Yunha Hwang

yunhacorn[at]gmail[dot]com

About me

I am an incoming Assistant Professor at MIT (starting Fall 2025) with a shared appointment between Biology, EECS and the Schwarzman College of Computing. Currently, I serve as the co-founder and CEO at Tatta Bio, a scientific nonprofit dedicated to advancing genomic AI for biological discovery. I completed my Ph.D. in Biology from Harvard University and B.S. in Computer Science from Stanford University. My research interests span machine learning for sustainable biomanufacturing, microbial evolution, and open science.

I am hiring PhD students and postdocs to start in Fall 2025, please email me if you are interested.

Research Interests

Microbial genomes encode the largest molecular, biochemical and functional diversity on Earth. My group’s research focuses on developing machine learning models and experimental approaches to discover and design novel biological functions. We integrate computation with expertise in evolution, ecology and biochemistry to characterize and harness the molecular potential of microbes.

Machine learning approaches to discover and design microbial biochemistry. Microbes are the world’s best chemists. We develop machine learning approaches and datasets to characterize and harness the full chemical potential of microbes.

Modeling and interpreting mechanisms of microbial evolution, ecology and function. AI is transforming how we conduct scientific inquiry. We build and interpret biological sequence models to discover mechanisms that underpin biological processes across scales.
Microbial applications for human and environmental health. From natural products, biomanufacturing to microbial therapies, we focus on research that addresses critical challenges.

Academic CV

Publications

For the most up to date list, please see my Google Scholar.

Nishant Jha, Joshua Kravitz, Jacob West-Roberts, Antonio Camargo, Simon Roux, Yunha Hwang, “Gaia: A Context-Aware Sequence Search and Discovery Tool for Microbial Proteins”, BioRxiv (2024)

Try out Gaia at https://gaia.tatta.bio/

Andre Cornman, Jacob West-Roberts, Antonio P Camargo, Simon Roux, Martin Beracochea, Milot Mirdita, Sergey Ovchinnikov, Yunha Hwang , “The OMG dataset: An Open MetaGenomic corpus for mixed-modality genomic language modeling”, ICLR (2025)

Jacob West-Roberts, Joshua Kravitz, Nishant Jha, Andre Cornman, Yunha Hwang “Diverse Genomic Embedding Benchmark for functional evaluation across the tree of life”, BioRxiv, (2024)

Yunha Hwang, Andre Cornman, Elizabeth Kellogg, Sergey Ovchinnikov, Peter Girguis “Genomic language model predicts protein co-regulation and function” Nature Communications, (2024)