I'm a forward-thinking learner 🙋 and researcher 📖 proficient in
numerical modeling and machine learning.
My last name, Junxing, carries a story of significance rooted in its Chinese origins. Jun 俊 signifies brilliance and exceptional intellect, while Xing 行 embodies the essence of action and determination.
During my childhood, my parents called me Jacky, a name that held a sense of familiarity and warmth.
As time passed, I found myself drawn to the simplicity and coolness of the initials J.C. Not only did it encapsulate my identity, but it also served as a convenient and distinctive moniker. Thus, J.C. became my preferred choice, reflecting both my heritage and my evolving sense of self.
0 Days of Research Works
Explore my journey through academia, professional experiences, and skill sets in my resume section, showcasing a comprehensive overview of my qualifications and achievements.
During my PhD, I developed thermodynamic software DIFFUSUP, modeled Venus and Earth evolutions, statistically analyzed geochemical data. I published extensively in top scientific journals, including Nature Communications, presented findings at top-tier conferences like AGU, and educated numerous students, showcasing a strong commitment to numerical modeling, earth sciences, and research.
I was awarded an outstanding student scholarship and pursued a Bachelor's degree in Earth and Planetary Science.
As a Data Scientist Intern at IBM, I spearheaded the development of over 100 machine learning projects, led a 10-person team in creating top-rated data science content for the Skills Network, reaching millions of users worldwide. Also, I orchestrated the integration of AI-embedded applications into the IBM Watson ecosystem and utilizing LLMs (e.g. GPT-4 Llama-2) and Watson NLP to analyze sentiment from various sources. I excel in tackling complex data science projects with precision and innovation.
I processed Brillouin laser experiments data, leading to publication in Scientific Reports.
If your system includes multiple cores (CPU cores), can we accelerate the Pandas by parallel calculation?
Pandas and its competitor Polars, which is also a similar data management python library written in Rust.So, here comes the question. Which one of the two animals is stronger?
Great expectations! This tool is an expert in doing data validation, including basic data understanding, information discovery, seamless fit and essential security.
Toronto, Ontario, Canada