Scientific Foundation
Our platform is built on peer-reviewed research in drug discovery, fair machine learning, and large language models.
Core Focus Areas
Drug-Target Interaction
Interpretable AI models for drug discovery, including attention-based DTI prediction, binding site analysis, and molecular generation.
Large Language Models
Parameter-efficient fine-tuning, time series forecasting, and architectural innovations in transformers.
Evolutionary Computation & COVID-19
Foundational work on modular genetic algorithms, agent-based modeling, and pandemic containment strategies.
Recent Publications
Equi-mRNA: Protein Translation Equivariant Encoding for mRNA Language Models
Yazdani-Jahromi M., Khodabandeh Yalabadi A., Garibay O.O.
BoKDiff: Best-of-K Diffusion Alignment for Target-Specific 3D Molecule Generation
Khodabandeh Yalabadi A., Yazdani-Jahromi M., Garibay O.O.
FairContrast: Enhancing Fairness through Contrastive Learning and Customized Augmenting Methods on Tabular Data
Tayebi A., Khodabandeh Yalabadi A., Yazdani-Jahromi M., Garibay O.O.
Evaluating Fairness and Bias in Large Language Models for Tabular Data
Tayebi A., Garibay O.O.
LLM-Mixer: Multiscale Mixing in LLMs for Time Series Forecasting
Kowsher M., Sobuj M.S.I., Prottasha N.J., Alanis E.A., Garibay O., Yousefi N.
Predicting Through Generation: Why Generation is Better for Prediction
Kowsher M., Prottasha N.J., Bhat P., Yu C.N., Soltanalian M., Garibay I., Garibay O.
Showing 6 of 23 publications
Interested in Collaborating?
We partner with academic institutions and industry leaders to advance therapeutic discovery.
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