Resume

I am a Second year masters student at the Amrita Vishwa Vidyapeetham in Automotive Electronics branch and also as a research assistant at Computational Engineering and Networking (CEN). I am working with the Cybersecurity-Lab-at-CEN and Computational Thinking-Lab-at-CEN and student of Prof. Soman KP . My research areas are Robotics, Autonomous vehicles, Machine Learning, Data mining,Deep learning, Reinforcement Learning, Causal inference,Cyber Security,Non linear dynamics, Convex optimisation, Natural language processing,Signal and Image processing, .

I strongly believe in open science and reproducible research and actively publish code on my Github profile.

I am Available on the job market!!

News

  • September 2018 organizing CAN Intrusion Detection Shared Task CANID 2018
  • September 2018 shortlisted for quarter finals (from 10,000 teams) IICDC 2018 Hackathon by Indian Government
  • July 2018 Secured 2nd place in DMD 2018 shared task in Cybersecurity domain. More details available at DMD2018
  • July 2018 Registered for IECSIL 2018 Shared Task at IECSIL 2018.
  • July 2018 Registered for Multi-target speaker detection and identification Challenge Evaluation Shared Task at MCE 2018.
  • July 2018 Registered for NIPS 2018: AI for Prosthetics Challenge at AI for Prosthetics Challenge 2018.

Conference Papers

1. Novel Deep Learning Model for Traffic Sign Detection Using Capsule Networks

Amara Dinesh Kumar

[ paper ] [ code ]

2. A Brief Survey on Autonomous Vehicle Possible Attacks,Exploits and Vulnerabilities

Amara Dinesh Kumar,Vinayakumar R, Soman KP

[paper]

3. DeepImageSpam: Deep Learning based Image Spam Detection

Amara Dinesh Kumar,Vinayakumar R, Soman KP

[paper] [code]

Book Chapters

1. Vinayakumar, R., K. P. Soman, Prabaharan Poornachandran, Vysakh S. Mohan, and Amara Dinesh Kumar. "ScaleNet: Scalable and Hybrid Framework for Cyber Threat Situational Awareness Based on DNS, URL, and Email Data Analysis." Journal of Cyber Security and Mobility 8, no. 2 (2019): 189-240.

2. Using Various Deep Neural Networks to Detect Domain Generation Algorithm Attacks, Deep Learning Applications for Cyber Security, Springer publications [under print]

Amara Dinesh Kumar, Harish Thodupunoori, Vinayakumar R, Soman KP, Prabaharan Poornachandran, Mamoun Alazab and Sitalakshmi Venkatraman

3. AmritaDGA: Data on Detecting Domain Generation Algorithms(DGAs)

Vinayakumar R, Jyotsna, Amara Dinesh Kumar,and Soman KP

Education

July 2017 - Present, M.tech in Automotive Electronics, Amrita Vishwa Vidyapeetham, Coimbatore

CGPA: 8.3 (Till 3rd Semester)

[ Deep Learning- A+, Reinforcement learning- A+, Multi Sensor Data fusion- A+ ]

June 2010 - June 2014, B.tech in Electronics and Communication , Jawaharlal Nehru Technological University, Hyderabad

CGPA: 7.84

Work Experience

Worked as 4G LTE Network Engineer for 2.6 years in Tata Consultancies and Services for Nokia Networks Client.

TCS Experience

Project Name

Nokia Solutions and Networks OY

Period

14-Oct-2014 To 30-Jun-2017

Roles

4G LTE DEVELOPER

Responsibility

1)Software Development for the Element Management System(EMS) application .

2)To Meet committed P gate schedules and zero escape defects and Zero escalations from customers within Solution Centers On time delivery-100%,CSI Feedback,SLA Compliance .

3)Development of Automation Framework for Test Execution and Result parsing of BT/SV/CP/Performance Test cases.

Technical Skills

Programming languages : C, C++

Scripting : Shell and Expect Scripting

Operating Systems : Red Hat Enterprise Linux

Networking : TCP/IP, VLANS, SNMP,ACL

Linux tools : AWK, SED Bash, Perl

Achievements

1) Performed Development for R11 and R12 releases of EMS software for the KDDI client and received best team award.

2)Performed development and DIT for 6 features ahead of the schedule and received on the spot award.

3)Received many appreciation mails from the client for delivering software defect free and ahead of the schedule

4)Took initiative to automate all DIT test cases and also received on the spot award for developing DIT AUTOMATION FRAMEWORK and saved 1 million to KDDI client.Wrote more than 5000 lines of bash,expect code.Developed the complete Automation Framework including libraries,supporting functions from the scratch.

Teaching and Mentoring Experience

Mentored 8 Teams ( from the upgrad data science PG diploma course ) for Reinforcement Learning project.

Master's Coursework

  • MA607 - Linear Algebra
  • CN613 - Computational optimization theory - linear and non-linear methods
  • CY603 - Pattern Recognition and Machine Learning
  • CN703 - Computational Methods for Cryptography
  • CN733 - Neural network & Deep learning
  • CY800 - Research Methodology
  • Deep Learning
  • Reinforcement Learning
  • Digital Control System
  • Multi Sensor Data Fusion
  • Probability Graphical Models
  • Sensing For Autonomous Vehicles
  • Electric Vehicle Architecture
  • Power Electronics and Converters
  • Real Time Operating Systems
  • Automotive Embedded Systems
  • Computer Vision and Image Processing
  • Cryptography

Skills

Languages : C, Embedded C, C++, Java, Scala, Python, Basics of R, Basics of Julia

Scripting Languages : Html, CSS, JavaScript, Bash, Awk, Sed ,Perl , XML

Embedded System Softwares : Matlab, Simulink, CarSim, Canoe, KEIL, Proteus, Arduino Studio

Frameworks : Scikit-learn, LibSVM, TensorFlow, Theano, Keras, , OpenAI Gym, PyTorch, Basics of Caffe, DeepChem, DragoNN, Weka

Database : MySQL, Introduction to Oracle

Documentation Tools : LibreOffice, Microsoft Office, and Latex

Participated the following events in the department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham