I'm a Teaching Professor at the Department of Computing Studies and Information Systems, Douglas College in New Westminster, British Columbia. Currently, I am teaching courses on Advanced Databases, System Analysis and Design, Data Analytics, and Fundamental Machine Learning. Aside from my teaching, I am actively pursuing theoretical and applied research related to Probabilistic and Bayesian Modeling, Anomaly Detection, Dimension Reduction, and interdisciplinary applications of Auto-Encoders. Previously, I taught undergraduate and graduate courses at Vancouver Island University, University of Manitoba and North South University.

I obtained my MSc in Computer Science Degree from University of Manitoba, supervised by Dr. Maxime Turgeon and Dr. Cüneyt Akçora, where I focused on Dimension Reduction and Anomaly Detection using Unsupervised Machine Learning. Along with Unsupervised settings, I researched on various Data Analytics methods, including Feature Extraction, Two-staged Modeling approach, Statistical Modeling under Dimension Reduction Lab and NSERC CREATE fund on The Visual and Automated Disease Analytics (VADA) graduate training program. Prior to that, I worked with Dr. Shahnewaz Siddique and Zunayeed Bin Zahir on interdisciplinary research topics including Robotics, Recommender Systems, Health Informatics and Computer Vision.

My research interests lie in the intersection of Supervised and Unsupervised Machine Learning, with a specific focus on Probabilistic and Bayesian Modeling, Anomaly Detection, and Dimension Reduction. I am currently exploring the intricacies of Auto-Encoders and their applications in Variational and Gaussian modeling. My work delves into the statistical interpretation and visualization of Unsupervised Machine Learning algorithms, emphasizing dimension reduction and anomaly detection. Additionally, I contribute to the field of Data Engineering by developing interactive Python packages for tasks such as Data Cleaning, Visualization, Model Interpretation, Data Scaler Selection, and Statistical Analysis. Explore some of my Python packages on PyPI.

• [July 2024] My paper titled "A Comprehensive Study of Auto-Encoders for Anomaly Detection: Efficiency and Trade-offs," published in the Machine Learning with Applications Journal, DOI: https://doi.org/10.1016/j.mlwa.2024.100572
• [June 2024] Received Research Dissemination Present and Research Dissemination Publish Grant from Douglas College
• [December 2023] Joined Douglas College, New Westminster Campus as a Teaching Professor.
• [August 2023] Started my new journey as a Faculty Member, at the Vancouver Island University.
• [May 2023] Promoted to Senior ML Engineer, Forum Inc
• [February 2023] Lastest Published Conference Paper - Feature Extraction and Prediction of Combined Text and Survey Data using Two-Staged Modeling
• [January 2023] My Msc dissertation, Dimension Reduction and Anomaly Detection using Unsupervised Machine is now online
• [December 2022] Successfully defended my MSc thesis.
• [November 2022] Manuscript in Preparation - A Comprehensive Study of Auto-Encoders for Anomaly Detection: Efficiency and Trade-Offs
• [November 2022] Guest Lecture, Introduction to Python and Numpy, STAT-447: Statistical Machine Learning for Data Science, Department of Mathematics and Statistics, University of Saskatchewan
• [September 2022] Received Graduate Travel Award from University of Manitoba, NSERC CREATE VADA Program

Stuff I work with





External Websites

• Personal Website
• ResearchGate
• Google Scholar
• LinkedIn

Python Packages

• Data Scaler Selector
• Image to Sketch
• Data Preparer