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State University Assistant

Detroit, Michigan, United States
October 22, 2016

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Angkit Choudhury

Apt #***, **** Second Ave Detroit, MI 48201 C: 313-***-**** Proficient with computer programming languages and highly motivated. Actively looking for a position in deep learning or machine learning fields. Working as a Graduate Research Assistant in deep learning in Wayne State University. My experience at Wayne State, IIT Guwahati, NIT Silchar and Indian Railways have given me valuable engineering skills and knowledge


Programming: MATLAB, C, C++(OOP), Python( Numpy, Scipy family of modules), Software Packages: Tensorflow, Theano, Ipython, CUDA(Parallel Processing), Panda, Machine Learning( scikit-learn), Simulink

MOOC: Machine Learning ( Supervised Learning, Unsupervised Learning, Large Scale Machine Learning) Deep Learning ( Computer Vision, Natural Language Processing) Master’s Thesis: Deep language model for solving large anagrams using Recurrent neural network and LSTM. EXPERIENCE

Graduate Research Assistant ( Wayne State University)(August,2015 - ) Vehicle Intelligence Using Machine Learning: (Wayne State University),2016 Photo Optical Character Recognition for Autonomous Vehicles

Designed an algorithm to read road signs for autonomous vehicles.

The algorithm can perform text recognition, character segmentation and character recognition.

Text recognition is done with sliding window algorithm and trained with a binary classifier.

Character segmentation is trained with binary classifier.

Character recognition is trained with multi class classifier which has 36 classes,26 letters(A-Z)+(0-9)

Programming is done using Python with open source libraries Scipy and Numpy and Tensorflow is used as the building platform.

Deep language model for solving large anagrams:

Generating meaningful English sentences for a given constraint set of characters ( Wayne State University), 2016

English PTB data set is tokenized and converted into integer ids.

Tokenized input and output texts are converted into dense vectors using word2vec in Tensorflow.

Tensorflow embedding seq2seq model is used to train the algorithm.

LSTM cell is used for the seq2seq model.

Performance is measured in log perplexity score.



Two Link Robot Arm Design ( Wayne State University), 2015

Designed a two link robot on a test bed with specified DH parameters.

Wrote Matlab code for moving each link of the robot individually for given angles.

Designed GUI interface by which the robot can write anything on test bed inputted by user.

Implemented DSTAR and PRM algorithm to move the robot avoiding obstacles present on test bed.

Implemented Spline algorithm to smoothen the path of the robot. Embedded System and Sensor fusion:

In vehicle control system using CAN protocol ( IIT Guwahati ), 2014

Integrated CAN bus controller, ARM as main control module and LCD display to provide interface.

Developed and implemented a digital driving system to improve driver-vehicle interface.

Used CAN bus(1) to meet real time requirements such as engine speed, wheel speed, throttle pedal locations.

Used CAN bus(2) for locker, windows, mirrors, interior lights feedback controls.

ARM7TDMI-S a 32 bit microprocessor based on RISC principles is integrated with CAN buses and LCD.

In vehicle control system is programmed using Embedded C and debugged with MPLAB XIDE.

A temperature sensor LM 35 integrated with the main module .

A fan and an alarm are programmed to turn on by the main module if the temperature feedback from the sensor crosses 250 degree F.


PID Control Design ( NIT Silchar),2013

Designed a PID feedback control system.

The designed system assists the driver in maintaining desired velocity and position of the car.

Tested the system under conditions in which the driver finds difficulty to maintain velocity and position by controlling the gas pedal.




Wayne State University, Detroit, MI

Master of Science, Electrical and Computer Engineering GPA: 3.83 ( Expected Graduation December 2016)

National Institute of Technology, Silchar, India

Bachelor of Science, Electronics and Communication Engineering GPA: 3.5 ( Graduated 2013)

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