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Biomedical Engineer - Image Processing

Harrison, New Jersey, United States
February 12, 2018

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Sanjana Udayashankar +1-973-***-****


To excel in fascinating Biomedical engineering field through hard work, innovation, research, skills and perseverance. Strongly driven to thrive in a rapidly changing, fast-paced environment - in an environment of growth and excellence.


aNew Jersey Institute of Technology - Newark, NJ Aug 2016 – Dec 22 M.S in Biomedical Engineering (GPA – 3.90/4.00)

M S Ramaiah Institute of Technology – Bangalore, India Sep 2011 – Aug 20 B.E in Medical Electronics (GPA – 9.40/10.00)


Medical Image Processing

Computer Methods in BME

Computer Aided Designing (CAD)

Biomedical Signal Processing


Medical Imaging Systems

Biomedical Instrumentation

Engineering Design

Medical Device Design


Programming languages: C, C++, Python Basics

Prototyping Platforms: MATLAB, SPM, Creo parametric, LabVIEW, FSL, AFNI, ITK/VTK

Medical Device Regulations: ISO 10993, ISO 13485, IRB approvals, FDAs regulations like 510(k) process, PMA, GMPs, Medical Device Classification


Biomedical Software Developer Intern – nVIAsoft, NJ Jun 2017– Aug 2017

Worked as Biometric Software Developer using MATLAB to identify and detect a person using hand vein biometrics

Image Processing techniques such as image segmentation, feature extraction and classification were used to identify and verify individuals who were enrolled

Was successful in developing an algorithm as a proof of concept to identify and verify a person who were enrolled in the system in about two months of time which fetched more clients to the startup company

Graduate Student Image Processing Research Assistant – NJIT, NJ Feb 2017 – Aug 2017

Worked on MRI brain image datasets to develop an algorithm that aids in ‘Automatic Brain Tumor Detection’

Imaging techniques such as K-means clustering and thresholding were used to segment the tumor, edge detection techniques were used to find the boundaries of tumor

Neural networks were trained to classify brain images as tumor or non-tumor which showed up-to 80% efficiency

Further worked on fMRI brain image datasets to segment the brain regions using imaging techniques such as Independent Component Analysis, SPM, AFNI, FSL Melodic

Associate Software Engineer – Accenture, India Oct 2015 – Apr 2016

Trained in the field of SAP Basis which emphasized on SAP-administrative work

Shadowed in installing of SAP software and knowledge on Transport Management System

Intern – Sankara Eye Hospital, India May 2014 – Jul 2014

Worked within the hospital ophthalmology department, understand the working of medical instruments used in that area, identifying the problems, troubleshooting and maintenance of medical equipment’s, documenting any service and repairs done


Automatic Brain Tumor Detection: A software developed to detect and mark the boundaries of brain tumor automatically in MRI scans with the help of image processing techniques such as K-means clustering, thresholding and neural networks

Semi - Automated Diagnosis of Rotator Cuff Tears in Ultrasound Images: An user interactive diagnostic tool was created to aid doctors in detecting and diagnosing Rotator Cuff Tears more efficiently and quickly. Artificial neural networks were used to classify the Rotator Cuff tears associated with different shoulder muscles/tendons. Neural networks showed 95% efficiency in classifying the tears

Pel-Dia: An electro-mechanical tool developed to measure the Inter Ischial Spine Distance trans-vaginally, when used by any healthcare worker provides objective measurement and aids in assessing potential CPD. (Patent Pending)


Semi-Automated Analysis of Tear in Rotator Cuff Ultrasound Images: Published this paper in International Journal of Innovative Trends in Engineering (IJITE) in Volume 25, Number 01, January 2017 and presented the same at “Second International Conference on Networks, Information and Communications 2015 (ICNIC 2015)” on 18th -20th May, 2015, held at Sri Venkateshwara College of Engineering, Bangalore

Nonlinear Medical Image Enhancement Technique Based on Image Compression and Histogram Matching Techniques: Author of this paper and presented the same at National Conference on Electrical & Electronics Engineering 2014 at HKBK college of Engineering supported by IEEE

Medical Hackathon: 1st runners up at the CAMTech India Jugaad-a-thon, a medical hackathon (an international event held at GE John F. Welch Technology Centre, Bangalore) and were awarded 1.5 lakh cash prize. The team is currently working on developing and commercialization of the product "Pel-dia". (Patent pending)

Best Project Award for the year 2014-2015: Received this title for the project entitled “Semi-automated diagnosis of Rotator Cuff tears in Ultrasound images” from MSRIT Alumni Association

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