Hi there! I'm Adam Stogsdill (He/Him). I'm a Biotechnical AI/ML Engineer at RAIsonance. Currently interested in joining a PhD program in AI focusing on medical data and diagnostics.

Private Email: adam.stogsdill@gmail.com

Link

Below is a step-by-step path of a mathematical journey that I will take to enhance and solidify my mathematical foundations and help reach profiency in advanced statistical methods.

Step 1: Master the Foundations

• Introduction to Proof Techniques:
  • Resources:
    • Textbook: "How to Prove It: A Structured Approach" by Daniel J. Velleman
    • Online Course: "Introduction to Mathematical Proofs" by Khan Academy
• Discrete Mathematics:
  • Resources:
    • Textbook: "Discrete Mathematics and Its Applications" by Kenneth H. Rosen
    • Online Course: "Discrete Mathematics" by MIT OpenCourseware
• Linear Algebra:
  • Resources:
    • Textbook: "Linear Algebra Done Right" by Sheldon Axler
    • Online Course: "MIT OpenCourseware 18.06: Linear Algebra"

Step 2: Deepen Your Understanding with Core Mathematics

• Calculus I, II, III:
  • Resources:
    • Textbook: "Calculus: Early Transcendentals" by James Stewart
    • Online Course: "Calculus" by Khan Academy
• Real Analysis:
  • Resources:
    • Textbook: "Principles of Mathematical Analysis" by Walter Rudin
    • Online Course: "Real Analysis" by MIT OpenCourseware
• Complex Analysis:
  • Resources:
    • Textbook: "Complex Analysis" by Lars Ahlfors
    • Online Course: "Complex Analysis" by MIT OpenCourseware
• Abstract Algebra:
  • Resources:
    • Textbook: "Abstract Algebra" by David S. Dummit and Richard M. Foote
    • Online Course: "Abstract Algebra" by Stanford University

Step 3: Explore Advanced Topics

• Number Theory:
  • Resources:
    • Textbook: "Elementary Number Theory" by David M. Burton
    • Online Course: "Number Theory" by Khan Academy
• Differential Equations:
  • Resources:
    • Textbook: "Differential Equations with Applications and Historical Notes" by George F. Simmons
    • Online Course: "Differential Equations" by MIT OpenCourseware
• Topology:
  • Resources:
    • Textbook: "Topology" by James Munkres
    • Online Course: "Topology" by Stanford University
• Statistical Learning:
  • Resources:
    • Textbook: "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman
    • Online Course: "Machine Learning" by Andrew Ng on Coursera

Step 4: Enhance Your Skills with Specialized Subjects

• Combinatorics:
  • Resources:
    • Textbook: "A Combinatorial Miscellany" by T. P. McDonough
    • Online Course: "Combinatorics" by MIT OpenCourseware
• Optimization:
  • Resources:
    • Textbook: "Introduction to Linear Optimization" by Dimitris Bertsimas and John N. Tsitsiklis
    • Online Course: "Linear Optimization" by MIT OpenCourseware
• Numerical Analysis:
  • Resources:
    • Textbook: "Numerical Analysis" by Richard L. Burden and J. Douglas Faires
    • Online Course: "Numerical Methods for Scientists and Engineers" by edX
• Mathematical Modeling:
  • Resources:
    • Textbook: "Mathematical Modeling" by J. N. Kapur
    • Online Course: "Applied Mathematical Modeling" by Duke University on Coursera