AI Researcher • Ph.D. Candidate • Computational Biology Enthusiast
I'm a Ph.D. candidate in Computer Science at the University of Central Florida, working at the intersection of machine learning, computational drug discovery, and bioinformatics. My research focuses on building robust, symmetry-aware models for biological sequence modeling, particularly in the context of mRNA, drug-target interaction, and fairness in AI systems.
- HELM (ICLR 2025): Developed the first hierarchical mRNA language model, improving antibody prediction by 8%.
- FragXsiteDTI (NeurIPS 2024): Transformer-based model for interpreting drug-target binding sites.
- FairBiNN (NeurIPS 2024): Bilevel optimization for balancing accuracy and fairness in neural networks.
- DeepDrugDomain: Toolkit for standardizing datasets and benchmarks in drug discovery tasks.
- Equi-mRNA (under review): Group-theoretic model for codon embeddings and equivariant mRNA generation.
- Languages: Python, C++, JavaScript, Dart, SQL, Solidity
- Frameworks: PyTorch, TensorFlow, Hugging Face Transformers
- Specialties: Group Theory in ML, Geometric Deep Learning, Language Modeling
- Tooling: Kubernetes, Docker, AWS, Slurm, Triton, CUDA
- 💼 AI Research Scientist Intern @ Microsoft Research (Bio-LLMs)
- Papers at NeurIPS, ICLR, RECOMB, and Briefings in Bioinformatics
- Featured on ABC News and UCF Today for drug repurposing work during the COVID-19 pandemic
🧠 Building the next generation of biological AI models, one codon at a time.