My passion for teaching blossomed during my PhD studies at Northwestern University. As a Teaching Assistant, I discovered the joy of helping students grasp complex concepts and witnessing their growth. Since 2020, I have had the privilege of leading summer courses in Computer Science, eagerly anticipating each opportunity to engage with young minds.
Creating a supportive learning environment that encourages critical thinking, questioning, and exploration is at the heart of my teaching philosophy. I am deeply committed to making learning an engaging and enriching experience for my students, and I find great fulfillment in contributing to their development as scholars and individuals.
Beyond the classroom, I find immense joy in tutoring and mentoring students one-on-one. Whether it’s helping a struggling student overcome a challenging concept or guiding a highly motivated learner to explore advanced topics, I cherish the opportunity to make a positive impact on their academic journey.
As I continue my career, despite not staying in an academic setting, I look forward to further opportunities to share my knowledge and passion with students, fostering their love for learning Computer Vision and helping them achieve their full potential.
| Code | Department | Course | Year | Quarter |
|---|---|---|---|---|
| 331 | CS | Introduction to Computational Photography | 2024 | Summer |
| 396 | CS | Computational Optics Seminar | 2023 | Summer |
| 396 | CS | Advanced Computer Graphics Seminar | 2022 | Winter |
| 331 | CS | Introduction to Computational Photography | 2021 | Summer |
| 349 | CS | Machine Learning | 2020 | Summer |
| Code | Department | Course | Year | Quarter |
|---|---|---|---|---|
| 331 | CS | Introduction to Computational Photography | 2019 | Fall |
| 395 | CS | Computational Photography Seminar | 2020 | Winter |
| 349 | CS | Machine Learning | 2020 | Spring |
When I initially took on a significant role as a co-instructor for the Northwestern NUCS 349: Machine Learning course, the unforeseen challenge of COVID-19 emerged, leading to a surprising rise in enrollment from 80 to 170 students just weeks before the start of the quarter. Faced with this sudden change, I utilized Campuswire to successfully transition the course online, ensuring an engaging and accessible learning experience for all students during the pandemic. This proactive adaptation not only illustrated the potential of well-organized online classes in addressing unexpected educational challenges, but also led to me being entrusted to teach the course as a full instructor by the summer term. For a more in-depth account of this transition, you can explore the news article here.
During my time as a Teaching Assistant for CS331: Introduction to Computational Photography, I was responsible for the transition of the course to an online format in response to the COVID-19 pandemic. This change allowed us to accommodate more participants due to the high demand. For the Fall 2020 term, I created a new set of homework assignments using Python and Jupyter notebooks. The aim was to use Python, a widely used open-source language in Computer Vision research, to gradually introduce students to the various aspects of computational photography, including vision and imaging.
The homework assignments are available for everyone to check out on our GitHub repository.