Research & Development
My research focuses on applying machine learning to genomics and developing bioinformatics solutions.
For a complete list of publications, visit my Google Scholar profile.
Development of a deep learning-based MRD detection system
Development of a deep learning-based genotype imputation system
Identification and filtering of germline mutation for accurate TMB calculation
Clustering and consensus generation of sequencing data
Deduplication of sequencing data
Essential gene prediction in bacterial genomes
The genome of Cowpea (Vigna unguiculata [L.] Walp.)
A multi-class classification approach for identifying cancer types using somatic mutation profiles
Miscellaneous Projects
Other notable projects and contributions in algorithm development and machine learning.
Development of a multimodal deep-learning model for patient survival prediction
- •Worked on a multimodal deep-learning model for patient survival prediction as part of a digital pathology team
- •The project used H&E images, patients' clinical data, and gene expression data for training the prediction model
- •The model consists of a convolutional neural network for training image data and a multilayer perceptron for training the clinical and mRNA data
- •Won several internal awards for the project
- •The project is currently pending a patent
Development of a Virtual Pathologist using Large Language Models
- •Teamed up with the digital pathology group on a Virtual Pathologist project
- •Uses a large language model (LLM) for generating explanations for pathology images
- •Our team won an internal award for this project
Patents
- •US Patent: In Progress (2024)
Development of a RAG system for internal documentation
- •Developed a RAG system for internal documentation using a large language model (LLM)
- •The system uses a large language model (LLM) for generating explanations for internal documentation
- •Ongoing work on generating test cases for project technical requirements and product requirements