Speaker "Ali Arsanjani" Details Back



Amalgamation : Patterns for Combining Data for Machine Learning Insight


We will be reviewing patterns that help with the process of amalgamation : 

taking structured and unstructured data and combining them in insightful ways.

Considerations and best practices for :

1. Data Mining and Data Collection

2. Data Preparation and Curation

3. Annotations and Training for Machine Learning

4. Context Aperture

5. Context Aggregation

6. Ontology Mappings 

7. Ensemble Neural Networks for Amalgamation


Dr. Ali Arsanjani is Founder and CTO of Analytics and Machine Learning at Deep Context, a deep learning startup . He is an advisor to startups and boards of larger companies via

In his previous role (1998-2018) , Dr. Arsanjani was an IBM Distinguished Engineer and Chief Technology Officer for IBM Analytics Hybrid Cloud and Machine Learning responsible for WW enablement of services teams with IBM's latest product assets to support providing highly customized solutions to clients’ complex problems by leveraging a spectrum of capabilities from data science, analytics, machine learning and cognitive computing.

Ali builds teams of teams across multiple geos in large-scale agile solution development of custom, context-aware, sentiment-sensitive cognitive systems that combine unstructured content and structured data to provide actionable insights for clients in finance, healthcare, retail, automotive , telecom and public sector. His career spans CTO responsibilities for SOA, BPM, Robotic Process Automation, Analytics, Machine Learning and Artificial Intelligence/Cognitive Systems.

He delivering actionable business insights thru' an amalgamation of structured and unstructured data using machine learning and artificial intelligence to augment traditional rule engines, custom/legacy systems.

In past jobs he has been CTO for SOA, BPM, Decision Management, Analytics, Content Management.

Ali Arsanjani has chaired standard bodies such as The Open Group and is responsible for co-leading the SOA Reference Architecture, SOA Maturity Model, and Cloud Computing Architecture standards. In his role as Chief Architect, he and his team specialize in harvesting and developing best-practices for the modeling, analysis, design, and implementation of SOA and Web Services on hundreds of projects WW across multiple industries, leading a community of practice of over 6000 people.