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Contact Information

Name Ye Wang
Professional Title Postdoctoral Research Scientist
Email yw4291@cumc.columbia.edu

Professional Summary

I am a postdoctoral research scientist in the laboratory of Prof. Chaolin Zhang at the Irving Medical Center of Columbia University. My long-term research interests involve developing programmable RNA-based therapeutic technologies to correct disease-causing mutations and enable scalable precision medicine for genetic and neurodegenerative disorders. My work is grounded in a learn-from-nature philosophy, drawing inspiration from natural RNA regulatory systems and translating their principles into engineered therapeutic platforms through bio-inspired design and AI-accelerated biological engineering.

Education

  • 2024 - present

    New York, NY

    Postdoctoral Research Scientist
    Columbia University
    Computational and Molecular Biology
    • Laboratory of Prof. Chaolin Zhang, Irving Medical Center
  • 2017 - 2023

    Beijing, China

    Ph.D.
    Tsinghua University
    Control Science and Engineering
  • 2013 - 2017

    Yangling, China

    B.S.
    Northwest A&F University
    Biotechnology

Awards

  • 2025
    Featured Article — Editors' Highlights in Biotechnology and Methods
    Nature Communications
  • 2021
    Youth Outstanding Paper Award
    World Artificial Intelligence Conference (WAIC)
  • 2020
    Breakthrough Article & Cover Paper
    Nucleic Acids Research
  • 2020
    Outstanding Student Scholarship
    Tsinghua University
  • 2014
    National Scholarship
    Ministry of Education of China

Publications

Student Mentorship

  • Matthew Sun (Ph.D. Student, Computer Science) — Columbia University | Jan 2026 – May 2026

    Mentored Matthew on applying machine learning approaches to RNA splice-site usage prediction, focusing on data preprocessing and quantitative modeling to improve splice-site usage quantification, supporting disease-relevant variant interpretation.

  • Luna Segarra Alonzo (Ph.D. Student) — University of Puerto Rico | Jun 2025 – Aug 2025

    Mentored Luna to approach RNA rewriting as a system-level regulatory design problem, emphasizing hypothesis-driven modeling, modular system architecture, and rigorous mechanistic validation. Resulted in a presentation at the Puerto Rico Neuroscience Conference.

  • Shiwei Liu (Ph.D. Student) — Tsinghua University | Feb 2020 – Aug 2020

    Guided Shiwei to model the encoding system as a layered architecture integrating constraint-aware encoding, probabilistic noise modeling, and fuzzy retrieval algorithms, enabling tolerant matching and error-resilient addressing. Advanced into a peer-reviewed publication: Biochemical Constraint Compatible Address Design for Fuzzy Retrieval of Images in DNA Storage (CAC 2020, IEEE).

  • Lekang Yuan (Ph.D. Student) — Tsinghua University | Aug 2019 – Aug 2020

    Guided Lekang to design computational pipelines combining probabilistic modeling and data-driven error learning. Served as team leader of the Tsinghua-A iGEM 2020 DNA storage project (Bronze Medal), leading to patent CN114023374B.

Skills

AI-guided Design: Generative AI for biological sequences (diffusion, flow matching), large-scale DNA/RNA sequence generation, RNA-seq and splicing analysis, sQTL analysis and variant effect modeling
Statistical & Computational Analysis: Bayesian inference and sampling, RNA-seq analysis, statistical modeling, Python, R
Molecular Biology: PCR, RT-qPCR, cloning, DNA/RNA extraction, Western blotting
Cell-based Techniques: Cell viability assays, transfection, CRISPR, cell sorting, confocal microscopy
High-Throughput Screening: Design and implementation of large-scale screening assays for sequence-to-function mapping