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Greetings and thank you for visiting my website!

I am pleased to share that my research interests primarily focus on the cutting-edge fields of statistical machine learning, data mining, and deep learning. My research papers in data science highlight collaborations with esteemed partners, including Globe and Mail, Manulife, St. Mike’s Hospital, and Toronto Police Services.

While my passion for data science drives my research endeavors, my true calling lies in teaching. I have the pleasure of instructing Data Science courses within the "Data Analytics, Big Data, and Predictive Analytics" and "Practical Data Science and Machine Learning" certificate programs, as well as the "Data Science and Analytics" master's program.

I take great pride in mentoring students through their Data Analytics Capstone Projects and serving as the second reader for all M.Sc. Data Science Major Research Projects.

Thank you for considering my website and I look forward to the opportunity to collaborate together.


I will be happy to connect with you!

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With a Ph.D. in Applied Mathematics and years of experience as an Assistant Professor and then an Associate Professor in the Mathematics Department, I have deep understanding of the field and have made significant contributions to it. Besides being a Data Science Professor, I am grateful for the opportunity to serve as an Assistant Program Director, Associate Member of Graduate Studies, and a member of the Continuing Education Contract Lecturers Advisory Group at Toronto Metropolitan University, which has given me a broader understanding of the importance of STEM education and its impact on society.

Recently, I had the privilege of sharing my academic journey from mathematics to data science in a talk on "From Mathematics to Data Science" for Society for Industrial and Applied Mathematics (SIAM) Student Chapter of Western Kentucky University. I invite you to watch the video to learn more about my experiences and insights on the fascinating field of data science.

As a subject matter expert on Data Science, I have prepared video lectures and online course materials for the courses CIND 123 Data Analytics: Basic Methods and CMTH 642 Data Analytics:  Advanced Methods, and CIND 840 Practical Approaches in Machine Learning. These video lectures are currently used in "Data Analytics, Big Data, and Predictive Analytics" and "Practical Data Science and Machine Learning" certificate programs at The Chang School of Continuing Education, Toronto Metropolitan University, and have served thousands of students. 


Here are a few short sample videos from the first lecture of Data Analytics: Basic Methods course.

Here is a my video tutorial on "How to conduct data analysis process systematically."

Here are the slides of my seminar series on "Linear Algebra for Machine Learning."

Seminar 1
Seminar 2
Seminar 3
Seminar 4
Seminar 5
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