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Jay Pathak


 

Ansys Blog Authors

Jay Pathak

Director, Software Development

Jay has more than 17 years of experience in enterprise software development with a focus on framework development, web services, 3D numerical simulations, scientific visualization, and machine learning. In his current role as Director of Software Development at Ansys, he manages technology teams with a focus on AI/ML as it applies to engineering simulation. He drives research projects, mentors development teams, and manages university collaboration and key customer relationships.

In previous roles at Ansys, Jay was instrumental in managing and leading physics teams for key development initiatives, such as growing the number of solvers over a decade and in the productization of Ansys Discovery AIM.

Prior to joining Ansys, Jay worked as a software engineer at Nei Software, which was acquired later by Autodesk Inc.

Education:

  • Masters Degree in Mechanical Engineering and Computer Science from the University of Florida

Licenses & Certifications: 

  • Lean Agile Project Management
  • Implementing Lean Agile for Your Team
  • UX Design Essentials for Executives
  • Parrallel and Distributed Computing
  • Handoop and MapReduce by Cloudera
  • Up and Running with Azure
  • Up and Running with ASP.NET
  • Machine Learning by Stanford University of Coursera 
  • Introduction to Artificial Intelligence
  • Executive Data Science Specialization
  • Inclusive Leadership

Joined Ansys: July 2005


Articles by This Author

Point Cloud and its different activation states

Revolutionizing 3D Surface-Contact Detection via Deep Learning

Learn how an advanced 3D deep-learning model from Ansys called ActivationNet supports the creation of high-quality, accurate models of multiple 3D surfaces in contact with one another. 

Vector and Streamline represented by different colors for velocity and pressure

Deep Learning Is Poised to end the Trade-off Between Speed and Fidelity

Learn how Ansys simulation software could use deep learning to deliver even higher speeds and fidelity simultaneously, in a single solution. 

Fatigue life and safety factor in stress life fatigue analysis using zero based loading.

Easy Simulation for Fatigue Analysis in Ansys AIM

Ansys AIM makes it easy to include fatigue analysis as part of linear or nonlinear structural analysis, helping your design process and product development costs.

Topology optimization app available at startup

How to Approach Topology Optimization in Ansys AIM 18.2

Topology optimization is a numerical technique that optimizes material layout for a given part or assembly for a given set of loads and boundary conditions.