Suggestions
Ujjwal Ratan
Leader, ML and Data Science, Healthcare and Life Sciences
Ujjwal Ratan is a prominent leader in the field of machine learning (ML) and data science, specifically focusing on healthcare and life sciences at Amazon Web Services (AWS). He plays a crucial role in leveraging AWS's cloud computing capabilities to address complex challenges in the healthcare sector.
Professional Background
- Current Position: Ujjwal Ratan serves as the Leader of ML and Data Science for Healthcare and Life Sciences at AWS. In this capacity, he is involved in various initiatives that utilize machine learning to improve healthcare outcomes and streamline processes within the industry.
- Experience: His work includes overseeing projects like the AWS Health AI Hackathon, which attracted over 2,300 participants and showcased innovative uses of Amazon Comprehend Medical to tackle healthcare data challenges.14
Expertise and Contributions
- Certifications: Ratan holds multiple AWS certifications, including:
- AWS Certified SysOps Administrator - Associate
- AWS Certified Developer - Associate
- AWS Certified Solutions Architect - Associate.2
- Thought Leadership: He actively shares insights on platforms like LinkedIn, discussing topics such as the integration of generative AI in drug discovery and clinical research, as well as advancements in applied machine learning for healthcare.56
Engagement with the Community
Ratan is also known for his engagement with the tech community through events like AWS re
Overall, Ujjwal Ratan's leadership at AWS positions him as a key figure in advancing machine learning applications in healthcare, driving significant contributions to both technology and patient care.
Highlights
What happens when you combine NVIDIA ‘s BioNemo with with Amazon Web Services (AWS)?
Biotech startup A-Alpha Bio tried just that, and the results were amazing. Specifically, they slashed experimental cycles and accelerated protein-protein interaction predictions at an unprecedented scale, processing 108 million inference calls in just 2 months. That’s 12x faster than before!
Check out this case study for details
https://lnkd.in/guPiybaF
#lifesciences #generativeAI #AWSisHow
Are you interested in accelerating your protein research workloads on AWS? Are you a fan of the Nvidia BioNemo framework? Check out these new blog posts on pre-training ESM-1nv for protein language modeling with NVIDIA BioNeMo. Discover how to deploy and customize generative models like ESM-1nv on GPU clusters with ParallelCluster, and run the BioNemo containers for training and inference on Sagemaker. These posts offer valuable tips for studying protein sequences, predicting properties, or discovering new therapeutics. Find out how #AWS and #NVIDIA have collaborated to make this possible.
Read the blog posts here: https://lnkd.in/geny2WMj https://lnkd.in/gZg7BVNU
