Experience

  • Feb. 2018 Present
    ‏‏‎

    Chairman

    IEEE Student Branch
    NIT Durgapur



  • Jul. 2017 Present
    ‏‏‎

    Undergraduate Researcher

    National Institute of Technology Durgapur
    Department of Electronics and Communication Engineering


  • May. 2018 Jul. 2018

    Summer Research Intern

    CERN
    A Large Ion Collider Experiment



  • May. 2017 Aug. 2017

    Software Developer Intern

    Google Summer of Code 2017
    RoboComp



  • May. 2017 Jul. 2017

    Summer Research Intern

    Indian Institute of Technology Kharagpur
    SWAN Labs

Education

  • B. Tech. 2015- Present

    Electronics and Communication Engineering

    National Institute of Technology Durgapur

  • High School2013-2015

    Computer Science

    Don Bosco School Park Circus

Interests

  • Wireless Communication
  • Signal Processing
  • Internet of Things

Projects

  • image

    Aqua SHIFT: an analysis tool for water transfer between flood and drought regions

    Mentor:

    • Abhay Raizada

    Team Members:

    • Abhishek Prasad
    • Abhishek Singh

  • image

    Wideband Wireless Channel Modelling for 60GHz millimetre wave in-vehicular Communication

    Supervisors:

    • Dr. Anirudhha Chandra
    • Dr. Ales Prokes

    Team Members:

    • Ushasi Ghosh

  • image

    Multilevel Technological Solution for Safe Disposal of Menstrual Waste

    Team Members:

    • Sanjucta Roy
    • Shalini Chakraborty
    • Neeraj K. Prajapati
    • Swarnendu Mondal
    • Satyajit Panda
    • Aakash Khandelwal

  • image

    Pyxel: Symmetric Key Chaotic Image Encryption by Sequential Pixel Shuffling

    Team Members:

    • Mayukh Bhattacharyya

  • image

    Random Opportunistic and Selective Exploration for Ground-Survivor Detection through UAVs

    Supervisors:

    • Dr. Sudip Misra
    • Anandarup Mukherjee

  • image

    Travel Route Recommender System for Tourists

    Team Members:

    • Vivek Modi
    • Arnav Kumar
    • Deeksha Chandwani

  • image

    Mobility Control Algorithm for Maximizing Node Coverage by Drones

    Team Members:

    • Agnivesh Adhikari

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Channel Modelling for 60 GHz mmWave Communication Inside Bus

Aniq Ur Rahman, Ushasi Ghosh, Aniruddha Chandra, Ales Prokes
Conference Papers IEEE Vehicular Networking Conference (VNC) 2018, Taipei, Taiwan

Abstract

The 5G vision acknowledges intravehicular communication as a means to enable passenger connectivity on the move. The capacity demand in a public transport vehicle is multi-fold compared to personal cars as there are more people on-board. In order to meet the demand, 5G standardization bodies prescribe moving the spectrum up to the millimetre wave (mmWave) regime. In this paper, we focus on buses as they are the most pervasive form of public transportation, and provide a wideband wireless channel model for 60GHz mmWave propagation inside bus. The model characterizes power delay profile (PDP) of the wireless intravehicular channel and is derived from about a thousand measured datasets within a bus. The proposed analytical model is further translated to a simple simulation algorithm which generates in-vehicle channel PDPs. The simulated PDPs are in good agreement with the measured data.

Hiding in Plain Sight - Symmetric Key Chaotic Image Encryption by Sequential Pixel Shuffling

Aniq Ur Rahman, Mayukh Bhattacharyya
Conference Papers Sixth International Symposium on Security in Computing and Communications (SSCC) 2018, Bangalore, India

Abstract

Security of personal information is affirmation of the right to privacy. With increasing data requirements of consumers and the bulk of archival information thereby created needs storage space and here cloud storage comes to the rescue, which however is prone to cyber attacks and needs better data security protocols as time changes. In this paper, we propose a novel symmetric-key image encryption scheme by shuffling the pixels which renders the information unintelligible. We show how our technique provides an additional layer of security on top of the regular encryption techniques. We analyze our algorithm by performing statistical and difference attack tests. We also discuss the brute force attack and its viability. The results validate effectiveness of our encryption scheme.

Enhancing Face Recognition Through Overlaying Training Images

Amrit S. Sinha, Aniq Ur Rahman, Ravi K. Kumar, Goutam Sanyal
Conference PapersSecond International Conference on Advanced Computational and Communication Paradigms (ICACCP) 2019, Sikkim, India

Abstract

In the usual face recognition approach, system is getting trained through a large number of training samples. It means in the process of training, features are extracted from all the training images individually. In this process many redundant features are required to be eliminate also. During feature elimination, some features also get suppressed due to inappropriate thresholds. So, this approach is typically time consuming and costly in the part of training. Hence, there is a requirement of feature extraction in such a way that it reduces the chance of data redundancy and system complexity. This paper presents a facial recognition technique by inclusion of superimposed version of all relevant images which improves the accuracy of the model by roughly 43 percent. The algorithm aims to establish the importance of superimposition strategy in the field of face recognition. The Haar feature based classifier is used, where a cascade function is trained from a set of images. We have used the open source database of faces from the archives of AT\&T Laboratories Cambridge to train and test our model.

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