Calculation Consulting

Haas lecture: UC Berkeley, 2014

Dr. Martin has been teaching Data Science for years at top universities like Stanford and UC berkeley.

An early pioneer in Machine Learning, in this lecture, we present a case study of Demand Media, the first Billion dollar IPO since Google--and former client

Demand Media
Case study

the first $1B IPO since Google

Data Science Leadership
Why data science is different

our process and approach

Questions & Answers
What we really do

look for answers here

More Lectures and Podcasts: Haas 2015 ; UC Berkeley 2018 ; Tech Emergence Podcast ; The Innovators / KSZU Stanford Radio ;

Public Talks: AI Research, Strategy, and Outreach

Dr. Martin presents regularly at major scientific AI conferences, top universities, and public forums

Why Deep Learning Works
Stanford Research Lecture Jan 2020

Our collaborative research with UC Berkeley to provide a new, practical theory of Deep Learning and useful tools for AI developers

AI and Machine Learing for Startups
Nov 2018

French Tech Hub Startup Accelerator

Artificial Intelligence: implications for society
Sept 2017

Stanford Palo Alto Rotary Club

Even More Lectures and Podcasts: FutureTech Podcast ; Stanford Golub Lecture ; ICML 2019 Lecture ; KDD 2019 Lecture ; Data Science at Home Podcast; Emerj Podcast

My story

A Lifetime of Data Science and Machine Learning.

The Beginning

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.
1990-1994

PhD, University of Chicago

Charles received his PhD at the world renowned University of Chicago in Theoretical Chemical Physics, using computational quantum field theory to understand the foundations of semiempirical molecular electronic structure. His work bridged the gap between first principles theory and industrial models.

bringing theory and practice together
1995-1998

NSF Postdoc

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

Bubble 1: 1999-2004

The Early Years

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
Bubble 2: 2006-2008

the Lean Startup conjecture

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
Bubble 3: 2010 to present

Machine Learning goes mainstream

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.

What I love -- Data Science, Machine Learning, and AI -- has gone mainstream.
So I decided to start an agency and help other companies change the world through science.

Bubble 1: 1999-2004

The Early Years

We help leading companies get ROI from Data

Haas lecture: UC Berkeley, 2014

Dr. Martin has been teaching Data Science for years at top universities like Stanford and UC berkeley.

Demand Media
Case study

Data Science Leadership
Why data science is different

Questions & Answers
What we really do

Public Talks: AI Research, Strategy, and Outreach

Dr. Martin presents regularly at major scientific AI conferences, top universities, and public forums

Why Deep Learning Works
Stanford Research Lecture Jan 2020

AI and Machine Learing for Startups
Nov 2018

Artificial Intelligence: implications for society
Sept 2017

Services

We are a boutique consultancy and software development shop
specializing in machine learning and data science. Let us help you ...

Strategy

Data Science

Product Development

My story

A Lifetime of Data Science and Machine Learning.

The Beginning

1990-1994

PhD, University of Chicago

1995-1998

NSF Postdoc

Bubble 2: 2006-2008

the Lean Startup conjecture

Bubble 3: 2010 to present

Machine Learning goes mainstream

write your data science story today

My team is your team

PhDs, hackers, and production engineers working together to get your ideas launched

Charles H. Martin, PhD
chief scientist

Staff
engineers extraordinaire

Thi Nguyen
office director

Contact Us

info@calculationconsulting.com

or find us on Quora, YouTube, LinkedIn, etc.

Haas lecture: UC Berkeley, 2014

Dr. Martin has been teaching Data Science for years at top universities like Stanford and UC berkeley.

Demand MediaCase study

Data Science LeadershipWhy data science is different

Questions & Answers What we really do

Public Talks: AI Research, Strategy, and Outreach

Dr. Martin presents regularly at major scientific AI conferences, top universities, and public forums

Why Deep Learning WorksStanford Research Lecture Jan 2020

AI and Machine Learing for StartupsNov 2018

Artificial Intelligence: implications for society Sept 2017

Services

We are a boutique consultancy and software development shopspecializing in machine learning and data science. Let us help you ...

Strategy

Data Science

Product Development

My story

A Lifetime of Data Science and Machine Learning.

The Beginning

1990-1994

PhD, University of Chicago

1995-1998

NSF Postdoc

Bubble 1: 1999-2004

The Early Years

Bubble 2: 2006-2008

the Lean Startup conjecture

Bubble 3: 2010 to present

Machine Learning goes mainstream

write your data science story today

My team is your team

PhDs, hackers, and production engineers working together to get your ideas launched

Charles H. Martin, PhDchief scientist

Staffengineers extraordinaire

Thi Nguyenoffice director

Contact Us

info@calculationconsulting.com

or find us on Quora, YouTube, LinkedIn, etc.

Demand Media
Case study

Data Science Leadership
Why data science is different

Questions & Answers
What we really do

Why Deep Learning Works
Stanford Research Lecture Jan 2020

AI and Machine Learing for Startups
Nov 2018

Artificial Intelligence: implications for society
Sept 2017

We are a boutique consultancy and software development shop
specializing in machine learning and data science. Let us help you ...

Charles H. Martin, PhD
chief scientist

Staff
engineers extraordinaire

Thi Nguyen
office director