Mayank Deshpande

Software Engineer

Bengaluru, Karnataka, India3 yrs 9 mos experience
Highly Stable

Key Highlights

  • Published research on Physics-Informed Neural Networks.
  • Experience in AWS infrastructure and Node.js development.
  • Strong background in machine learning and data analytics.
Stackforce AI infers this person is a skilled software engineer with expertise in machine learning and cloud infrastructure.

Contact

Skills

Core Skills

Node.jsAwsDeep LearningPhysics-informed Neural Networks

Other Skills

JestSonarQubeAWS CloudFormationAgileNVIDIA MODULUSPythonCC++C#Machine LearningData AnalysisBig DataData StructuresData ScienceData Analytics

Experience

3 yrs 9 mos
Total Experience
3 yrs 9 mos
Average Tenure
3 yrs 9 mos
Current Experience

Airbus

2 roles

AI Software Developer

Promoted

Mar 2025Present · 1 yr 1 mo

Associate Software Developer

Aug 2022Jul 2025 · 2 yrs 11 mos

Telstra

SDE Intern

Mar 2022Aug 2022 · 5 mos · Bengaluru, Karnataka, India

  • Worked on unit tests for node.js primarily using Jest and some SonarQube. Helped in migrating solutions by creating infrastructures in AWS using AWS CloudFormation. Learned the agile way of accomplishing scope and how software architectures and philosophies are executed practically using agile.
Node.jsJestSonarQubeAWSAWS CloudFormationAgile

Datawhiz

Teaching Assistant

Jul 2020Jul 2020 · 0 mo · Hyderabad, Telangana, India

  • Teaching Assistant of Dr. Achal Agarwal for the Bootcamp provided by DataWhiz

Covindia

Data Analyst

Mar 2020Jun 2020 · 3 mos · Hyderabad, Telangana, India

  • Analyzed daily positive case data against different factors that displayed the potential to influence the rate of spread in cases.

Nvidia

Research Collaborator

Jul 2019Aug 2022 · 3 yrs 1 mo

  • Worked with Nvidia Singapore on a project funded by Ministry of Defence, India, to assist in airfoil design optimization using PINNs (Physics-Informed Neural Networks) with the help of Nvidia MODULUS (Previously known as NVIDIA SIMNET) deep learning framework.
  • Was the first author on the paper (published by IEEE Singapore) on the investigations on convergence behaviour of Physics Informed Neural Networks across spectral ranges and derivative orders which now has multiple citations.
Physics-Informed Neural NetworksDeep LearningNVIDIA MODULUS

Education

Mahindra University

Bachelor's degree — Computer Science

Jan 2018Jan 2022

Jubilee Hills Public School

High School Diploma

Jan 2004Jan 2016

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