Homesearch
Services
Industries
About
Partnerships
Insights
Careers
The CrowdStrike event: Addressing the mismatch between automated processes gone wrong and manual recovery
We are looking for the best
Are you one of the top 10% in your field? Do you have a passion for technology and want to make a difference? If so, we are looking for you!
DISCOVER OPENINGS
Investors
The CrowdStrike event: Addressing the mismatch between automated processes gone wrong and manual recovery
NASDAQ CM: GDYN
$16.81
Nov 20, 2024 4:00 PM EST
Get in touch
search
Naresh Rajendra Shah

Naresh Rajendra Shah

Naresh has over 8 years of development experience in the relatively nascent field of Deep Learning. He has worked with different types of solutions in the Deep Learning space from the days prior to Tensorflow and Pytorch where he used to build Deep Learning models on top of Theano/Caffe as frameworks. He is currently focused on nimble, agile solutions to accelerate value recognition of Generative AI solutions at Grid Dynamics. He has a Bachelor's in Electrical Engineering, BITS-Hyderabad, and a Master's in Business Analytics and Big Data, IE Business School. He has previously worked with different companies across fields like P&G, GE Healthcare, and his own startup, Untangle AI in the Explainable AI Space.

Blog posts:

July 21, 2024 The CrowdStrike event: Addressing the mismatch between automated processes gone wrong and manual recovery
October 23, 2023 Exploring the transformative impact of generative AI in manufacturing
October 02, 2023 Driving business success with generative AI: Techniques for value-driven transformation
September 22, 2023 How generative AI elevates customer engagement in B2C manufacturing and retail
September 12, 2023 Generative AI in pharma and life sciences: Pragmatic applications and outcomes

Naresh Rajendra Shah

Naresh has over 8 years of development experience in the relatively nascent field of Deep Learning. He has worked with different types of solutions in the Deep Learning space from the days prior to Tensorflow and Pytorch where he used to build Deep Learning models on top of Theano/Caffe as frameworks. He is currently focused on nimble, agile solutions to accelerate value recognition of Generative AI solutions at Grid Dynamics. He has a Bachelor's in Electrical Engineering, BITS-Hyderabad, and a Master's in Business Analytics and Big Data, IE Business School. He has previously worked with different companies across fields like P&G, GE Healthcare, and his own startup, Untangle AI in the Explainable AI Space.

Naresh Rajendra Shah

The CrowdStrike event: Addressing the mismatch between automated processes gone wrong and manual recovery

Insights, Media and News / By Naresh Rajendra Shah, Manga Sridhar Akella

Data democratization should be viewed as a continuum between centralized and decentralized approaches, and companies need to assess their culture’s readiness for this shift. It is important to consider privacy, security, and compliance issues while allowing for data access and decision-making at different levels within the organization.

Generative AI in pharma and life sciences: Pragmatic applications and outcomes

White Papers / By Naresh Rajendra Shah, Anindya Gupta

The pharma and life sciences industry is experiencing a data revolution. As everything becomes more digital, the amount of biomedical data is exploding. This presents an opportunity to tap into valuable insights to advance R&D, manufacturing, marketing, and more. However, companies struggle to effectively analyze all this data. Generative AI is the solution. Unlike analytical