Richard Kublik

Tenet3 is an R&D software and services company supporting the government and the defense industry. We build secure software platforms to help organizations collect, organize, model, and understand the structure and information about their complex systems and processes. Our R&D services produce tailored quantitative analytics, grounded in statistics and computer science, and fed by data, to provide decision support around questions of systems security, criticality, knowledge discovery, trust and assurance.

I can tackle your toughest scientific and technical problems. With a PhD in Applied mathematics and a diverse background I am able to construct a unique solution to your problem, rather than applying a one-size-fits-all approach. - Passionate about learning and applying new technologies and techniques - Effective communicator - Provide high-quality results with positive feedback and recommendations from previous clients and colleagues - Committed to the project’s success and teamwork

As part of the sports analytics team, I worked on various sports analytics projects using Python, R, SQL, and other tools to collect, clean, and analyze large and complex datasets from sources like NextGen Stats, historical betting data, and fantasy sports data.

Octet Research provides modeling and simulation services to help pharma/biotech companies optimize drug development. The company aims at a quantitative understanding of the physiology of health, disease, and the body’s response to drugs through a model-based approach. I volunteered at Octet Research as part of my career exploration where I developed and shared training materials on PK/PD modeling.

Materials Resources, LLC (MRL) specializes in determining the impact of micro scale characteristics of materials on their macro-scale performance. MRL uses an advanced approach that integrates the latest advances in computational science, the principles of materials science, and engineering solutions. As the only software developer at MRL, I was responsible for building the first version of their software that enables users to perform analysis on various materials.

I designed and developed a locally adaptive time stepping (LATS) algorithm that provides improved efficiency over the standard methods currently used in computational neuroscience. The underlying benefit of the LATS method is that the computational cost scales with the amount of activity in the neurons, and not with the size or number of cells. Thus for large systems with sparse activity, the LATS method provides a substantial reduction in computational cost compared to traditional methods.

Type 1 Diabetes occurs when the immune system attacks and destroys the insulin producing beta-cells in the pancreas. One theory suggests that under specific conditions, a naturally occurring period of programmed cell death can cause the immune system to target the beta-cells. We constructed a mathematical model and through a combination of numerical simulations and dynamical systems analysis, we determined conditions under which the model predictions support the initial theory.

Trumpet and Piano