My teaching method is centered around teaching the student how to think critically and learn things on their own. All too often, learners develop a need for handheld instruction, when in reality the best instruction comes from being challenged and having to go above and beyond. I make sure that students are supported at every step of the journey but also encouraged to go and explore difficult topics and build their own projects. I take my time with the fundamentals and ensure that the student understands them very well before moving on to advanced topics. I also like to give a lot of practice problems and projects so that the student is able to develop their skills well.
If a student is preparing for a specific test or exam then I will help them prepare by walking through practice tests and questions. After noting down what they struggle with after a diagnostic exam, we will proceed by focusing in on problem areas and studying them in a detailed manner.
I'm offering tutoring for Math, Programming, and SAT Test Prep to middle and high schoolers over Zoom. I've been tutoring one-on-one for over a year now, and have worked with large groups for longer, having taught over 20 different individuals in the last year through personal tutoring and group sessions. I attended Ardrey Kell high school and then moved on to attend the North Carolina School of Science and Math where I finished with a 4.86 weighted GPA on a 4.0 scale. Throughout my high school career, I excelled in my math classes and took as many advanced ones as I could. I took AP Calculus BC in 10th grade and Multivariable Calculus in 11th grade, along with other advanced classes such as Graph Theory, Number Theory, Group Theory, and Research in Mathematics. I've also been programming since I was in 3rd grade, and among the top computing students in the nation, having competed in the Platinum division of the United States of America Computing Olympiad, which is the highest division. I've also worked on Computer Science and Machine Learning research under professors at the University of Chapel Hill. In 11th grade, I led a team from my school to win the Samsung Solve for Tomorrow National competition against 2000 other schools by developing a mobile app that utilizes machine learning to classify food waste. In addition, I also got a 1550/1600 on my SAT (780 Reading/Writing, 770 Math), an 800/800 on my SAT Math Level 2 Subject test, and a 5/5 on my AP Calculus BC exam. I am also an American Invitational Mathematics Exam (AIME) qualifier.
Rates are negotiable
Georgia Institute of Technology Atlanta, GA (August 2021 Onwards)
- B.S Computer Science
- Concentrations: Intelligence and Theory
North Carolina School of Science and Math Durham, NC (August 2019 - May 2021)
- High School Degree
- GPA: 4.86
- Relevant Coursework: Multivariable Calculus, Java, Advanced Java, Foundations of Data Science
North Carolina School of Science and Math
Ryden AI Program Teaching Assistant Durham, NC (August 2020-May 2021)
- Lead planning and logistics for a Hackathon catering to 70+ high schoolers from the state of North Carolina
- Developed Machine Learning curriculum for a wide variety of students
- Developed interactive projects to demonstrate AI for social good
UNC Chapel Hill
Research Intern Chapel Hill, NC (June 2020 - August 2020)
- Applied Natural Language Processing techniques to a text classification problem
- Converted large datasets into insightful visualizations
- Worked with PyTorch to construct a Long Short Term Memory Network to classify movie dialogue as
delivered by a male or female character
- Wrote formal research paper summarizing the project
Competitions and Personal Projects
Samsung Solve for Tomorrow Competition (November 2020 - May 2020)
Technologies Used: Python, Tensorflow, Flutter, Dart
- Won national competition as Machine Learning lead for my school’s team
- Utilized Object Detection algorithm to classify waste in the form of an app to make it easier for students on
our campus to recycle.
- Built a cross-platform mobile app using Flutter and Dart that incorporated the tflite object detection algo-
rithm mentioned above.
Implied Volatility Modeling (January 2020)
Technologies Used: PyTorch, Python
- Developed machine learning and deep learning models to predict the implied volatility of options contracts
- Collaborated with others in a team environment utilizing Git and GitHub
- Conducted research into various volatility modeling techniques like SABR
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