Teaching

I teach because I believe learning is transformative. Whether in person or online, higher education is a unique space where students expand their ways of thinking, develop critical skills, and redefine their sense of what is possible. As an instructor, my core philosophy is that teaching must be designed in service of the student. This means recognizing that learners come from diverse backgrounds with varied levels of preparation, confidence, and motivation, and intentionally building pathways that support each student’s success. Effective instruction begins not with content delivery, but with a commitment to students’ growth and intellectual development.

My teaching philosophy is grounded in student-centered design and equity-minded pedagogy. I draw on the framework of backward design as articulated by Wiggins and McTighe (2005), which emphasizes identifying clear learning outcomes and then aligning instruction and assessment strategies with those goals. This model ensures that every component of a course—lectures, assignments, feedback—supports the specific skills and knowledge students are expected to develop. It also reinforces the principle that teaching should be evaluated by what students genuinely learn, not simply by what is “covered.”

Equally important is acknowledging that students do not all start in the same place. As Ambrose et al. (2010) emphasize in How Learning Works, students bring a wide range of prior knowledge, beliefs, identities, and experiences that shape their learning. My responsibility is to recognize these differences and create inclusive environments in which all students have the opportunity to thrive. This includes maintaining clear and transparent course structures, offering flexible modes of engagement, and combining foundational support with meaningful academic challenge.

Instructional Methods and Learning Design

My instructional approach emphasizes active learning, frequent feedback, and metacognitive reflection. I design courses around a flipped classroom model, where students engage with core materials—such as readings, video lectures, or guided walkthroughs—before synchronous sessions like class meetings or office hours. This design ensures that our live interactions focus on application, clarification, and collaborative problem-solving. In both in-person and online formats, I incorporate short in-class quizzes, breakout discussions, and structured peer activities to reinforce core concepts and promote engaged learning.

Assignments are scaffolded to support deep learning and sustained intellectual growth. Early-stage exercises provide accessible entry points into complex material, meeting students at various levels of experience. As the course progresses, students encounter layered challenges that involve synthesis, abstraction, and independent exploration. Major assignments serve as low-stakes practicums, encouraging students to apply course content to industry-relevant problems. These projects are intentionally sequenced: students move from learning how to read and critique research papers, to articulating hypotheses, designing experiments, and developing nuanced discussions grounded in theory. Graduates frequently report that this structured, open-ended project model builds both confidence and competence in their professional applications of machine learning.

Teaching at Scale and in Online Environments

In my role as Instructor of Record for CS7641: Machine Learning and CS7642: Reinforcement Learning in Georgia Tech’s OMSCS program, I have taught and supported thousands of graduate students. These courses are integral to the Machine Learning specialization and are consistently among the largest and most active offerings at Georgia Tech, with a high volume of students progressing through them each semester. Leading these courses has deepened my understanding of how to deliver rigorous, high-quality instruction at scale while maintaining personal connection and responsiveness.

My responsibilities extend beyond teaching content. I lead large instructional teams, oversee ongoing curriculum development, and mentor new teaching assistants as they enter the program. I work closely with TAs to ensure consistency in grading and communication, and I routinely analyze student performance data to identify common challenges and adapt our support strategies. This feedback-driven process allows me to refine both course materials and the overall learning experience across diverse delivery formats and learner backgrounds.

Teaching at scale has also reinforced the importance of accessibility and inclusion. In asynchronous, online environments, students may feel disconnected from their peers and instructors. To address this, I establish clear and predictable rhythms: weekly updates, structured checkpoints, and dependable office hour availability. I also create space for student voice through discussion prompts, mid-course surveys, and reflective check-ins at the end of each module. These channels provide insight into students’ needs while reinforcing a sense of belonging and support, even in large, distributed classrooms.

References

1. Wiggins, G., & McTighe, J. (2005). Understanding by Design. ASCD.
2. Ambrose, S. A., et al. (2010). How Learning Works. Jossey-Bass.