Narrendran Ramesh

Narrendran Ramesh, an accomplished technologist, author, and entrepreneur, has a rich background in building research organizations and groundbreaking products across various sectors like finance, automobile, technology, oil and gas, and logistics.

His expertise lies in theoretical and applied machine learning, particularly in the distribution and multi-threading of large-scale applications of Machine Learning and Artificial Intelligence. He has a keen interest in utilizing AI to revolutionize enterprise operations.

Throughout his career, he has excelled in working with exceptional talents and shaping high-performing teams. Prior to his current role at Udacity, Narrendran held key positions in renowned companies where he contributed to the advancement of AI technologies and managed complex software R&D projects end-to-end.

Narrendran Ramesh holds an impressive educational background, including a Graduate degree in Data Science - Big Data Systems from Harvard Extension School, a Doctorate in Business Administration and applied Computer Science from Westcliff University, an MBA in Finance from Concordia University Chicago, and a Bachelor's in Electronics and Communication Engineering from R.M.K Engineering College.

He has held significant roles in organizations like Deloitte as an API Consultant, nThrive as an RPA Engineer, Kelly as a Product Manager, Change Healthcare as an RPA Builder, U.S. Xpress, Inc. as an RPA Consultant, BP as an RPA Consultant, Toyota North America as a Product Manager, American Airlines Federal Credit Union as an RPA Developer, Augur IT Inc as an RPA Developer, and Concordia University Chicago as a member of the Master of Business Student Association.

Additionally, Narrendran Ramesh has valuable work experience as a Confidential Assistant at Defence Research and Development Organisation (DRDO) and as an Information Technology Consultant at VIRAM CONSTRUCTIONS PRIVATE LIMITED, showcasing his versatile skill set and expertise.

His specialties include theoretical and applied machine learning, artificial intelligence, large-scale distribution of scientific computing, and the management of complex software R&D projects encompassing conception, fundraising, implementation, sales, and delivery.