Doctoral Student & Hagley Scholar
University of Delaware
15 years of experience building machine learning models and developing
generative AI applications for scientific computing.
An experienced engineer specializing in Django, SciPy, and NumPy. My career spans high-performance computing at NASA and CERN to deep research at Harvard University. I focus on making complex data systems private, scalable, and intelligent.
The most powerful AI technologies carry significant ethical and privacy risks that can derail even the most ambitious projects. My consulting practice, Garini LLC, blends 15 years of deep technical execution with the ethical and strategic foresight required for modern enterprise. I specialize in building advanced, secure systems that don’t just work—they align with organizational integrity and long-term project viability.
Having seen the urgent need for technical guardrails firsthand during my research at Harvard University, I co-authored the O’Reilly textbook, Hands-on Differential Privacy. This work serves as the primary curriculum for Harvard’s Applied Privacy for Data Science course. Today, I serve as a strategic consultant and project leader for startups and established firms alike, specializing in architecting and deploying RAG (Retrieval-Augmented Generation) systems and complex language models.
My approach is informed by a rigorous commitment to privacy, technical excellence, and the belief that the best technology is built on a foundation of ethical responsibility.
Expertise in building secure, scalable backend architectures and data-driven platforms. Extensive experience developing Django-based tools for private data analysis at institutions like Harvard.
Specializing in the architecture and deployment of RAG (Retrieval-Augmented Generation) systems and complex LLM pipelines. Designing end-to-end NLP systems and AI ethics governance frameworks since 2011.
Deep technical proficiency in PyTorch, TensorFlow, Keras, and scikit-learn. Experienced in developing predictive models for diverse industries ranging from finance to fitness optimization.
Comprehensive management and configuration of enterprise cloud environments across AWS, Google Cloud (GCP), and Azure. Proven track record in deploying complex machine learning models at scale.
Designing high-performance APIs using FastAPI and Flask to power data-intensive applications. Focused on creating maintainable, low-latency interfaces for scientific computing and SaaS platforms.
Author of Hands-on Differential Privacy (O'Reilly), the textbook used for Harvard’s CS208.
Master of Liberal Arts in Software Engineering from Harvard University and B.Sc. in Physics and Mathematics from UMD.
Former CTO of Flyzen and current Owner of Garini Consulting, specializing in AI-driven project management.
Research and development for global institutions including NASA Goddard and CERN. Specialized in quantum mechanical approximations and high-performance data analysis.
A history of helping early-stage startups navigate critical technology decisions as a Fractional CTO and Principal Research Engineer. Expert in backend architecture design and long-term technical roadmap development.
My technical expertise is forged at the intersection of high-performance scientific research and modern enterprise AI architecture. I leverage a foundation in physics and software engineering to deploy intelligent systems that are as technically robust as they are ethically grounded.
Designing and deploying advanced Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. Specialized in architecting end-to-end AI pipelines for scientific and financial computing since 2011.
Expert implementation of ethical guardrails and differential privacy protocols. Providing strategic consulting to translate organizational values into technical model-building processes.
Managing complex software teams through Agile and Scrum methodologies. Fractional CTO advisory for early-stage startups to navigate key technology, cloud infrastructure (AWS/GCP), and backend decisions.
Leveraging 15 years of experience in artificial intelligence and scientific computing to build secure, ethically-grounded data systems. From NASA simulations to Harvard research, I bridge the gap between complex engineering and strategic foresight.
University of Delaware
Harvard University
Harvard SEAS
Flyzen
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Currently accepting a limited number of advisory calls and development engagements. Whether you’re architecting a new RAG system or need an ethical audit for your AI strategy, let’s connect.