I've been lucky to have had the opportunity to teach, mentor, and work with a number of smart and motivated students. Quite a few of these opportunities presented themselves as TAships that I've held over the years while others have come in the form of collaborations that I've had with fellow students.
- Fall 2019, 2018: Data Analytics for Engineers (COE 3803)
DAE was an interdisciplinary, introductory machine learning and data science class aimed at undergraduate juniors and seniors across the College of Engineering at GaTech. In addition to carrying out the usual TA responsibilities of holding office hours, grading homework, etc. I was also actively involved in the development of the course material and running of DAE by virtue of it being a new course taught by my (former) advisor Dr. Eva Dyer along with Dr. A.J. Medford!
- Spring 2018: Mathematical Foundations of Data Science (ECE 4813)
MFDS was a new, special topics course taught by Dr. Kiryung Lee which introduced senior ECE undergraduates to a number of foundational topics in machine learning and data science. I was the sole TA for the class and had the responsibility of grading homework and conducting (some of my most popular and appreciated) office hours.
- Summer 2021: Professional and Technical Communications for ECE (ECE 3005)
ECE 3005 prepares students for advanced communication tasks required in academic and professional settings. I was mainly responsible for grading homework and providing feedback on various forms of deliverables including but not limited to resumes, presentations, and technical documentation/reports.
- Spring 2024: Linear Algebra (MATH 1554, MATH 3406)
Typical linear algebra courses covering material ranging from vector spaces and geometry of real spaces to orthogonality, SVD, to least squares and preliminary materials on Markov chains.
- June 2019: Hands-On Tech Day Camp, GaTech. [Github repository]
H.O.T. Days @ Georgia Tech is a one-week-long summer day camp designed to expose students attending high schools in Georgia to electrical and computer engineering (ECE) concepts and their various applications. Under Dr. Eva Dyer & Dr. Mark Davenport, I had the opportunity to introduce ~40 rising high school juniors/seniors to image processing, convolutional neural networks, and style transfer.
- May 2019: Deep Learning for Microscopy Image Analysis, Marine Biological Laboratory
DL@MBL is a short summer course meant to familiarize researchers in the life sciences with state-of-the-art deep learning techniques, tools, and frameworks that could be used to solve problems involving microscopy image analysis in their research. I was happy to accompany Dr. Dyer (who was a course faculty member) as one of her TAs in 2019, and worked with the attendees during labs covering topics ranging from introductory image processing to advanced deep learning models for image denoising, segmentation and classification. I also had the chance to eat some great sea food and tour the Marine Biological Lab + Woods Hole during my visit!
- June/July 2016: Embedded Systems and IoT, Eduvance.
I had the opportunity to serve as one of the junior instructors for the Summer 2016 offering of Summer Industrial Training and Internship Program in Embedded Systems and IoT, a month long course conducted by Eduvance in collaboration with the ARM University Program, Cypress University Alliance, and Microchip Technologies. The course introduced rising seniors pursuing ECE and other related majors to embedded systems in both theory and practice with the intention of making them better prepared to execute their senior design projects.
- Joseph Miano: During his time as an undergrad at GT, Joe and I collaborated on a project dealing with multi-scale representation learning of X-ray microtomogrphy data. Our work together eventually led to a paper presented at ICIP 2021, and an extended abstract that was presented at BioImage Informatics 2019. Joe's contribution to this project formed a significant chunk of his undergraduate thesis.
- Suhee Cho: Suhee and I collaborated during her visit to Georgia Tech as an exchange student through her home university, KAIST, in South Korea. We worked together on my project studying the architectural biases of the canonical cortical microcircuit under the purview of predictive coding, leading to a journal paper and a Cosyne talk (as well as a conference poster presentation for Suhee herself!). Suhee is now at Dr. Jay McClelland's lab at Stanford!