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4th NOAA Workshop on Leveraging AI in Environmental Sciences has ended
The interactive workshop will be a virtual event to build collaboration and initiate the active development of AI-powered applications and community standards.

We invite developers, data scientists, domain experts, social scientists, and downstream users to form small teams around different use cases that are relevant to three themes relevant to NOAA Mission Areas: Fire Weather and Impacts, AI for Ocean Conservation, and Interoperable Digital Twin Earth.

All information about workshop logistics can be found in the handbook for participants.

If you encounter issues registering for the workshop, please contact ai.workshop@noaa.gov.
avatar for Soumyendu Sarkar

Soumyendu Sarkar

Hewlett Packard Enterprise
Senior Distinguished Technologist, Hewlett Packard Labs
Milpitas, CA

Contact Me

Soumyendu is an Artificial Intelligence Chief Technologist at Hewlett Packard Labs and develops solutions in emerging areas of Machine Learning like Reinforcement Learning applications for clean energy solutions including wave energy converters and Trustworthy AI. These solutions helped lower the Levelized Cost of Energy (LCOE) for wave energy converters by increasing the energy capture efficiency and reducing structural stress to limit maintenance and protect against survival conditions. Soumyendu also contributes to other areas of AI research and productization with multi-agent Reinforcement Learning, computer vision, video analytics, natural language processing (NLP), trustworthy AI, and Auto ML. He has developed AI at scale with research and innovation, software and systems engineering, and hardware optimizations. Before joining HPE, Soumyendu had contributed to developing market-leading computer vision, machine learning, and imaging products at Intel Corporation. In Bell Labs at Lucent Technologies and subsequent spin-offs, he worked as a Distinguished Member of Technical Staff and developed market-leading telecom products. Soumyendu is currently researching on digital twins for weather and augmentation and analytics of weather data with Machine Learning.
Tuesday, September 6
 

12:00am MDT

9:30am MDT

11:30am MDT

1:30pm MDT

 
Wednesday, September 7
 

9:30am MDT

11:30am MDT

1:00pm MDT

2:00pm MDT

3:00pm MDT

 
Thursday, September 8
 

9:30am MDT

11:30am MDT

1:30pm MDT

3:00pm MDT

 
Friday, September 9
 

9:30am MDT

11:30am MDT

1:00pm MDT

 
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