Yunan Luo
Assistant Professor
Develops machine learning methods for computational biology and protein engineering.
Yunan Luo's lab at Georgia Tech works on proteins, drugs & materials and genomics & computational biology. 21 papers since 2023, 8 at top venues, mostly ICLR and Nature Communications. 7 PhD students. 2 alumni. Applications close .
At a glance
- papers, 2023–2026
- 5/ year
- at T1 venues
- 38%
- PhD students
- 7
- MS students
- 0
- alumni listed
- 2
Papers by yearfrom the lab homepage, 2023–2026
- 2 papers2026 · T1 0 · collecting
- 5 papers2025 · T1 2
- 6 papers2024 · T1 2
- 8 papers2023 · T1 4
T1 venuesOtherVenues: ICLR, Nature Communications, ICML, Nature Machine Intelligence, NeurIPS
Research focuspaper titles that use each topic's words
- Proteins, drugs & materials11 papers
- Genomics & computational biology0 papers
- protein engineering0 papers
- computational biology0 papers
- computational science0 papers
Paper list
From the lab homepage.
20262 papers
- RECOMBDeconvolving mutation effects on protein stability and function with disentangled protein language models (opens in a new tab)
- RECOMBEvolutionary profile enhancement improves protein function annotation
20255 papers
- Nature Communications (T1)Generalizable and scalable protein stability prediction with rewired protein generative models
- ICLR (T1)Group Ligands Docking to Protein Pockets
- RECOMBLearning maximally spanning representations improves protein function annotation (opens in a new tab)
- iSciencePareto-optimal sampling for multi-objective protein sequence design
- RECOMBRewiring protein sequence and structure generative models to enhance protein stability prediction (opens in a new tab)
20246 papers
- Communications ChemistryBioDolphin as a comprehensive database of lipid–protein binding interactions
- RECOMBContrastive Fitness Learning: Reprogramming Protein Language Models for Low-N Learning of Protein Fitness Landscape
- ICML (T1)FAFE: Immune Complex Modeling with Geodesic Distance Loss on Noisy Group Frames
- PLOS Computational BiologyLeveraging conformal prediction to annotate enzyme function space with limited false positives
- Nature Communications (T1)Machine learning-guided co-optimization of fitness and diversity facilitates combinatorial library design in enzyme engineering
- Nature Reviews Electrical EngineeringOpportunities and challenges of graph neural networks in electrical engineering
20238 papers
- Nature Machine Intelligence (T1)Calibrated geometric deep learning improves kinase-drug binding predictions
- PSBContrastive learning of protein representations with graph neural networks for structural and functional annotations
- Science (T1)Enzyme function prediction using contrastive learning
- ICLR (T1)Interpretable Geometric Deep Learning via Learnable Randomness Injection
- NeurIPS (T1)LinkerNet: Fragment Poses and Linker Co-Design with 3D Equivariant Diffusion
- eLifeMetabolic activity organizes olfactory representations
- Nature Computational ScienceSensing the shape of functional proteins with topology
- ISMBSupervised biological network alignment with graph neural networks
Where alumni went2 listed
Apply to Georgia TechFall 2027
Georgia Tech Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- optional
- English
- TOEFL/IELTS
- Fee
- See program page
Not yet confirmed for this intake.
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- Papers
- The lab homepage
- Members
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