University, Taipei (2012-2016) 3.5/4.3 GPA

//Certificate:

Publication/Conference/Award

Chen, Y.C., Yang, J. (2022, April). Mechanisms of Substrate Selectivity and Transport by a Bacterial Methionine ABC Importer. American Society for Biochemistry and Molecular Biology, Philadelphia, NY. [paper]

Zhang, S., Xu, J., Chen, Y. C., Ma, J., Li, Z., Wang, Y., & Yu, Y. (2020, October). Revisiting 3D context modeling with supervised pre-training for universal lesion detection in CT slices. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 542-551). Springer, Cham. [Third Author, paper]

Chemical Engineering/Biochemistry Student Award, 2022, The American Institute of Chemists