CV

Summary

Data Scientist at EVident Battery with a strong background in machine learning, data science, and a passion for tackling practical challenges with AI. Equipped with 7 years of experience in Python and relevant libraries including Pandas, TensorFlow, and PyTorch, applying advanced deep learning techniques to solve real-world problems. M.S. in computer science at Yale University and a summa cum laude graduate of Tulane University.

Education

• M.S. in Computer Science, Yale University, 2024
  • Relevant Coursework:
    • Trustworthy Deep Learning
    • Topics in Applied ML
    • Natural Language Processing
    • Computer Vision
    • Deep Learning on Graph-Structured Data
• B.S. in Computer Science, B.S. in Mathematics, Tulane University, 2021, summa cum laude
  • Relevant Coursework:
    • Data Science
    • Algorithms
    • Experimental Mathematics
    • C++ for Scientists and Engineers
    • Ordinary Differential Equations

Work Experience

• EVident Battery, Data Scientist (July 2024 - present)
  • Performed data ingestion of multi-dimensional signal data using modern machine learning libraries, carrying out exploratory data analysis and creating effective visualizations to communicate with non-technical investor audiences
  • Fine-tuned and deployed state-of-the-art transformer models capable of diagnosing anomalies in EV battery packs with ~98% accuracy
  • Independently organized the deployment of team software to AWS Elastic Beanstalk, demonstrating proficiency with cloud computing and web hosting tools
• Yale University, Course Manager (August 2022 - May 2024)
  • Lead a team of 20 TAs & responsible for ~150 students in Yale’s Introduction to Computer Science course (CS201).
  • Wrote automated grading scripts using Yale’s Linux clusters, coordinated and hired TAs, developed novel curriculum material/exams, and acted as a reliable point of contact for students and TAs alike.
  • Sharpened leadership skills and facilitated a comfortable and efficient work environment for students and instructors.
• U.S. Dept. of Veterans Affairs, Bioinformatics Software Engineer (August 2021 - July 2022)
  • Worked both independently and on Agile teams of ~10 developers on Cancer Care Tracking System (CCTS), a production-scale database that tracks cancer symptoms of veterans and makes predictive conclusions.
  • Routinely identified and resolved both visual front-end and logical/database back-end bugs using ASP and SQL respectively.
  • Created an interactive web page using ASP and JavaScript/D3 to visualize the timeliness of care given to patients at VAs across the country.
• Yale Center for Research Computing, Research Support Intern (June - August 2019)
  • Wrote a Slurm command seff-array from scratch in Python to handle job arrays and display statistics about their efficiency in a histogram, enabling all users of Yale supercomputers to request memory more intelligently and saving system time/power for all users.
  • Interfaced with Yale clusters using Python and Slurm to record hardware/partition information into a Pandas dataframe, then converted the data into an automatically updated Markdown table of cluster records.
• Yale Center for Medical Informatics, VR Engineering Intern (June - August 2018)
  • Wrote software in Unity and Blender to model molecules in VR for use in Yale medical research
  • Created a VR environment for bioengineers to analyze small-molecule interaction in proteins
  • Integrated project data with YCMI MySQL server using C#

Technical Skills

• Programming Languages
  • Python
  • C/C++/C#
  • Julia
  • MATLAB
  • SQL
  • ASP/.VB
  • Ruby
• Libraries
  • TensorFlow
  • PyTorch
  • OpenCV
  • NLTK
  • Pandas
  • Numpy
  • CUDA/cuDNN
• Tools and Frameworks
  • Git
  • AWS
  • Microsoft Azure
  • Docker
  • UNIX
  • Slurm