Hema Ramamoorthy

Data And AI Lead at Digital Catapult

Hema Ramamoorthy has a diverse work experience spanning over several years. Hema is currently working at Digital Catapult as a Data and AI Lead, where they are involved in developing new innovative projects and initiatives, seeking R&D funding, working with corporate partners and startups, and implementing machine learning for commercial and R&D projects.

Prior to this, Hema worked at Tongadive as a Machine Learning Consultant, where they were responsible for data analysis, data pre-processing, and the development of a Time Series Analytics Engine using Deep Neural Network (LSTM). Hema also worked on requirements gathering, time series analysis, forecast engine development, and implementing Anomaly Detection using Autoencoder. Additionally, they developed REST APIs using Python and Flask to connect the Analytics Engine to the main Blockchain software module.

Before Tongadive, Hema had a consultancy role as a Data/AI Consultant/Director, where they provided expertise in data and AI. Hema also worked at Speakerbus as an Embedded Software Design Engineer, both at Speakerbus Ltd and Speakerbus, where they focused on embedded software design.

Hema also has experience working at Tech Mahindra Limited as a Design Lead, at Motorola as a Consultant, and at Caritor Solutions India Pvt Ltd as a Senior Software Engineer.

Overall, Hema Ramamoorthy has a strong background in data analysis, AI, machine learning, and software engineering, with a career history that includes roles in various industries and a range of responsibilities.

Hema Ramamoorthy's education history includes a Bachelor of Engineering degree in Electronics and Communication from Bharathidasan University. Additionally, they attended the University of California, Berkeley, Haas School of Business for a Data Strategy program in 2022 and The Open University for Data Management in the years 2023 to 2024. Hema Ramamoorthy has also obtained certifications in Anonymisation, Open Data for Data Producers, Pitching to Investors, and AWS Machine Learning Foundations.

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