Dabin Jeong

Dabin Jeong

Senior Data Scientist · Lotfollahi Lab

About me

I am an AI for Life Science researcher at the Lotfollahi Lab, Wellcome Sanger Institute, working at the intersection of machine learning and biomedical science.

I see myself as a problem finder as much as a problem solver. My background in bioinformatics and biochemistry leads me to look for gaps where existing computational approaches fall short. Rather than simply applying established AI frameworks to biology, I focus on identifying under-explored problems in the domain and developing novel solutions to address the problems. I translate the complexity of biological and medical questions into well-defined computational problems, then build the models needed to solve them.

💡 Research Interest

  • Multi-modal learning of biomedical images and spatial transcriptomics
  • Regulatory DNA sequence generation
  • Temporal cell dynamics modeling

🚩 Research Vision

I see DNA as both a code and a codebook, deeply intertwined. My long-term goal is to build a program that simulates biological systems starting from DNA sequence.

What I cannot create, I do not understand. — Richard Feynman

💼 Professional Experience

Senior Data Scientist · Wellcome Sanger Institute, UK · Oct 2024 – present

  • Led SIGMMA, a hierarchical contrastive learning framework aligning H&E histopathology with spatial transcriptomics (ICML 2026 workshop paper; journal version in preparation)
  • Led LocoGen, a generative framework for de novo regulatory DNA design that uses property-guided generation for out-of-distribution objectives in a lab-in-the-loop cycle (NeurIPS 2026)

Research Intern · LG AI Research, Korea · Jan – Apr 2024

  • Contributed to ExaonePath, a self-supervised foundation model for H&E histopathology images (press)
  • Built a scalable, reproducible multi-omics preprocessing pipeline

🔥 News

  • 🎉 Sep 2026 · LocoGen, a locality-aware generative model for designing regulatory DNA, was accepted to NeurIPS 2026.
  • 🎉 Jul 2026 · Selected as one of 500 participants from over 6,000 applicants in the Anthropic × Gladstone Claude Life Sciences Hackathon, where I built a generative model that infers missing cell states across time points (LinkedIn post).
  • 🎉 Jun 2026 · SIGMMA was accepted to the ICML FM4LS/SD4H workshop; a journal version is in preparation (manuscript).
  • 🎉 Oct 2024 · Joined the Wellcome Sanger Institute.

🎓 Education

Ph.D., Interdisciplinary Program of Bioinformatics · Seoul National University, Korea · graduated Aug 2024

  • Thesis: Computational modeling of molecular interactions for biomarker discovery using single/multi-omics data
  • 3 first-authored and 10 co-authored papers
  • Developed GOAT, a graph neural network for multi-omics biomarker discovery in eosinophilic asthma (Bioinformatics, 2023)
  • Developed RNA-seq quantification and normalization pipelines for ICGC-ARGO

B.S., Biochemistry · Yonsei University, Korea · graduated Aug 2018

Publications

Full list on Google Scholar.

Dabin Jeong (2026). LocoGen. NeurIPS 2026.
Dabin Jeong (2026). SIGMMA. ICML 2026 Workshops (FM4LS / SD4H).
PDF Project
Dabin Jeong, Bonil Koo, Minsik Oh, Tae-Bum Kim, Sun Kim (2023). GOAT: Gene-level biomarker discovery from multi-Omics data using graph ATtention neural network for eosinophilic asthma subtype. Bioinformatics, 39(10).
PDF DOI

Technical Skills

  • Programming · Python, R, Shell, LaTeX
  • ML / Deep Learning · PyTorch, PyTorch Geometric, DGL, scikit-learn
  • Workflow & Reproducibility · Nextflow, Snakemake, Docker, Git

Awards & Achievements

  • 🏆 Invited talk (2023) · National Heart & Lung Institute, Imperial College London (host: Prof. Kian Fan Chung) — Deep graph attention for multi-omics network biomarkers in eosinophilic asthma
  • 🏆 National Excellence Scholarship (2016) · Natural Sciences and Engineering; sole recipient in the department

Languages

  • English · full professional proficiency
  • Korean · native
  • Spanish · conversational

🎶 Personal Interest

  • 🧶 Knitting
  • 🎲 Board games
  • ♟️ Chess
  • Linguistics, especially how symbols come to embody concepts (I admire Douglas Hofstadter and Terry Winograd)
  • Favorite books: Gödel, Escher, Bach; Surfaces and Essences; Language as a Cognitive Process