Chandrashekar K.
About Chandrashekar K.
Chandrashekar K. is a Senior Software Engineer at Bosch Global Software Technologies, specializing in automotive software development and model-based design. He holds a Bachelor of Technology in Electrical, Electronics and Communications Engineering from Amrita Vishwa Vidyapeetham and has expertise in Functional Safety, Automotive SPICE, Computer Vision, and Deep Learning.
Work at Bosch Global Software Technologies
Chandrashekar K. has been employed at Bosch Global Software Technologies since 2022 as a Senior Software Engineer. Prior to this role, he worked as an Embedded Software Developer at the same company from 2019 to 2022. His tenure at Bosch began with an internship from 2018 to 2019, where he gained foundational experience in software development. Throughout his time at Bosch, he has focused on enhancing automotive software solutions, leveraging his expertise in functional safety and automotive SPICE.
Education and Expertise
Chandrashekar K. completed his Bachelor of Technology in Electrical, Electronics and Communications Engineering at Amrita Vishwa Vidyapeetham, Coimbatore, from 2015 to 2019. His educational background includes a strong foundation in Mathematics and Computer Science, achieved during his high school studies at St. Mary's School from 2013 to 2015. He possesses advanced skills in Matlab and Simulink, model-based design, computer vision, and deep learning, which are essential for modern engineering and AI applications.
Background
Chandrashekar K. began his professional journey with an internship at CDAC, Noida, in 2017, where he worked for one month. He later interned at Bosch Global Software Technologies from 2018 to 2019, which paved the way for his subsequent role as an Embedded Software Developer. Additionally, he gained research experience as a Research Intern at the Indian Institute of Science (IISc) in 2018 for three months, further broadening his technical skills and knowledge in the field.
Achievements
Chandrashekar K. has developed a strong command of critical engineering tools and methodologies, including functional safety and automotive SPICE. His proficiency in model-based design enhances the efficiency of developing complex control systems. Furthermore, he demonstrates a comprehensive understanding of CAN and CANFD protocols, which are vital for automotive communication systems. His advanced skills in computer vision and deep learning position him as a knowledgeable professional in modern AI technologies.