About me

Hi, I’m Yist! I am a PhD student at École polytechnique fédérale de Lausanne (EPFL), working on machine learning and computational biology. I received EDIC fellowship and am advised by Prof. Maria Brbić at the MLBio lab. My research focuses on advancing AI models for single-cell analysis (gene expression profiles, multi-omics data, and spatial transcriptomics) while developing biology-inspired models that can contribute to the broader ML community.

Before moving to Switzerland, I earned my Bachelor of Science degree with First Class Honors from the Chinese University of Hong Kong, majoring in Mathematics and Information Engineering.

I dedicate 2-3 hours weekly to mentoring female students in my fields. If you'd like someone to discuss your project or future academic plans with, feel free to reach out. TOGETHER WE RISE!

Download CV here (Last update: Oct. 2024)

News

  • October 2024:: Began my role as Vice President for Women+ in IC at EPFL! Join us and feel free to reach out if you have ideas on how we can better promote women’s presence in our community!
  • September 2024: Excited to present our work, LUNA, at the EcoCloud Annual Event in Lausanne, the Human Cell Atlas General Meeting 2024 in Milan, and Single Cell Genomics 2024 in Greece! Stay tuned—our preprint is coming soon.
  • August 2024: Co-organizing the AIDrugX workshop at NeurIPS 2024. Check out our website and submit your work!
  • July 2024: The abstract of our work LUNA was accepted as a poster at Single Cell Genomics 2024. See you in Greece!
  • July 2024: Successfully passed my candidacy exam on July 5th! Officially a PhD candidate—exciting times ahead!
  • May 2024: Thrilled to announce that two of our papers were accepted at ICML 2024!

Research Interests

Curiosity is the driving force behind my research, and the opportunity to collaborate with exceptional people is what fuels it even further! I am particularly curious about the following topics:

  1. Cellular world—how single cells function, communicate, differentiate, teach, learn, and come together to form living organisms.
  2. Graphs and randomness.
  3. Non-human-centered research: benefit nature and wildlife, like social animal behavior and protecting natural habitats.
  4. Intersection of machine learning and classical information/coding theories.

Research Experience

Prior to joining EPFL, I worked closely with Professor Sidharth Jaggi, Professor Li Yu, Professor Ma Shiqian, and Professor Irwin King. I was also fortunate to receive invaluable guidance from Professor Chandra Nair, the director of my program.