science

MAKING A DIFFERENCE
AT THE INTERSECTION
OF SCIENCE AND ENGINEERING

MACHINE LEARNING

We’re into the science of getting computers to act for people without being explicitly programmed. These powerful machines have given us spam filters, effective search engines, optical character recognition, self-driving cars, and a much better understanding of the human genome. We are in the habit of using these functions daily without even thinking about it consciously. Here, we are committed to enhancing this experience. We focus on the study and construction of algorithms with particular focus on computational statistics.

OUR RECONCILING EDGE

The relentless flow of data in recent years has outpaced many people and organizations in their ability to process, analyze, store and understand such huge datasets. We stay ahead of the ‘volume, variability, velocity’ trap through an enhanced capability to extract useful information from these massive datasets.
We focus on methodologies that identify potentially useful and meaningful patterns in the data. We also develop data analysis and discovery algorithms to produce a complete list of patterns. After evaluation, we add these data patterns to our knowledge frameworks.
We focus on identity-resolution, ontology learning, knowledge discovery and transforming relational databases into RDF. We use time-tested methods such as information extraction and ETL (Extract, Transform and Load). The end result is the transformation of data from disparate sources into structured formats.
Based upon its interaction with experience, environment or input data, there is a vast array of different ways an algorithm can model a problem. We select the best model according to the roles of input and the model preparation process. We combine this with established methods like supervised learning, unsupervised learning, semi-supervised learning and reinforcement learning.

SCIENCE VISUALIZATION

We delve into the scientific data and then present this data graphically allowing researchers to gain deeper insight.