Portfolio

Gee-nomics (C++)

• Built a class that implemented a Trie-based multi-map
• Worked with files that contained ~3 million bases (e.g. Ferroglobus_placidus's genome), storing the information in tries
• Searched the tries and found exact matches and SNiPs (single nucleotide polymorphisms, i.e. an exact match excluding one base) of short DNA sequences

Modeling and Predicting Stroke (Python in Jupyter Notebook)

• Visualized and preprocessed the data (imputing, resampling, normalizing, encoding features, and crossing features)
• Trained models (logistic regression, neural network, spuport vector machine, and decision tree) and evaluated accuracy
• Applied techniques such as PCA and bootstrap aggregation

Sokoban Solver (LISP)

• Checked if the end condition of the search problem had been met, i.e. all the boxes and the keeper are on goal positions (goal-test)
• Took the current state and generated all the possible states that could be reached in one move (next-states)
• Wrote an admissible heuristic that adds a high cost for moves that would make the game unsolvable (heuristic305110110)
• Generated some test cases according to the following mapping: blank=0, wall=1, box=2, keeper=3, goal=4, box+goal=5, keeper+goal=6

Zombie Dash (C++)

• Built the backend of a game called Zombie Dash by writing classes using polymorphism and managing the interaction between objects
• One example is determining object overlap vs object intersect. The first uses Euclidean distance between the center of two objects and the second uses a bounding box surrounding the objects