I’m a scientist with hands-on experience spanning the full spectrum of biomedical research—from the clinic to the lab bench to computational modeling of large scale data. Im interested in bridging theory and application—leveraging large scale clinical, biological, and health data to drive meaningful biomedical innovation using rigorous and reproducible approaches. Check out my CV.
Networks are foundational across biomedical innovation. Constructed networks and network graphs are used to connect functional pathways, disease states, integrate multimodal data, identify biomarkers, and design drug targets. My work explores the reproducibility and statistical rigor of methods that infer these networks from sequencing and non-graph data sources.
Advances in machine learning and artificial intelligence offer unprecedented opportunities for data-driven discovery. My research focuses on the theoretical underpinnings and statistical rigor of these methods, ensuring robust and interpretable results for biomedical applications.
Genomic sequences can be mined to determine unique barcodes that identify particular taxonomies. These sequences not only serve as diagnostic indicators for strain detection but also reveal critical insights into functional and disease pathways. My research aims to bridge computational genomics with actionable diagnostics and therapeutic strategies.
I collaborated with E.L.i.T.E. in Harlem, NYC, and Global Code in Accra, Ghana to develop curriculum, structure learning, assist in hands-on material, and teach classroom lectures. Engineering material was tailored to different education levels:
As the president and board member of Genomix, a student-run organization at Penn State University, I represented the bioinformatics and genomics community. During my graduate studies, I also served as a teaching assistant for a graduate genomics course, delivering lectures and grading assignments. Key contributions include:
As a volunteer mentor, I guided middle school, high school, and undergraduate students through their professional development. I believe in sharing lessons learned to help others seeking advice or pursuing their interests in STEM. I participated in programs such as:
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