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Public sector organizations are turning towards artificial intelligence (AI)/machine learning (ML) models to make more informed decisions across areas like re-opening offices and servicing citizens. However, they are struggling to build and operationalize these models quickly. Various studies have found that organizations take months to develop machine learning models and that most of these models (~95%) never making it through the very complex and time-consuming process.
Already constrained for data-science resources, how can public sector organizations build, train and deploy effective machine learning models, across program areas, quickly and arm policymakers with timely insights in an environment where real-world data is changing rapidly?
An automated data science approach can address these challenges and enable public sector organizations to operationalize AI/ML at speed and scale. From democratizing data science skillsets (i.e. making it easier for anyone to build ML models) to accelerating the model deployment lifecycle, this approach can help public sector organizations effectively use AI to improve program outcomes and improve citizen experience.
To learn more, join our panel featuring subject matter experts and public officials who will discuss:
Dr. Suman De, Head of Government Healthcare Analytics, Infosys Public Services
Dr. Daniel Parton, Lead Data Scientist, Bardess Group and Advisor, Tangent Works
Idris Motiwala, Principal Product Manager, Couchbase
Dr. Suman De - Head of Government Healthcare Analytics, Infosys Public Services
Dr. De is head of government healthcare analytics for Infosys Public Services. He has extensive experience in the public healthcare sector and previously worked for the World Health Organization, UNICEF and the Indian Public Health Association.
At Infosys, Dr. De leads the area of advanced data science and artificial intelligence-enabled population health, social determinants of health analytics, opioid management, care management, and value-based care. He is a frequent public speaker at various healthcare conferences, forums and at major universities, including the Massachusetts Institute of Technology.
Dr. De is based in Hartford, Connecticut. He holds a medical degree from the University of Calcutta and master’s degree in healthcare administration from the Tata Institute of Social Sciences in Mumbai, India.
Dr. Daniel Parton - Lead Data Scientist, Bardess Group, Advisor, Tangent Works
Dr. Daniel Parton leads the data science practice at the analytics consultancy, Bardess. He has a background in academia, including a PhD in computational biophysics from University of Oxford, and previously worked in marketing analytics at Omnicom. He brings both technical and management experience to his role of leading cross-functional data analytics teams, and has led successful and impactful projects for companies in finance, retail, tech, media, manufacturing, pharma and sports/entertainment industries.Daniel also acts as an advisor for the Tangent Works InstantML forecasting platform. Bardess is the North American master reseller for Tangent Works.
Idris Motiwala - Principal Product Manager, Couchbase
Idris Motiwala is a Principal Product Manager at Couchbase leading the Analytics product portfolio. He has 25+ years’ experience at both Fortune 500 and high-growth startups, delivering high-tech customer-centric software products spanning go to market, sales, and business development. He has also led business and technical teams in digital transformation, cloud, mobile, and advanced analytics space. Idris holds a master’s degree in technology management and certifications in product and program management.