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Shreekant Vishwas Marwadi
www.linkedin.com/in/shreekant-marwadi
Houghton, MI 49931
OBJECTIVE: Looking for full time opportunities in Signal processing area from May 2018. SKILLS: MATLAB (All Signal Processing and Machine Learning Toolboxes), Python (OpenCV, TensorFlow), C\C++, Verilog, Arduino, CAN, TMS320C6713 DSP, Code Composer Studio, MS Office, Linux EDUCATION:
Michigan Technological University Houghton, MI
MS Electrical Engineering Signal Processing GPA: 3.66 Graduating May 2018 University of Pune Pune, India
Bachelor’s in Electronics and Telecommunication Engineering GPA: 3.50 2011 - 2015 WORK EXPERIENCE:
Research Assistant Michigan Technological University May–December 2017 Simulation of VANET routing protocol Prof. Dr. Aurenice Oliveira
• SUMO, used to generate and simulate traffic on street maps from “openstreetmap.org”
• A network simulator(NS-3) is used for simulating and testing performance of Greedy Perimeter Stateless Routing
(GPSR) VANET routing protocol on the traffic scenario created using SUMO Teaching Assistant / Grader Michigan Technological University September–December 2017 PROJECTS:
Autonomous Driving (Lane, Road Signs and Vehicle Detection) January 2018 - Present
• Road Signs and Vehicle detection using Convolutional Neural Network (CNN)
• Lane detection using color segmentation
• Results: The code was written in MATLAB with use of Neural Network Toolbox, Parallel processing and simulated successfully, Used Ground Truth Labeler App for making Ground truth training data
• Currently working on correlation tracker for tracking a segmented targets Implementation of Machine learning classifiers to classify MNIST data August–December 2017
• Implementation of Logistic Regression, Naïve Bayes, KNN, SVM and MLP Classifiers
• Results: Classifiers were coded in python and the results were compared based on different parameters Blind Signal (Mixed Speech) Separation March–May 2017
• We used two data analysis methods for BSS those were ICA and SFA
• Results: The code was written in MATLAB and Simulated successfully, Compared and documented the performance of these methods on basis of different parameters Face detection using k-means clustering November 2015-April 2016
• Detection and extraction of faces from a given image features such as eyes, mouth etc. using k-mean clustering
• neural networks to increase the accuracy rate
• Results: Code was written in MATLAB and simulated successfully 3 Level R.F.S. Security System June 2014-May 2015
We have implemented an idea of having a 3-level security system, which will enhance the security of high profile places.
• Face recognition using Eigen face algorithm
• Speaker recognition using Mel Frequency Cepstrum Coefficient (MFCC)
• RFID card technique wiegand protocol
• Recognition part code was implemented in MATLAB and then merged with RFID and ARM-7 for hardware implementation with C++
• Results: Coding was done in MATLAB, C++ and successfully implemented on a prototype Research Paper: Published this project on IJESRT having ISSN: 2277-9655 impact factor of 3.449 on date 15/03/2015. http://www.ijesrt.com/issues%20pdf%20file/Archives-2015/March-2015/32_R.F.S.%20SECURITY%20SYSTEM%20FOR%20PARLIAMENT%20AND%20HIGH%20PROFILE%20PLACES.pdf REVIEW PAPER:
Emotion Recognition based on signal processing January– February 2017
• I have reviewed current research and its challenges on “emotional recognition using signal-processing techniques” http://www.csl.mtu.edu/classes/cs4760/www/projects/s17/grad12/www/