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design new products and predict revenue from your data and your customer's data.
set up a big data solution and apply machine learning algorithms to discover the patterns that drive traffic, engagement, and sales.
build and deploy modern, end-to-end, cloud-based software systems.
Turning Information into Intelligence that can be Implemented for you and your customers.
Charles started college classes in organic and physical chemistry at 15. He enrolled at the Ohio State University and immediately started working in a theoretical chemistry group because they had a Cray Supercomputer. Still a teenager, he took first place in the SIAM National Applied Math Contest. His research involved non-equilibrium statistical mechanics, and in his first publication
he invented a new kind of Monte Carlo simulation.
Charles received his PhD at the world renowned University of Chicago in Theoretical Chemical Physics, using computational quantum field theory to understand
bringing theory and practice together
Dr. Martin was an NSF Postdoctoral Fellow -- 1 of 2 nationwide -- in theoretical chemistry. He went to UIUC to work in a theoretical physics & chemistry group, studying computational neuroscience and neural networks. He published several single author papers, a 100 page review on computational quantum mechanics, and even built a neuromorpic chip which has been featured recently.
Today he is collaborating with data science researches at Berkeley, and is
an authority on Why Deep Learning Works.
FutureTech Podcast Stanford Golub Lecture
Inspired by the power of machine learning, Dr. Martin came to Silicon Valley in 1999 to work with eSelf, a machine learning startup building a personalized search engine using semi-supervised algorithms.
Seeing the power of machine learning, he started consulting for large firms like Roche, France Telecom and eBay as a subject matter expert (SME) in machine learning. At eBay, Dr. Martin pioneered the use of structural SVMs for search relevance.
An early adopter of Machine Learning in industry
What really goes on at a successful startup? We can tell you because our chief scientist was at Aardvark--a lean startup case study,
and acquired by Google for $50M. Building on his work on search relevance at eBay, Dr. Martin brought production level machine earning to the early Aardvark product.
understanding what startups need
Before the acquisition, he was recruited to work in the very prestigious Active Equities Group (Barclays)--the group that invented the index fund. BGI was acquired by Blackrock, the largest financial institution in the world. Dr. Martin developed several machine learning algorithms to predict the markets (portable alpha).
think like a quant--generate revenue
In 2010, Dr. Martin left Blackrock to consult for the late stage startup Demand Media (the brainchild of Richard Rosenblatt, former chairman of MySpace). Within a few weeks of joining, he created a machine learning algorithm that revolutionized their growth, kick started bubble 3, and changed SEO forever. In 2011 ...
Demand Media was the first $1B IPO since Google.
Since then, he has supported many large clients, including GLG, Mode Media, Swoop, and GoDaddy, and several early stage startups.
you will work directly with a hands on expert in data science and machine learning
my software engineers and data geeks have world class training in computer engineering
she keeps the wheels turning and makes sure everyone is on task
"hiring PhD’s is crucial: they have the training to work deeply and autonomously on hard problems that you need to solve to be competitive"