As an independent project, I built a simulation in Python to model the behavior of viral content as it spreads through a social media network. The model investigates key parameters influencing virality, inluding sharing probability and sharing duration. To better mimic real-world factors, I incorporated natural fluctuations in user activity, such as simulating users arbitrarily going online and offline.
Skills: Python, NetworkX, Modeling
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I conducted research into the limitations of industry-standard machine learning interpretability frameworks. In the process, I authored substantial portions of the methods section and contributed visual figures for the research paper, which was published in the April 2024 issue of Proceedings of the ACM on Human-Computer Interaction (PACMHCI).
Skills: Python, Pandas, Research, ML
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I built a visualizer for several heuristics that seek to approximate a solution to the traveling salesperson problem (TSP). I utilized arbitrary insertion to generate a preliminary approximation, and 2-OPT to eliminate path crossings. The visualizer allows users to easily build custom maps with an intuitive input format.
Skills: Python, Numpy, Matplotlib, algorithms
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I built an interactive too with Python and the Pygame library to demonstrate the mechanics of common sorting algorithms. It begins with a randomized array, visually represented by varying heights of columns, to reflect the values being sorted. Users can engage with the algorithms (insertion, selection, and bubble sort) via keypresses, triggering a vivid animation where the current and comparison indices are highlighted in red and green, respectively.
Skills: Python, Pygame, algorithms, data structures
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