Hello, World!

I'm Colin Zhang, currently a Ph.D. student at Osaka University, focusing on computational fluid dynamics, machine learning applications, and 3D bioprinting. My passion with science and engineering started early, but it was during my mechanical engineering studies at UC Santa Barbara that I discovered my passion for computational problem-solving. This intersection of science and computation sparked my interest in programming, opening up a world of new problem-solving techniques and introducing me to the power of computational thinking.

As I developed skills in Python, C, JavaScript, HTML/CSS, and machine learning, I began to see how programming could transform traditional engineering fields. I'm particularly excited about the potential of combining machine learning with biotechnology. As a MEXT scholar in Japan, I've had the chance to dive deeper into these areas while also supporting undergraduates at Osaka University's Main Library.

Outside of my academic pursuits, I have a diverse range of interests. I love the challenge of mountain climbing and the perspective-broadening experiences of travel. I'm a firm believer in lifelong learning, often immersing myself in online courses to expand my knowledge. To unwind, I lose myself in a good book, finding it both relaxing and enlightening. These experiences continue to shape me not just as a student and researcher, but as a person.

Japanese News Scraper

NHK NEWS WEB EASY Scraper

Welcome to the NEWS WEB EASY Scraper. This tool helps you fetch and display simplified Japanese news articles from the NHK NEWS WEB EASY website. It not only provides you with the news content, but also extracts key vocabulary and their pronunciations, along with dictionary definitions where available*.

To start, simply click on the 'Fetch News' button. You can also copy the content to your clipboard using the 'Copy Content' button.

During news update periods, the news fetching function may not work correctly. In addition, please be aware that the 'Fetch News' function extracts a random article from the 10 latest headlines on the NHK NEWS WEB EASY website.

*The dictionary feature is no longer available for news after 2024/10/01 due to changes in the NHK NEWS WEB EASY website.

You can also explore a user-friendly graphical interface version of this tool, developed with Python. Check it out on this GitHub repository.
All news content is copyrighted by NHK (Japan Broadcasting Corporation).
The "NEWS WEB EASY" uses the "Reikai Elementary School Japanese Dictionary 5th Edition" by Sanseido. The copyright of the dictionary belongs to Sanseido Co., Ltd., the creator of the dictionary.

Research Interests

3D extrusion bioprinting is advancing rapidly in the field of tissue engineering, enabling the creation of complex, biologically engineered structures with high precision. Key challenges in the process include optimizing needle geometry, extrusion parameters, and maintaining cell viability. Numerical analysis and machine learning are increasingly applied to control factors such as fluid shear stress, ink rheology, and extrusion velocity, improving printability and ensuring better cell survival rates in the printed structures. This combination of computational methods and experimental validation offers a promising path toward more effective bioprinting solutions for tissue regeneration and therapeutic applications.

GraphicalAbstract1

Figure 1. Graphical workflow for bioprinting optimization: Rheological testing provides ink properties for numerical simulation of needle extrusion, followed by live/dead cell viability analysis. A machine learning model integrates cell type, ink viscosity, and extrusion parameters to predict and optimize cell viability outcomes. Created with BioRender.

Publications

  1. Colin Zhang, Kelum C. M. L. Elvitigala, Wildan Mubarok, Yasunori Okano, and Shinji Sakai. (2024). Machine learning-based prediction and optimisation framework for as-extruded cell viability in extrusion-based 3D bioprinting. Virtual and Physical Prototyping, 19(1), e2400330.
    https://doi.org/10.1080/17452759.2024.2400330. Open Access.
  2. Mitsuyuki Hidaka, Masaru Kojima, Colin Zhang, Yasunori Okano, and Shinji Sakai. (2024). Experimental and numerical approaches for optimizing conjunction area design to enhance switching efficiency in single-nozzle multi-ink bioprinting systems. International Journal of Bioprinting, 10(5), 4091.
    https://doi.org/10.36922/ijb.4091. Open Access.
  3. Wildan Mubarok, Colin Zhang, and Shinji Sakai. (2024). 3D Bioprinting of Sugar Beet Pectin through Horseradish Peroxidase-Catalyzed Cross-Linking. ACS Applied Bio Materials, 7(5), 3506-3514. https://doi.org/10.1021/acsabm.4c00418.

Conferences

  1. The 55th Autumn Meeting of The Society of Chemical Engineers, Japan, Hokkaido University, September 10-13, 2024
    Presentation Title: Predictive modeling of cell viability in extrusion-based 3D bioprinting using machine learning [Featured Presentation (22 out of 1130)]
    Colin Zhang, Yasunori Okano, and Shinji Sakai
  2. The 53rd Autumn Meeting of The Society of Chemical Engineers, Japan, Shinshu University, September 14-16, 2022
    Presentation Title: A Numerical Investigation of Stresses, Printing Efficiency, Printability, and Cell Viability in Nozzle Printheads for 3D Extrusion Bioprinting
    Colin Zhang, Mitsuyuki Hidaka, Masaru Kojima, Shinji Sakai, and Yasunori Okano

Course Certificates

Contact Information

You can reach me by executing the following Python script, which uses ASCII-to-string conversion:

"".join(chr(i) for i in (107, 111, 114, 105, 110, 46, 106, 97, 112, 97, 110, 64, 103, 109, 97, 105, 108, 46, 99, 111, 109))

Or, the JavaScript version which can be run directly in your browser's console:

String.fromCharCode(107, 111, 114, 105, 110, 46, 106, 97, 112, 97, 110, 64, 103, 109, 97, 105, 108, 46, 99, 111, 109);