I have two primary motivations for teaching. The first is succinctly described by a quote from an interview with Donald Knuth, a mathematician and successful teacher at Stanford. He said that the thrill of teaching is “when the light comes into somebody's eyes and they have now experienced something because you were able to help them learn it.” The way Dr. Knuth explained his love of teaching entirely resonates with me and has been my primary motivation for teaching since I was young.

My second motivation is more self-interested. Contrary to the saying, “Those who can, do. Those who cannot, teach.”, I believe those who want to deeply understand something, teach. I see teaching as an effective tool to complement my own learn. In reality, even subject matter experts have the potential to learn from the fresh perspective of a student. I had an eye-opening experience recently when a master’s student came to me for help with his Python code on deep learning-based adversarial example generation. He was attempting to take the derivative of the output of a neural network classifier as opposed to the derivative of the cost function, which I knew was incorrect. However, I was not able to accurately describe my reasoning. I went back to the literature and read extensively on the subject. The next time we met, I was able to share with him my newfound understanding of the reason was incorrect. Not only could he make progress on his code, but I left the experience with more insight into my own research on making anti-malware engines more robust against adversarial examples.


My current teaching area of interest is two-fold: 1) data analytics: text mining, web mining, artificial intelligence, deep learning, and 2) algorithm design and programming: Python, Java, data structures and algorithms.


I have experience both as a sole instructor and as a teaching assistant. At the University of Arizona, my Graduate-level, online course, MIS 562, Cyber Threat Intelligence (CTI) is in progress. The first time I taught CTI was in Summer 2019 and student evaluations reflected that I was an effective instructor (4.67/5.00 n = 21).

I firmly believe in making myself available to students and provide them with actionable feedback as early as possible. A couple of the free-text responses of students selected from the evaluation survey of my cyber threat intelligence course in 2019 reflect this:

I have also served as a teaching assistant for the following on-site courses: MIS 464, Data Analytics; MIS 511/411, Social and Ethical Issues of the Internet; and MIS 331, Database Management Systems. For the Data Analytics course, in addition to grading and class material preparation, I hosted outside-of-class, supplemental labs for students on Python, Weka, and Tableau. Also, I held weekly office hours for guiding the students through the course project. Finally, during my master’s at Concordia University, I served as a teaching assistant for the Fall 2015 graduate course, COMP 6321, Machine Learning, where I handled all grading and filled-in as a lecturer, as needed.