Robert Kwapich

Let me introduce myself.

I am a machine learning engineer coming from a diverse academic environment. My interests include theoretical and pragmatic aspects of applying modern deep learning solutions to complex, and data-intensive problems.

I have five years of experience in data-driven research, from problem formulation, data acquisition through data engineering, statistical analyses, optimal model architecture, and hyperparameter search, through visualizations and reporting to a broad audience of diverse backgrounds.

I think of my background and experience as a series of interlocking projects with an underlying and unifying theme. Data is inseparable from what we want to discover, how we get there, and the audience that perceives it. Problems, projects, and tech stacks are continuously changing to address the rising demands. However, the principles remain the same.

As a constantly growing engineer, I strive for excellence and proficiency in methods that help address the problem. My first task is always to understand the complexity and scope of the problem, then identify the tools and techniques best suited to address it. Over the years, I have been fortunate to collaborate with excellent investigators and managers on fascinating and complex projects ranging from gait analysis, the human microbiome, familial polygenic risk factors in autoimmune diseases to brain states during sleep-wake cycles. I have contributed a small, significant brick to the wall of knowledge in much more extensive endeavors.

Curriculum vitae

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Skills

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Projects

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