Daniel K. Email & Phone Number

Cambrio builds AI (automated intelligence) tools that accelerate your capability to prototype, benchmark, and operationalize analysis workflows. We specialize in complex domains like: life sciences, geospatial, scientific sensors, and healthcare, where deep expertise is required to understand context and "see" things or "read" signals. Because the demand.

Boston, Massachusetts, US

Developed new technology to keep indico on the bleeding edge of AI/machine learning and deep learning (convolutional neural networks, recurrent neural networks, deep vs. wide models, attention, fine tuning, transfer learning, etc). Specifically, I focused on new ways to represent and learn from data when you don't have millions of labeled examples. To.

At a time when wearable devices were all about quantity/counting stuff (steps, miles, heartbeats), Aidetic developed algorithms to measure the shapes of human movements in real-time, using the sensors that were already installed in 1B+ mobile devices. It was a pretty classic early-stage experience: built hardware + software prototypes, designed machine.

Boston, MA, US

I led data science projects as part of the Strategy, Innovation & Analytics organization. Operating as internal consultants, we partnered with business unit managers to understand how business operations could be improved, using data + predictive models. Example: using weather data and historical claims volumes to predict where appraisals will be needed.

City Of London, England, GB

Consulting tech expert for science, engineering, behavioral economics, and computational stuff; scope spanned pre-sales to business development (i.e., partnerships, testing new kinds of products) to actually implementing version 1.0 for new software features. In helping organizations solve technical problems using open innovation, I had a hand in many of.

Before "data science" was a thing, Aentropia was my vehicle to explore challenging computational problems, provide data/consulting engagements, and develop intellectual property.

New York, New York, US

Using huge amounts of proprietary and public data (hundreds of genomes, all kinds of "omics" data), we explained how T-cells behave during various autoimmune diseases. Our model showed how key molecular networks are competitively balanced in the healthy state, and how disease states happen when inflammation pathways disturb the healthy balance.I was also.

St. Louis, MO, US

Dissertation gist: We discovered a solution to a long-standing paradox of molecular biophysics, by using billions of experimental observations and statistical physics to show how protein molecules are predictably flexible. In hindsight, this strategy of using distributed computing tricks to apply a mathematical model to many many observations was an early.

Kansas City, Missouri, US

South San Francisco, California, US

Abbott Park, Illinois, US

Abbott Park, Illinois, US

Ph.D., Biomedical Engineering

Bachelor Of Science (B.S.), Chemical Engineering & Biology