CV

Education

• Incoming Ph.D. Student at The University of Texas at Austin, Fall 2025
• M.S. Data Science, Columbia University, 2023
• B.S. Computer Science, The University of Texas at Austin, 2022

Publications

Discovering Effective Policies for Land-Use Planning with Neuroevolution

D. Young et al., “Discovering effective policies for land-use planning with neuroevolution,” Environmental Data Science, vol. 4, p. e30, 2025. doi:10.1017/eds.2025.18

Experience

• Summer 2023 - Current: Cognizant AI Lab - Data Scientist
  • Research and develop machine learning-based solutions to global challenges such as climate change using automatic decision-making methods such as evolutionary search
  • Contributor to Project Resilience - a collaboration with the UN to use AI for sustainable development
• Fall 2023: Columbia University - Complex Resilient Intelligent Systems Lab - Student Researcher
  • Analyzed weights of deep CNNs to identify alignment with an optimal maximum entropy distribution, then modified SGD to use this alignment to converge in less iterations.
• Summer 2022: University of Texas at Austin - Stephen Yi Lab - Student Researcher
  • Processed germline and somatic mutations and compared deleterious effects using statistical methods.
• Summer 2020: Amazon - Devices Team - SDE Intern
  • Designed camera setup and created real-time video stitching application for preliminary use in driving.
• Summer 2019: Santa Clara County Technology Services and Solutions - SDE Intern
  • Created handwriting reader to automatically process government forms, map services to help senior citizens find programs.

Skills

• Machine Learning
  • Numpy, Pandas, Scikit-Learn
• Deep Learning
  • PyTorch, Huggingface/Transformers, Tensorflow, Keras
• Visualization
  • Matplotlib, Plotly, Dash
• Software Engineering
  • Git, Docker, React, SQLAlchemy, Selenium, Gitlab CI/CD, AWS Deployment, Agile Methodologies