A versatile AI Engineer/Computational Biologist/Data Scientist with hands-on experience in multiple biosciences industries and proficient with several programming languages. Passionate about solving real-life problems with appropriate models. Collaborative and responsive with the ability to grasp new concepts quickly.


Programming languages

  • Python
  • R
  • Linux

Machine learning packages

  • Pytorch
  • JAX
  • Keras

Machine learning models

  • Recurrent neural network
  • Convolutional neural network
  • Graph neural network
  • Markov chain
  • Conventional machine learning models

Work Experience (4)

Data Scientist II/Investigator I
Novartis Institutes for BioMedical Research (NIBR)
2020 - Current
Cambridge, MA

Utilize deep learning, statistical modeling, and software engineering on biologics data to make impact on science and decision making.

Machine learning scientist/Computational biologist
Kintai Therapeutics
2020 - 2020
Cambridge, MA

Provided high-level recommendations to enhance R&D data utilization and prioritized biomarkers nomination by designing and executing appropriate machine learning models on demand.

  • The only hire in the whole company for designing and executing machine learning methods for scientific research.

  • Collaborated with the omics team to interrogate machine learning model output to deliver high value readouts.

  • Upgraded current in-house bioinformatics workflow by comparing and integrating several popular methods.

Machine learning engineer intern
2019 - 2019
Cambridge, MA

Worked with a group of machine learning scientists and software engineers to enhance a deep learning pipeline

  • Reduced errors from time series prediction by proposing and implementing a working deep learning (LSTM) model.

  • Contributed a variety of functions to the company‚Äôs deep learning code base through Git and improved the performance of a vital deep neural network.

  • Identified the potential performance weaknesses of the current deep neural network in production, developed a concrete quality control framework for identifying results with high predictive error.

  • Made an entertaining Slack bot using Markov Chain to impersonate colleagues during a hackathon.

Statistical genetics intern
2018 - 2018
Cambridge, MA

Performed all kinds of computational analysis to support publications and internal drug discovery. Supported research decision making by making statistical model comparisons.

  • Applied various statistical modeling techniques on human high dimensional genomic data. Increased the productivity of research by developing an efficient HLA analysis pipeline, a linear mixed effect model pipeline and a data visualization pipeline.

  • Contributed to several potential publications by helping collaborators and providing key results.

Education (4)

Genetics and Genomics
Boston University
2015 - 2019
Pharmacology and Experimental Therapeutics
Tufts University
2013 - 2015
Summer scholar
University of California, Los Angeles (UCLA)
2012 - 2012
West China School of Pharmaceutical Science
Sichuan University
2009 - 2013



Career mentor
Mass General Hospital Postdoc Association (MGPA)
2020 - 2021

Participated in a mentoring program to help postdocs who are interested in a career in the industry by providing career advising and networking. Meet (virtually) with mentees on a monthly basis to share knowledge, support, and encouragement with the goal of advancing their careers.

New England Science Symposium(NESS) staff
Harvard Medical School
2016 - 2018

Worked with plenary committee for symposium abstract reviewing and screening, driven by the passion for creating a better scientific community for the minority groups. Contributed to the success of symposium by facilitating registration and providing information for attendees.

Volunteer at The Maxwell & Eleanor Blum Patient and Family Learning Center,
Dana-Farber Cancer Institute
2014 - 2015

Assisted patients and families with computer searches, made appropriate referrals to Boston Children's Hospital, Dana-Farber, and Brigham and Women's Hospital departments, and helped locating desired resources.



Native speaker