Engineer

SHALIN RATHI

• +1-919-***-**** • **********@*****.*** • www.linkedin.com/in/shalinrathi/ •

EDUCATION

Master of Science in Electrical Engineering, GPA: 3.50/4.00 Aug’18 – May’20 North Carolina State University, Raleigh, NC, USA

Coursework: Digital Image Processing, Computer Vision, Neural Networks, Mechatronics, Object Oriented Design and Development, Quantum Computing, Pattern Recognition

Bachelor of Technology in Electronics and Communications Engineering, CPGA: 8.51/10.0 Jul’11 – Jun’15 Nirma University, Ahmedabad, Gujarat, India

Coursework: Signals and Systems, Digital Signal Processing, Data Structures, Embedded Systems, Digital Circuits TECHNICAL SKILLS and CERTIFICATIONS

Languages: Python, C, R, C++, Ruby, SAP ABAP, HTML, CSS Software Tools: Keras, PyTorch, Tensorflow, Pandas, Tkinter, Ruby on Rails, Docker, Django, Kubernetes, MySQL, MATLAB, Git, Jenkins, Bash, Qiskit, AWS

Udemy: Machine Learning A-Z: Hands-On Python and R in Data Science, Deep Learning A-Z: Hands-On Artificial Neural Networks WORK EXPERIENCE

Graduate Student Research Assistant, NCSU Jun’19 – May’20

• Developed an algorithm for doing instance segmentation using Watershed and KMeans coupled with edge detection to identify number of vacuoles and area occupied by each in stomata of plant cells.

• Created a UI in Python that takes CZI file as input, performs segmentation on individual images from the stack and outputs the rate of vacuole fusion in plant stomata as it progresses from closed to open state and vice versa. Infosys Limited, Systems Engineer Aug’15 – Sept’17

• Developed, tested and documented SAP Reports, Interfaces, Conversions, Enhancements, Forms, Workflows that meets the documented design in SAP SD, SAP MM and provided support in SAP FICO for a major client.

• Maintained proficiency in technology and tools for continuous improvement, in order to enhance productivity and quality of systems development.

Broadcom Corporation, Intern (Infrastructure and Networking Group) Jan’15 – Jun’15

• Built an automated code review system using Jenkins that builds Android OS and (if successful) flashes it into an Android device to check for successful booting of the device anytime a new patch is pushed on team’s Gerrit repository, and finally posting a pass/fail review for the patch in the repository.

• Saved the team almost 2 hours of manual checking per patch. PROJECTS

Surveillance system using RaspberryPi (ongoing)

• Creating a system on RaspberryPi which can identify familiar faces and unlock the front door of the house. For unknown faces, it will send a notification to mobile device for further action. Line Follower using LEGO EV3 (2019)

• Created ultrasonic sonic sensor circuit for obstacle avoidance and 3 sensor array for black line detection over white surface.

• Interfaced the circuits to work with EV3 brick and park custom built robot as close to obstacle as possible. Time tracking of reviewers on Expertiza (2019)

• Track time taken by peers, reviewing a project to help better understand whether the review was done in full honesty or not.

• Refactored development, which was then moved to production. Visual Tracking using Siamese Network (2019)

• Trained an offline model from annotated video dataset (DAVIS 2016).

• The model then uses online learning to detect the object with initial bounding box, by creating a mask around the object.

• This masking aids the object tracking as opposed to tracking with only bounding box. Using Artistic images to improve object classification (2019)

• Improve generalization and performance of image classification on Imagenet dataset by creating adversarial samples, which are stylized images using various painting styles available in BAM dataset. Skin detection (2019)

• Evaluated varies techniques used in skin detection, like Bayesian classifier, SVM, etc using different colour spaces, like YCbCr, HSV, and RGB on AFLW and ColorFERET dataset, by plotting the ROC curve.

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