• Chandler Smith - Research Engineer at the Cooperative AI Foundation (Present)
• Andrei Muresanu - AI Research Scientist at Vector Institute (Present)
• Nikhil Chandak - Ph.D. student at Max Planck Institute (Present)
• Eunseo Choi - S.M. Student at Massachusetts Institute of Technology (Present)
• Mehul Damani - Ph.D. Student at Massachusetts Institute of Technology (2023-2024)
• Kartik Sharma - Ph.D. Student at Georgia Institute of Technology (Present)
• Zhou Fan - Ph.D. Student at Harvard University (2022)
• Rahul Duggal - Ph.D. Student at Georgia Institute of Technology (2020)
• Jiachen Yang - Ph.D. Student at Georgia Institute of Technology (2018-20)
• Prasenjeet Biswal - MS Student at Georgia Institute of Technology (2018)
• Jenna Kwon - Undergraduate Researcher at Georgia Institute of Technology (2016-17)

CSE 6740: Computational Data Analytics/Machine Learning

Graduate Student Instructor and Head Teaching Assistant (Class of 200 students), Georgia Tech, Fall 2018

Focused on Theoretical/computational foundations of analyzing large/complex modern datasets, including the fundamental concepts of machine learning and data mining needed for both research and practice. As a co-instructor, I helped design the course structure and materials, conducted several lectures and managed a team of 6 teaching assistants.

CSE 6240: Topics in Temporal Point Process, Optimal Transport and GANs

Teaching Assistant (class of 20 PhD students), Georgia Tech, Spring 2018

Covered advanced topics in machine learning, including Point processes and event sequence analysis, Optimal transport and Wasserstein learning and Particle filters and data assimilation. Students were expected to produce interesting research results in the form of a publishable paper and as a TA, I prepared problem sets, conducted review sessions, and mentored student teams to work towards a research paper.

CSE 6740: Computational Data Analytics/Machine Learning

Head Teaching Assistant (Class of 150 students), Georgia Tech, Fall 2016

As a TA, I created weekly quizzes, developed hands-on homework programming assignments, brainstormed and provided feedback on project proposals, graded all materials in the course, and conducted lectures on Sequential Models, Support Vector Machines, Dimensionality Reduction for Manifold data, Neural Networks and Deep Learning.

CSE 6240: Web Search and Text Mining

Taught by Prof. Srijan Kumar, Spring 2020

Conducted Guest Lectures on Temporal Graph Representation Learning