Chaitanya pursued his Master's in Robotics and Control from the Umeå University, Umeå, Sweden (Autumn 2017). His research emphasis is primarily on Data Science, Artificial Intelligence and Distributed Computing.

Currently, Chaitanya is an Engineering Consultant at Infotiv, Gothenburg.

Experience

  • Software Engineering Consultant

    at Infotiv AB

    September 2019 - at Present

    Västra Götalands Län

    Autonomous Vehicle Platform: Project with the goal of creating a miniature platform for an autonomous car developed of internal education. This platform has a number of nodes connected through a CAN module network, similar to how a real car works, and a full sensor suite to be used for autonomous research. • Worked on the software development of the Battery Monitoring System to control the power output for the whole car while communicating through CAN modules. • Worked in the final integration of all the available nodes to get the platform running. • Currently working on the ADAS unit to build the next generation CAN communication interface through a Raspberry pi. Also to develop a robust server framework to receive camera images and to send signals to the car from a wireless remote client.

  • Master Thesis worker

    at Volvo Cars

    February 2019 - September 2019

    Västra Götalands Län

    Deep Learning for Big Data Analytics for Predictive Aging Models in Electrical Vehicles : A Survival Analysis Study on Batteries Battery behavior data was collected from 32 Volvo V60 cars in a highly compressed format and analysed in order to create a battery aging model in real world scenarios. This was achieved through a data science pipeline which was responsible for decompressing, cleaning, extracting and selecting significant features. The processed data was used to perform predictive survival analysis. This was achieved through the statistical methods and through memory-based recurrent neural networks. Thesis report : http://umu.diva-portal.org/smash/get/diva2:1360100/FULLTEXT01.pdf

  • Summer worker

    at Sony Mobile Communication

    June 2018 - August 2018

    Skåne Län

    Worked on high accuracy robust indoor localization system for a mobile robot using only visual input. A LEGO EV3 brick was used as the control module and a Raspberry Pi model 3B+ equipped with ROS Kinetic, OpenCV3 for image processing, scikit-learn for machine learning computations. A web server was setup on the robot to stream the processed frames to a remote desktop client. The project was successfully completed under the supervision of Mr. Andrej Petef (Senior Research Manager | Research and Incubation at Sony Mobile Communications, Sweden)

  • Distributed Computing Researcher

    at Singapore University of Technology and Design

    January 2016 - August 2017

    Singapore

    Worked as Research Assistant in Applied Complexity group under principle investigator Prof. Roland Bouffanais (Singapore University of Technology and Design) and Prof. Dick K. P. Yue (Massachusetts Institute of Technology). • Worked on collective Environment Sensing project in collaboration with Singapore-MIT Alliance for Research and Technology, Singapore (SMART) and Massachusetts Institute of Technology (MIT) • Implemented Hadoop and Distributed Tensorflow on a raspberry pi cluster as a fault tolerant message passing interface for distributed computing • Developed an algorithm using pure python for distributed scientific calculations on large clusters and scaled up the operation to test a cluster of 8 to run complex fluid dynamics library Assisted in the research on swarming in collaboration with Ministry of Defense, Singapore.

  • Robotics Engineering Intern

    at Infinium Robotics

    July 2015 - September 2015

    Singapore

    • Worked as an intern with the Product Development team for Infinium Serve specializing in the field of Embedded Systems. • Successfully ported Picuntu (linux distro) on a fully functional Tronsmart mk908ii (portable android tv box). This enabled on-board processing for the drone to avoid communication lag between the remote central processing unit and the drone to minimize collision. • Contributed towards developing an obstacle detection technique using an electromagnetic sensor. • Researched in the area of distance sensors to replace the conventional sonar with a compact laser sensor.

Education

  • Masters in Robotics and Control (Specializing in AI)

    at Umea University

    2017 - 2019 (2 years) Västerbottens Län

  • Bachelors of Technology in Electronics and Communication

    at The LNMIIT

    2011 - 2015 (4 years) Jaipur - Rājasthān

Languages

  • English Native

Hives