🎓 Yale University Graduate

• Master’s in Technology Management from the Yale School of Management, Inaugural Class of 2025
• B.S. in Computer Science & Mathematics from Yale Collge, Class of 2024

💻 AI/ML & LLM Specialist | Technology Fellow at Palantir Technologies| Technical Program Manager | College and Tech Mentor

I’m a recent graduate from Yale University that combines a corporate background in large-scale technology deployment and operations with hands-on technical expertise in AI, ML, LLMs, and software development. On campus, I served as a Teaching Fellow for graduate and undergraduate computer science and AI courses, mentoring students in programming, data structures, and applied machine learning. My work bridges the gap between technical execution and strategic impact, whether in the classroom, in industry, or through ventures like Pathway, an AI-powered platform supporting non-traditional community college and veteran transfers.

Currently participating in Palantir's inaugural American Tech Fellowship (Fall 2025), a selective intensive program focused on enterprise AI deployment and data-driven decision systems. Working hands-on with:

• Palantir Foundry - Advanced data integration and analysis platform
• AIP (Artificial Intelligence Platform) - Enterprise AI deployment for real-world problem solving
• Enterprise Software Development - Building operational workflows and AI-powered automation
• Capstone Project - Developing end-to-end AI solutions for industrial applications

Selected from 500+ applicants for technical expertise and practical innovation mindset.

I bring 10+ years of operations leadership experience to technical product management, having scaled teams and managed complex implementations across global markets. This background, combined with my CS education and growing technical skills, enables me to effectively bridge business strategy with engineering execution in fast-growing technology companies.

• Corporate Operations & Technology Deployment

  • Led enterprise system rollouts across 10+ countries, working with 2,500+ suppliers and 500+ internal stakeholders.
  • Oversaw the deployment of a global product tracker and price modulator in LATAM and EMEA regions.
  • Scaled a retail/wholesale business from 3 to 12 locations, growing sales by 350% in 15 months.

• Entrepreneurship & Innovation

  • Founder of Pathway, an AI-powered platform designed to support community college and veteran students in transferring to four-year institutions.
  • Applied AI/ML and UX design to solve real-world educational challenges.

• Teaching Assistant/Fellow for Yale School of Management & Yale College
  • Supported graduate and undergraduate courses in AI applications, computer science fundamentals, and mathematical techniques.
    • Courses supported included in Artificial Intelligence, Large Language Models, Algorithms, Mathematics for CS, & Information Systems.
  • Designed review materials, graded complex programming assignments, and ran office hours to help students succeed in Python, C, C++, Go, and AI concepts.
  • Mentored students on AI/ML workflows, software engineering best practices, and data structures & algorithms.
  • Organized and led technical workshops, coding reviews, and one-on-one mentoring sessions.

• Languages: Python, C++, C, Go, Rust, JavaScript & others
• AI/ML: PyTorch, TensorFlow, LLMs, NLP, RAG Systems, HuggingFace
• Tools & Systems: Git, Jupyter, Node.js, Agile/Scrum
• Other: Data Analysis, UX Design, Project Management
• Enterprise Platforms (Ongoing): Palantir Foundry, Palantir AIP
• Data Operations (Ongoing): Enterprise data integration, operational workflows, AI-powered dashboards

• Building portfolio of full-stack applications - coming soon
• Pathway (private) – AI-powered transfer support platform for higher education.

I have a deep interest in:

• Linear Algebra for powering data transformations, ML optimizations, and computer vision pipelines.
• Probability Theory & Statistics for driving decision-making under uncertainty, risk modeling, and data analysis for AI systems.
• Harmonic Analysis & Real Analysis for applied in signal processing, neural network theory, and large-scale data interpretation.
• Number Theory & Discrete Mathematics for essential for algorithm design and computational efficiency.
• Formal Proof Writing for ensuring algorithmic correctness, robust system design, and scalable architectures.

At Yale, I conducted self-directed research under the guidance of Professor Ronald Coifman, exploring the connections between harmonic analysis, Fourier methods, and neural network architectures. This work deepened my understanding of how mathematical theory can inform and optimize AI and ML systems, particularly in areas like feature extraction, data compression, and pattern recognition.

In my corporate and technical projects, these fields underpin work in AI model development, predictive analytics, optimization algorithms, and secure systems design. I also plan to release a Mathematics Roadmap for self-directed learners, providing resources and structured pathways for mastering these topics in ways that are directly applicable to technology and industry.

Reach me up at [email protected] or on LinkedIn.