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Madhawa Vidanapathirana has a diverse work experience in the field of software engineering. Madhawa is currently working at Sanctuary AI as a SE - Cognitive Services since March 2023. Prior to this, they worked at Microsoft as an SDE II for the Mixed Reality team from December 2021 to February 2023. Madhawa also worked as a Graduate Research Assistant at Simon Fraser University from September 2019 to August 2021.

In 2018, Madhawa initiated YOLO3-4-Py, a Python wrapper on YOLO 3.0 implementation in Darknet. This open-source project gained popularity on GitHub with 450+ stars and 150+ forks. Additionally, Madhawa worked as a Software Engineer at CodeGen International from January 2018 to August 2019, where they gained experience in machine learning and data science and worked with Salesforce and Microsoft Dynamics 365 REST APIs.

In 2017, Madhawa contributed to the Google Summer of Code program at WSO2. Madhawa also worked as a Trainee Software Engineer at WSO2 from August 2016 to December 2016.

Overall, Madhawa has a strong background in software engineering, with experience in cognitive services, mixed reality, research, open-source projects, machine learning, and API development.

Madhawa Vidanapathirana completed their M.Sc. in Computing Science (Thesis) with a focus on Computer Graphics and Vision at Simon Fraser University from 2019 to 2021. Prior to that, they obtained a B.Sc. in Engineering with a specialization in Computer Science and Engineering from the University of Moratuwa, where they studied from 2014 to 2018. In 2012 and 2013, Madhawa pursued a Professional Qualification in Accounting and Business/Management at The Chartered Institute of Management Accountants. Madhawa'ssecondary education was at Ananda College, where they completed their GCE Advanced Level studies in Physical Sciences from 1999 to 2012.

During their educational journey, Madhawa also received various certifications. In August 2013, they obtained a certification in Machine Learning from Stanford University through Coursera. In 2018, they completed several specializations and courses in deep learning and machine learning, including Deep Learning Specialization, Sequence Models, Convolutional Neural Networks, Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, Structuring Machine Learning Projects, and Neural Networks and Deep Learning. These certifications were also acquired through Coursera.