My story

My innate curiosity to understand the underlying mechanisms behind the world around me led me to study a Bachelor's degree in Cellular, Molecular and Microbial Biology. It was during my undergraduate studies where I stumbled upon the field of Bioinformatics which lays at the intersection between biological science, applied statistics and computer technology. As an undergraduate Bioinformatics researcher, I developed a data pipeline, Nybbler, to perform targeted subsampling for genetic sequences of COVID-19. In addition, I also worked on other research projects including MinION, which enables real-time genetic sequencing by utilizing GPU parallelization with CUDA, under the supervision of Dr. Paul Gordon and Dr. Quan Long. Aside from my involvement in academia, I was also recognized for my strong academic track record and campus involvement through the means of various awards. During my studies, I hosted a medical conference, MedX; I was a faculty representative on the First Year Council; I also co-founded a national student-run, not-for-profit organization, COUHR, which operates in 4 cities across Canada and led the technological development department within the organization to create a mobile health tracking application for patients with Alzheimer's disease.

After recognizing that the forefront of medical and biological innovation is empowered and driven by the use of big data and artificial intelligence, I was motivated to pursue a Master's degree in Mathematics and Statistics to gain a deeper understanding of the mechanisms behind such advancements. This transition from a non-traditional background to a technical field involving robust mathematics, statistics, and computer science marked a difficult period in my academic journey. Through the guidance of my peers and my supervisor, Dr. Qingrun Zhang, I was able to maintain my academic excellence while engaging in various meaningful research data science projects. With the use of various machine learning and statistical testing techniques, I identified key genes and biomarkers correlated with diseases such as Glaucoma and Cancer. Meanwhile, I also devised and developed a novel optimization method which reduced run-times for evolutionary analysis by more than 2900% through parallelization.

Currently, I am working as a Data Mining Analyst at the University of Calgary, where I explore the application of state-of-the-art methods, such as transformers, to filter and summarize relevant biomedical scientific literature. My work focuses on enhancing the efficiency of data extraction and interpretation, driving advancements in biomedical research and bioinformatics. I am now seeking opportunities in data science and machine learning within a corporate setting, driven by a keen interest in applying these techniques in a business context. Having not yet worked in such an environment, I am eager to see the immediate, tangible results that these applications can deliver.

Outside of this, owing to my affinity for novelty, I hold many scattered interests in subjects such as artificial intelligence, finance, biotechnology, music and reading. Recently, the book that left the strongest impression on me was The Almanack of Naval Ravikant. I also make YouTube tutorials for Web Automation Development which have currently accumulated more than 100,000 views. Finally, I am very passionate about playing basketball and volleyball, and always enjoy a stimulating conservation!