• Assist students with learning fundamental computer vision algorithms as well as basic machine learning frameworks necessary for automated understanding of images and videos• Grade homework and provide help across topics such as recognition from images, activity/event recognition from videos, scene segmentation and clustering, motion and tracking, deep learning for images and videos• Organize office hours and weekly reviews for 40 students

• Understand flows on hyperbolic surfaces and 3-manifolds that are chosen randomly• Estimate the “error” of various theorems in geometry and number theory via computer simulation• Develop a connection between the continued Fraction and hyperbolic geometry• Approximate irrational numbers by simulating the path of the cutting sequence as it intersects the Farey Tessellation• Implement mathematical simulations using Python libraries: Pandas, Matplotlib, NumPy

• Organize and run weekly meetings related to programming and computing• Contact and communicate with sponsors and faculty for prizes, guest speakers, and community events• Diversify the learning and networking experience for IU students through collaboration and friendly competition

• Apply Markov Chains and continuous time stochastic processes to simulate procedural content generation.• Observe the advantages and limitations of stochastic models in mimicking human-like content generation• Process and clean hundreds of MIDI files for usable data from Bach’s Well-Tempered Clavier• Utilize a nested hash map data structure to represent two unique stochastic processes• Implement stochastic models in Python utilizing both continuous and discrete time spaces to artificially compose classical music