Engineer Software

*** * **** **** ***. Apt. O*** SPHURTI MORE **********@*****.***

Sunnyvale, CA 49086 906-***-****

SUMMARY

MS in Electrical Engineering with 2 years of industry experience as a Software Engineer. Currently working with the Moonshot Factory (Google X) as a Test Engineer through Collabera Inc. Proficient in Computer Vision and Deep Learning EDUCATION

Michigan Technological University, Houghton, MI May’ 19 Master of Science in Electrical Engineering

University of Pune, Maharashtra, India May’ 15

Bachelor of Engineering in Electronics and Telecommunication INDUSTRY EXPERIENCE

Collabera Inc. Client – X development LLC., Designation: Test Engineer Jan’20-Present

• Train the supervised learning algorithms to perform robotic operations and collect massive amount of data on the same

• Test the performance of deployed machine learning models manually and autonomously

• Evaluate long running experiments on multiple robotic systems by running Python scripts through Bash Syntel Pvt. Ltd, Designation: Software Engineer Sept’15-June’17

• Assisted production support environment for Standard Life Investments on Mainframe, PL/SQL, SAS

• Analyzed and maintained financial data of over £500,000 per business cycle through TWS, CRIMSV9 tools

• Communicated the progress to clients through daily client meetings and presentations

• Received ‘KUDOS’ award for resolving issues vigilantly and reducing department’s workload by 20% in a year PROJECT EXPERIENCE

Graduate Thesis- Road Sign Detection for Autonomous Vehicles Michigan Technological University Aug’18-April’19

• Researched feature and neural network-based methods employed to detect road signs

• Implemented image processing algorithms to detect the signs for SAE AutoDrive Challenge in Python, TensorFlow

• Evaluated the performance of the algorithms based on processor speed on CPU and detection accuracy

• Achieved 80% test accuracy for YOLO and 71% for HOG with linear SVM after 100 cross-validations of a large dataset

• Secured 3rd position in SAE AutoDrive 2019 challenge for traffic sign detection Robotics Quadrathlon Michigan Technological University March’18-April’18

• Programmed a ClearPath jackal with the ability to perform line stopping and lane, wall, person follower

• Collaborated with a group of three and developed image processing and controls-based algorithms using ROS

• Worked with LiDAR, Cameras and PS3 controller to operate the ClearPath jackal

• Led the team efficiently for development and testing of the algorithms 3D Point Cloud Processing and vehicle tracking Michigan Technological University March’18-April’18

• Generated a 3D point cloud using surface reconstruction in MATLAB and introduced noise to analyze its nature

• Extracted the point cloud data to fit complex surfaces such as sphere, cylinder and mapped triangular mesh to get 3D points

• Developed a kernelized correlation tracker in Python, OpenCV to track a targeted vehicle in a video stream TECHNICAL SKILLS

• C/ C ++ • Python • MATLAB • Linux • Bash • ROS

• OpenCV • TensorFlow • PCL • Object detection • Object tracking • Neural Networks PUBLICATIONS

• Comparing machine learning and neural network-based approaches for sign detection and classification in autonomous vehicles Author: Sphurti More, Dr. Jeremy Bos. SPIE defense + commercial sensing conference 2020 Link - https://doi.org/10.1117/12.2558966

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