Seeking Software Engineering & AI/ML Internships

Aidan Michael Allen

Quantitative Math Rigor × Software Engineering

M.S. in Computer Science & Engineering student at Santa Clara University with a double major B.S. in Computer Science and Mathematics from California Lutheran University (Cum Laude, Presidential Scholar). Former NCAA D-III Men's Golf Captain combining native iOS app development, systems engineering, and statistical modeling.

Move cursor across the screen to rotate 3D world & dynamic physics meshes
Leadership

NCAA Golf Captain

Cal Lutheran D-III | 18-20 hrs/wk maintaining 3.5 GPA

Education

MS CS & Engineering

Santa Clara University (Expected 2028)

Dual Major

BS CS & Mathematics

Cum Laude, Presidential Scholar Recipient

Proficiency

Java, Swift & Python

iOS Mobile, Statistical Models & Robotics

// PORTFOLIO SHOWCASE

Featured Projects & Capstones

Mathematics Capstone | 2025

Strokes Gained Regression & Ranking Model

This interactive model demonstrates the adjusted ranking equation developed in my mathematics capstone. It uses four Strokes Gained categories to calculate a predicted round score. Adjust the category values to see how each one influences the result.

// ADJUSTED RANKING MODEL EQUATION

Predicted Score =

70.26386678 - 0.5(OTT) - 0.5(APP) - 0.5(ARG) - 0.25(PUTT)

The adjusted coefficients were selected to reduce the average ranking difference when compared with FedEx Cup standings.

Strokes Gained Inputs

+0.771

Performance on tee shots on par 4s and par 5s.

+0.626

Performance on shots toward the green and tee shots on par 3s.

+0.222

Performance on shots within 50 yards of the green.

+0.495

Performance on shots taken on the putting surface.

Positive Strokes Gained values indicate performance above the benchmark. Because the model uses negative coefficients, higher Strokes Gained values reduce the predicted score.

MODEL OUTPUT

Predicted Round Score

69.3306

Lower predicted scores indicate stronger modeled performance.

Coefficient Contributions

SCORE IMPACT
Off the Tee (-0.5) -0.3855
Approach (-0.5) -0.3130
Around the Green (-0.5) -0.1110
Putting (-0.25) -0.1238
Model Intercept 70.26386678
2022 RORY MCILROY EXAMPLE

The default inputs reproduce the 2022 Rory McIlroy example from my capstone presentation. His Strokes Gained values produce a predicted score of approximately 69.3306, which was ranked first in the model's 2022 top-ten comparison.

Original Regression Models

Before developing the adjusted ranking model, I constructed two multiple linear regression models using Strokes Gained categories to predict total round score.

Individual Player Regression

Original regression coefficients

SG Off the Tee -1.517114257
SG Approach -0.7539111244
SG Around the Green -0.1501375134
SG Putting -1.059062787
Overall Player Regression

Original regression coefficients

SG Off the Tee -0.6301947264
SG Approach -0.5803066787
SG Around the Green -0.9593203519
SG Putting -1.353153833

The coefficients above belong to the original regression models. The interactive calculator uses the separate adjusted ranking model coefficients shown in the equation above.

FedEx Cup Ranking Comparison

I used predicted scores to create player rankings and compared those rankings against the actual PGA Tour FedEx Cup standings. The ranking model coefficients were adjusted by 0.25 to reduce the average ranking difference.

2022

1.9 / 1.7

Reported average ranking differences

2023

2.69 / 2.53

Reported average ranking differences

2024

2.38 / 2.53

Reported average ranking differences

Each pair represents the two average ranking difference figures reported in the capstone presentation.

Model Limitations

  • • Limited sample size.
  • • Regression dataset focused on the 2024 season, creating potential seasonal bias.
  • • Does not account for weather, course difficulty, or course length.
  • • Ranking comparison focused on the top ten rather than the entire PGA Tour standings.

Future Improvements

  • • Expand the dataset to include more seasons and players.
  • • Incorporate course difficulty and weather variables.
  • • Apply machine learning models.
  • • Develop an application or interface for easier player analysis.

// TECHNICAL CAPABILITIES

Skills Matrix

Programming Languages

iOS & Dev Tools

Math & Analytics

// CAREER ROADMAP

Work Experience & Leadership

Robotics Data Collection Operator

Oct 2026 - Present

Cobot • Full-time | Santa Clara, CA

  • •Operate robotic hardware to execute tasks and support ongoing development and testing.
  • •Troubleshoot hardware and software issues and identify actionable solutions in real-time.
  • •Develop creative testing approaches to explore new robotics capabilities in a fast-paced environment.

Technical Operations Specialist

June 2026 - July 2026

Summit Creek Capital Partners

  • •Evaluated and implemented company hardware solutions including workstations and monitors.
  • •Configured software systems, deployed company website, and supported core tech infrastructure.
  • •Integrated software tools and APIs to improve system connectivity and operational efficiency.

Biotechnology Research Intern

Aug 2021 - June 2022

MesaGen LLC / Granite Technical Institute

  • •Conducted computational modeling and data analysis examining cell division mechanisms.
  • •Synthesized research findings and presented data in scientific team review sessions.

Collegiate Golf Athlete & Team Captain

Aug 2022 - May 2026

California Lutheran University Men's Golf

  • •Served as team captain; committed 18-20 hours weekly to training and regional/national NCAA competitions while maintaining 3.5 Cum Laude GPA.
  • •Inducted into Chi Alpha Sigma National College Athlete Honor Society.

// GET IN TOUCH

Let's Connect & Build Together

I am currently seeking Software Engineering and AI/ML Internship opportunities where I can apply my quantitative math background and software development skills.

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