Welcome to my website!
My current research interests include statistical machine learning, data mining and deep learning. Some of my research papers in data science involve projects with partners such as Globe and Mail, Manulife, St. Mike’s Hospital, and Toronto Police Services.
Although, I love doing research in data science my passion is teaching. I am teaching Data Science courses in the "Data Analytics, Big Data, and Predictive Analytics" and "Practical Data Science and Machine Learning" certificate programs and "Data Science and Analytics" masters program.
I supervise students in their Data Analytics Capstone Projects and I am the second reader of all the M.Sc. Data Science Major Research Projects.
I will be happy to connect with you!
Since receiving my Ph.D. in Applied Mathematics, I have worked as an Assistant Professor and then, as an Associate Professor in the Department of Mathematics.
I am an Assistant Program Director, an Associate Member of Graduate Studies and a member of the Continuing Education Contract Lecturers Advisory Group at Toronto Metropolitan University.
I shared 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 Here is the video of that talk:
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."