ML&DS

NeoViews - Predicting Soccer Player Locations

  • Description: Developed a Long Short-Term Memory (LSTM) model to accurately predict soccer player locations throughout an entire match, achieving a prediction accuracy within 10 meters. Benchmarked the model against various optimization methods, including Bayesian optimization and linear regression, to evaluate performance improvements and accuracy.

  • Media:

soccer ML

Pathfinding Algorithms Visualization

  • Description: Developed a visualization tool for Q-learning and Dijkstra's algorithms, focusing on practical applications of reinforcement learning in navigation and optimization tasks.

dakotacsk/PIE_ShortestPathFindingVisualization - GitHub

  • Media:

HVAC System Optimization

  • Description: Utilized ML and physics-based modeling to optimize energy use in air handling units (AHUs), integrating data science to enhance building sustainability. This includes leveraging an ensemble model (GBR, LSTM, Batch-RL, etc.) to create the best result for the complex system. Project is currently being evaluated in the physical HVAC system of a building.
  • Media:
    HVAC System Optimization

Laplacian Over Gaussian Operator

  • Description: Developed a Python package for edge detection using the Laplacian of Gaussian (LoG) method to demonstrate image processing concepts with a packet of teaching materials to explain the mathematical basis of LoG. Includes customizable filters, example scripts, slides, a simple paper write up, a math proof, etc.

dakotacsk/LaplacianOverGaussianOperator - GitHub

  • Media: An image of Olin College's Miller Academic Center with LoG applied

Data Science Journal

  • Description: Documented data visualization projects using tools such as Python (pandas, matplotlib, etc.), Excel, and Tableau, creating interactive network graphs, animated graphs, and more.
  • Skills: Data Engineering, Data Visualization
  • Link: Data Science Journal

The Phillipian State of The Academy

  • Description: Led data analysis of a student survey with 80.5% participation, finding correlations using Python and libraries like pandas and numpy, and visualizing data.
  • Skills: Data Engineering (Python), Data Visualization (HTML/CSS/JS)
  • Link: Visit Project