Projects:

EECS 485 P4-P5: MapReduce and Web Search Engine

Utilized Python multithreading and a MapReduce framework to build an efficient document analysis pipeline.
Constructed an indexing API on top of document analysis results using Python Networking and Flask to quickly deliver data to a search engine frontend.
Designed a search frontend to pull links at scale from a SQL Database using Python and Flask.

Caption: The web interface for the search model

EECS 280 P5: Machine Learning

Built an efficient Binary Search Tree data structure using recursion for search to store values in a Map.
Implemented a Map data structure to easily query through large datasets.
Created a Bag of Words machine learning model to classify forum posts by category based on category word frequency.

Caption: Some of the test data ran through the model

EECS 281 P4: Pokémon Traveling Salesperson Problem (TSP)

Engineered a Minimum Spanning Tree algorithm between a set of Pokémon nodes
Coded a Nearest Neighbor TSP algorithm to quickly find a non-optimal TSP route between Pokémon nodes
Devised an Optimal TSP algorithm using a Branch and Bound framework to find an optimal TSP route between Pokémon nodes

Caption: Some (cropped) optimal TSP output. The top line is total path length, the bottom line is the path between node indexes.

Note: I am aware of my lack of personal projects beyond internships and class, and am working to remedy it as much as possible! Stay tuned, and check this page and my blog frequently :).

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