Our Leadership

Christopher Bouton, Ph.D.


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Dr. Bouton received his BA in Neuroscience (Magna Cum Laude) from Amherst College in 1996 and his Ph.D. in Molecular Neurobiology from Johns Hopkins University in 2001. Dr. Bouton is the CEO of Vyasa Analytics, applying novel deep learning approaches for enterprise clients.

Previously Dr. Bouton was the CEO of Entagen a software company founded in 2008 that provided innovative Big Data products including Extera and TripleMap. Entagen's technologies won numerous awards including the "Innovative Technology of the Year Award for Big Data" from the Massachusetts Technology Leadership Council in 2012 and Entagen was recognized as a Gartner "Cool Vendor" in the Life Sciences in 2013. Entagen was acquired by Thomson Reuters in 2013.

Prior to his role as the CEO of Entagen, Dr. Bouton worked as a computational biologist at LION Bioscience Research Inc. and Aveo Pharmaceuticals from 2001 and 2004, leading the microarray data analysis functions at both companies. In 2004 he accepted the position of Head of Integrative Data Mining for Pfizer and led a group of Ph.D. level scientists conducting research in the areas of computational biology, systems biology, knowledge engineering, software development, machine learning and large-scale ‘omics data analysis. While at Pfizer, Dr. Bouton conceived of and implemented an organization-wide knowledgebase called Pfizerpedia for which he won the 2007 William E. Upjohn Award in Innovation.

Dr. Bouton is an author on over a dozen scientific papers and book chapters and his work has been covered in a number of industry news articles.


Our Name

Vyasa is the name of a central and revered figure in the Hindu dharma. As the key compiler and storyteller of sacred Hindu texts, Vyasa brought together knowledge from across many sources. Our CEO, Christopher Bouton lived in India for four years as a boy and has great respect for the many belief systems and writings from the deep and rich tapestry of knowledge and thought that are part of the Hindu and broader Indian culture. He believes that our data today has the ability to tell us important valuable stories and that novel technologies such as deep learning can act as approaches towards gaining greater insight into these stories.


Why We're Excited About Deep Learning

Hype, especially in our 24/7 driven media age, can often distort the perceived importance of any given technological development. There is no doubt that “Artificial Intelligence” (A.I.) and the deep learning algorithms that underpin these A.I. approaches are currently the subject of just such a hype cycle. While it will take time for the wheat to be separated from the chaff, what will emerge is a set of technological advances that do in fact have radical novel capabilities that will fundamentally enhance our ability to utilize computational approaches in some of humanity’s most critical pursuits.

At the heart of these advances is the fundamental notion that machines can now learn to recognize patterns, objects and outcomes without being given a priori rule sets to operate on. While this may seem a radical notion, it is not without precedence. There is a computer that has been around for as long as we’ve been around, the human brain (in particular the brain’s cortical architecture) which operates in a very similar manner. Our brains though are limited by the amount of information that they can ingest and consider at any given point in time. This is not the case for artificial intelligence approaches which can incorporate far more variables for learning and thus can provide deeper insights based on an understanding of the complexity and interconnectedness of variables that far surpasses what humans are capable of. 

These types of capabilities are highly relevant in areas, such as the life sciences and healthcare, where many complex variables across disparate information sources need to be brought to bear for insight generation and effective decision making. Fundamental to that capability though is the need to securely provide deep learning systems with enterprise data at scale. 

Vyasa Cortex is an enterprise scale deep learning platform, built from the ground up with consideration for Big Data scale data handling and provision to a range of deep learning approaches. Cortex handles disparate structured and unstructured data as chunks, or statements, and instead of attempting to model or format that content, utilizes a novel deep learning methodology called Neural Concept Recognition developed by Vyasa to identify the concepts latent in the content. Cortex can then enable the application of a pipeline of A.I. approaches on the concepts identified in the system.

At Vyasa we see a future in which A.I. driven approaches enable humans to elevate the nature of our work beyond the rote activities so often inherent in our current processing of digital content. It is exciting to imagine what will be possible when we are able to apply these approaches across large pools of content to help advance our understanding and capabilities across a wide array of pursuits. Hyped or not, AI technologies are here to stay, they are powerful and they are game changing for those enterprises that can apply them effectively at scale.

- Christopher Bouton, Ph.D.
June 2017