Research

Research in applied mathematics, computational biology, machine learning, and biomedical AI.

Research Overview

My research lies at the intersection of applied mathematics, computational biology, machine learning, and biomedical artificial intelligence. I develop mathematical and computational approaches to extract meaningful information from complex biological data, investigate cellular dynamics, and understand biological systems through quantitative analysis.

My current research focuses on RNA velocity and cellular state transitions, nanopore long-read sequencing, large-scale biological network analysis, and machine learning for biomedical applications.

Research Projects

The following projects illustrate my ongoing research in computational biology, applied mathematics, and biomedical AI.

project thumbnail

Macrophage State Transitions in Lung Cancer

Integrating RNA velocity and long-read single-cell transcriptomics to investigate macrophage plasticity in non-small cell lung cancer.
project thumbnail

Mechanism-Aware Multiscale Modeling of Glioblastoma

A mathematical and computational framework linking tumor infiltration, mechanical mass effect, MRI, and single-cell and spatial transcriptomics.
project thumbnail

BioFilter-EVTS

A biology-guided framework for evaluating and refining RNA velocity visualizations using transition consistency, pseudotime, lineage structure, and marker-gene progression.
project thumbnail

Mega-Scale Cell-Cell Similarity Network Analysis

Scalable graph analysis of more than one million embryonic mouse brain cells to identify developmental modules and transition-associated cells.
project thumbnail

Nanopore Long-Read Sequencing and Computational Genomics

Machine learning and mathematical approaches for RNA velocity and DNA methylation analysis using Nanopore long-read sequencing.
project thumbnail

Topology- and Graph-Guided AI for Cardiometabolic Phenotyping

Integrating topological data analysis, patient similarity networks, and graph neural networks to discover cardiometabolic phenotypes and predict longitudinal disease risk in All of Us.

Research Funding

MS-INBRE Project Development Grant

Integrating RNA Velocity and Isoform-Level Analysis to Define Macrophage State Transitions in Non-Small Cell Lung Cancer

  • Role: Principal Investigator
  • Award Amount: $292,000
  • Project Period: September 1, 2026 – August 31, 2028

NSF HBCU-UP Implementation Project (#2510537)

Strengthening the Diverse STEM Pipeline through a Holistic Multi-layer Approach

  • Role: Co-Principal Investigator, Lead Author, and Technical Lead
  • Total Project Award: $2,245,846
  • Project Period: August 1, 2025 – July 31, 2030

NSF HBCU-UP Research Initiation Award (#2300445)

Uncovering and Extracting Biological Information from Nanopore Long-Read Sequencing Data with Machine Learning and Mathematical Approaches

  • Role: Principal Investigator
  • Award Amount: $299,882
  • Original Project Period: August 1, 2023 – July 31, 2026

Nissan Foundation Award

Increasing the STEM Pipeline

  • Role: Principal Investigator
  • Award Amount: $45,000
  • Project Period: April 1, 2026 – March 31, 2027

Explore my Publications and Research Group for additional information.