(my philosophy: teach math using english)

Teaching Assistantships


      Recipient of Machine Learning Department's Best TA Award, for the following contributions and student feedback.
  • Convex Optimization (PhD course) (Fall'13) - Ryan Tibshirani and Barnabas Poczos
    Duties of the four TAs included designing homeworks and solutions from scratch, designing exams, grading homeworks and exams, conducting weekly recitations, holding weekly office hours, guiding and grading several project groups, taking videos, organizing scribes, maintaing the website, etc.
    Additionally, based on feedback from the previous year, I was involved with reshaping the course structure with the professors during the summer. We decided to offer a 9 and 12 credit version, i.e. making course research projects optional. The HWs were structured to have one "mastery" question (basics, practice), one theoretical proof question, one implementation question, and a choice between an advanced theory and advanced implementation question. We also brought in new material, and re-ordered the course.
  • Convex Optimization (PhD course) (Fall'12) - Geoff Gordon and Ryan Tibshirani
    Duties of the four TAs included designing homeworks and solutions from scratch, designing exams, grading homeworks and exams, conducting weekly recitations, holding weekly office hours, guiding and grading several project groups, taking videos, organizing scribes, maintaing the website, etc.

Videos

Here is a set of short remedial videos that are suitable to review pre-requisite material (that one has learnt but forgotten) before an introductory graduate course in machine learning. There are 4 sets of videos - one each on multivariate calculus, multivariate probability/statistics, real/functional analysis and the singular value decomposition. Each set consists of 3 videos, usually around 12-15 minutes long. All videos are hosted on Youtube, and the videos page has a description of prerequisites for the videos and what they cover.


Guest Lectures


Future Faculty Program (in progress)

A fantastic program run by CMU's Eberly Teaching Center for aspiring faculty
Observations
  • Classroom Teaching Observation (Spring '14)
  • Microteaching Workshop (Spring '14)
Core
  • Planning and Delivering Effective Lectures (Fall '14)
  • Course and Syllabus Design Seminar (Summer '14)
Elective
  • Promoting Peer Learning (Fall '14)
  • Syllabus Workshop (Summer '14)
  • Crafting a Teaching Statement Seminar (Summer '14)
  • Building a Teaching Portfolio Seminar (Spring '14)