Teaching

I am not teaching during the academic year 2021/22 as I am on sabbatical.

Check back in Fall 2022!

Let's have a conversation!

My teaching goal is to re-frame all of our learning as a conversation. I've learned from toddlers recently: nobody should think of themselves an expert vs. novice; we are all discovering together, exchanging ideas, and building on them.

While it is extremely difficult to reframe entire semester-long courses from this point of view in the present educational system, I promise to - at least - keep lectures interactive during the semester. One example of what this means is the use of interactive quiz slides throughout the lecture, such as these slides - they are not presented all at once, but dispersed around the lecture.

Studying tips:

Advice for graduate students

Past courses

Spring 2021

Fall 2020

Older

For a full list of courses I've taught, go here: courses taught at IIT, at Penn State, at UIC, at UK.

SPRING 2021 courses - quick facts

Math 563: Mathematical statistics

    • Tuesdays & Thursdays 2pm-3:15pm

    • At a glance:

      • Input:
        (fundamental statistical concepts,
        critical thinking,
        skepticism         ("do you really believe this claim?"),
        enthusiasm for learning how to understand and work with data)
        Output:
        general understanding of mathematical statistics,
        basic experience in using R/Rstudio/Markdown,
        all the background for the Stats Qualifying Exam.

    • Interactive, with participation a grade component:

      • AhaSlides! interactive quizzes for working through examples in the lectures;

      • Campuswire as the main communication platform (wiki-style, social style, quick, easy to use).

    • Respectful of many facets of humankind (share your culture! share your experience! you are valued!) and inclusive (choose your method of participation: anonymous (yes, it counts for credit), camera on/off, share identity, ... This is your class.

STAT 514 / ITMD 514 Applied computational statistics for analytics

    • Mondays 8:05am - 10:45am

    • At a glance:

      • Input:
        (fundamental statistical concepts,
        corresponding computational tools,
        an open mind,
        enthusiasm about learning to work with data)
        Output:
        ability to extract actionable insights from data.

      • Extensive use of R/Rstudio, Python/Anaconda, Markdown.

      • Putting things together hands-on: the how-and-why of it all.

      • Online, but interactive, with participation a grade component:

        • AhaSlides! interactive quizzes for working through examples in the lectures;

        • Campuswire as the main communication platform (wiki-style, social style, quick, easy to use).

      • Respectful of many facets of humankind (share your culture! share your experience! you are valued!) and inclusive (choose your method of participation: anonymous (yes, it counts for credit), camera on/off, share identity, ... This is your class.