Current Postdoctoral Scholars

Catheter-associated urinary tract infections (CAUTI) are one of the most common nosocomial infections worldwide and represents a significant healthcare burden. CAUTI is often a polymicrobial disease, where a patient is infected with multiple uropathogens. Thus, my research focuses primarily on investigations into the polymicrobial interactions occurring in CAUTI.

Cystic Fibrosis (CF) is a recessive genetic disorder which causes abnormally thick mucus in essentially all mucosal organ systems. Historically, people with CF had a greatly reduced lifespan due to lethal respiratory infections resulting from an inability to clear microbes from the respiratory tract. Thankfully, in recent years the advent of chemical therapies has greatly extended the average lifespan of people with CF. However, there is now a growing awareness of morbidity and mortality caused by the effects of CF on other organ systems, particularly the gastrointestinal tract. Of note, people with CF have a rate of colorectal cancer (CRC) 5-10 times higher than the general population.

My research interests lie at the intersection of RNA biology, host-pathogen interactions, and non-coding RNA-mediated gene regulation. During my doctoral studies, I focused on the identification and functional characterization of stress-responsive small RNAs (sRNAs) in Deinococcus radiodurans, an extremophilic bacterium renowned for its extraordinary resistance to ionizing radiation and DNA damage. This work provided novel insights into RNA-based regulatory mechanisms that facilitate cellular adaptation under stress.

My research focuses on the application of deep learning techniques to cancer prognosis through the integration of multi-omics and multi-region sequencing data. I am particularly interested in developing deep learning models that explicitly account for intratumor heterogeneity, a defining feature of cancer progression characterized by the coexistence of genetically distinct subclones within the same tumor. These subclones are major drivers of disease recurrence, metastasis, and treatment resistance, yet they are often overlooked in conventional prognostic models.

My research focuses on the theoretical and numerical aspects of graph modeling. I am now extending these mathematical frameworks to bioinformatics problems. Using single-cell spatial expression data, my aim is to build geometry-aware, interpretable models that provide principled comparisons across samples and generate insights into cancer progression. 

Toxoplasma gondii is an intracellular parasite that infects a wide range of hosts, including humans, and is estimated to infect approximately one third of the world population. Following the acute phase of infection, T. gondii establishes chronic infection where tachyzoites differentiate into the slowly replicating bradyzoite form of the parasite and persist as intracellular cysts in both the brain and skeletal muscle. This is associated with chronic inflammation and a loss of motor function in infected mice.

Cryptococcus neoformans is a haploid budding yeast that causes cryptococcal meningoencephalitis in immunocompromised individuals, leading to approximately 120,000 deaths worldwide each year. My research investigates how this environmental fungal pathogen adapts to host-induced stress conditions, by examining the pathways involved in translatome reprogramming and virulence regulation.

Eventually, I aim to identify key regulatory networks that can be targeted for the development of novel antifungal strategies.