{"id":608,"date":"2023-10-31T15:24:09","date_gmt":"2023-10-31T15:24:09","guid":{"rendered":"https:\/\/blogs.mathworks.com\/finance\/?p=608"},"modified":"2024-03-12T14:59:30","modified_gmt":"2024-03-12T14:59:30","slug":"the-path-to-carbon-neutrality-a-time-series-approach","status":"publish","type":"post","link":"https:\/\/blogs.mathworks.com\/finance\/2023\/10\/31\/the-path-to-carbon-neutrality-a-time-series-approach\/","title":{"rendered":"The Path to Carbon Neutrality: A Time Series Approach"},"content":{"rendered":"

The following blog was written by <\/span><\/span>Leslie Zhang<\/span><\/span><\/a>, a <\/span>Northeastern<\/span> graduate who recently joined <\/span><\/span>MathWorks Engineering Development program<\/span><\/span><\/a>.<\/span> This post aims to highlight the <\/span>collaboration <\/span>opportunities available to students <\/span>and Leslie\u2019s journey to joining MathWorks<\/span>.\u00a0<\/span>\u00a0<\/span><\/span>\u00a0<\/span><\/em><\/p>\n

Background:<\/h2>\n

As a young engineer, I always dreamed of contributing to a company that values innovation and fosters collaboration. My journey led me to a place that exceeded my expectations – the <\/span>MATLAB and Simulink Challenge Projects<\/span><\/a> and the Engineering Development Group at MathWorks.<\/span>\u00a0<\/span><\/p>\n

My education stands at the intersections between Econometrics and Computer Science, and this leads me to explore the interest in deploying data science models to resolve industrial pain points.<\/span> In February 2023, I got a chance to collaborate with MathWorks through the MATLAB and Simulink Challenge Projects, led by Roberto Valenti<\/a>. This initiative provides a platform for students to engage in research, explore cutting-edge technologies, and contribute to groundbreaking projects. It was through this project that I had the privilege of collaborating with Yuchen Dong<\/a>, a Senior Financial Application Engineer at MathWorks. Together, we embarked on a mission to tackle the pressing issue of carbon neutrality using a time series approach.<\/span>\u00a0<\/span><\/p>\n

Our project aimed to develop innovative solutions using machine learning, deep learning, time series analysis, and Monte Carlo simulation, all powered by MATLAB. <\/span>In comparison with open-source tools like Python and TensorFlow,<\/span> I choose MATLAB as the primary language because it empowers data model deployment with extensive toolboxes such as Econometrics Toolbox<\/a>\u00a0that supports auto code generation. MATLAB also provides specialized tools for displaying and sharing models in standalone applications and web applications, such as MATLAB Compiler<\/a> and MATLAB Production Server<\/a>. <\/span>Our journey culminated in the publication of a conference paper titled “<\/span>The Path to Carbon Neutrality: A Time Series Approach<\/span><\/a>“, presented at the 2023 SPIE Conference: Machine Learning Chapter in San Diego, California. <\/span>This Machine Learning conference attracts engineers and scientists to show how data science can release its potential in various industries, from optics manufacturing, physics, to environmental engineering.\u00a0<\/span>\u00a0<\/span><\/p>\n

The project highlighted the potential of MathWorks’ software in addressing complex challenges and underscored the company’s commitment to sustainability and carbon reduction efforts.\u00a0<\/span>\u00a0<\/span><\/p>\n

\"\"<\/p>\n

Poster presented at SPIE 2023<\/em><\/p>\n

\"\"<\/p>\n

Yuchen Dong and Leslie Zhang at SPIE 2023<\/em><\/p>\n

The project:<\/h2>\n

This example produced from this project leveraged MATLAB R2023a and according toolboxes to<\/p>\n