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Dr Nikesh Bajaj

Postdoctoral Research Fellow

Intelligent Systems Research Group / Machine Learning & Signal Processing, University of East London

Nikesh Bajaj has completed his PhD in Machine Learning & Signal processing from Queen Mary University of London. the Innovate UK funded project - Automation and Transparency across Financial and Legal Services, in collaboration with Intelligent Voice Ltd. and Strenuus Ltd.

  • EB1.99
    University of East London
    Docklands Campus
    University Way
    London, E16 2RD
    United Kingdom
    E16 2RD
  • n.bajaj@uel.ac.uk

    Nikesh Bajaj is a Postdoctoral Research Fellow at the University of East London, working on the Innovate UK funded project - Automation and Transparency across Financial and Legal Services, in collaboration with Intelligent Voice Ltd. and Strenuus Ltd. The project includes working with machine learning researchers, data scientists, linguistics experts and expert interrogators to model human behaviour for deception detection. He completed his PhD from Queen Mary University of London in a joint program with University of Genova. His PhD work is focused on predictive analysis of auditory attention using physiological signals e.g. EEG, PPG, GSR (Project page -http://PhyAAt.github.io). In addition to research, Nikesh has 5+ years of teaching experience. His research interests focus on signal processing, machine learning, deep learning, and optimization.

    Python Libraries:
    Nikesh has a few python libraries distributed on PYPI: spkit, pylfsr, regml, phyaat
    The details are at https://pypi.org/user/nikeshbajaj/

    Homepage:  http://nikeshbajaj.in

    Github: https://github.com/Nikeshbajaj



    Overview

    - Innovate UK funded project - Automation and Transparency across Financial and Legal Services
    - PhD Thesis - Predictive Analysis of Auditory Attention from Physiological Signals - https://PhyAAt.github.io
    - Indian Sign Language Recognition


    Collaborators

    Research

    Enhancement of A5/1: Using variable feedback polynomials of LFSR

    Bajaj, Nikesh. 2011. Emerging Trends in Networks and Computer Communications (ETNCC). pp. 55-60.

    Indian sign language recognition"

    Deora, Divya, and Nikesh Bajaj. 2012. Emerging Technology Trends in Electronics, Communication and Networking (ET2ECN). pp. 1-5.

    Audio in Image Steganography based on Wavelet Trans-form

    Kaul, Nitin, and Nikesh Bajaj. 2013. International Journal of Computer Applications 79. no. 3.

    - Fraud detection in telephone conversations for financial services using linguistic features

    - Automatic and tunable algorithm for EEG artifact removal using wavelet decomposition with applications in predictive modeling during auditory tasks

    - Auditory Attention, Implications for Serious Game Design

    - Indian sign language recognition

    Full publication list: http://nikeshbajaj.in/publication


    Extension of wavelet family in fractional fourierdomain

    Bajaj, Nikesh, and Rahul Kashyap. 2012. Emerging Technology Trends in Electronics, Communication and Networking(ET2ECN). pp. 1-4.

    Automatic and tunable algorithm for EEG artifact removal using wavelet decomposition with applications in predictive modeling during auditory tasks

    Bajaj, N., Carrión, J. R., Bellotti, F., Berta, R., & De Gloria, A.. 2020. Biomedical Signal Processing and Control 55.

    Fraud detection in telephone conversations for financial services using linguistic features

    Bajaj, Nikesh, Tracy Goodluck Constance, Marvin Rajwadi, Julie A. Wall, Mansour Moniri, Cornelius Glackin, Nigel Cannings, Chris Woodruff and James Laird.. 2019. 2019.

    Auditory Attention, Implications for Serious Game Design

    Bajaj, Nikesh, Francesco Bellotti, Riccardo Berta, Jesùs Requena Carriòn, and Alessandro DeGloria. 2018. International Conference on Games and Learning Alliance.  pp. 201-209..

    Facial Expression Recognition using Neural Network with Regularized Back-propagation Algorithm

    Dogra, Ashish Kumar, Nikesh Bajaj, and Harish Kumar Dogra. 2013. International Journal of Computer Applications 77. no. 5.

    A Neuroscience Based Approach to Game Based Learning Design

    Bajaj, Nikesh, Francesco Bellotti, Riccardo Berta, and Alessandro De Gloria. 2016. International Conference on Games and Learning Alliance. pp. 444-454.

    Publications

    Innovate UK funded project

    Funding

    Machine Learning & Signal Processing



    - Speech and Audio processing
    - Image and Video processing
    - Wavelet Analysis
    - Fractional Fourier Analysis
    - Mathematical Modelling
    - Statistical analysis/Learning
    - Classification models, multitask approach
    - Ensemble Approach
    - Feature Engineering/Analysis
    - Deeplearning: CNN & RNN

    Interests

    Portfolio

    As Teaching Assistant

    - Data Analytics

    - Coding for Scientist

    - Digital Signal Processing

    - Signals & Systems Theory

    - Security Engineering


    As Ass. Professor (India)

    - Digital Signal Processing

    - Signals & Systems

    - Advanced Transform Techniques

    - Information Theory & Coding

    - Coding & Cryptography

    Teaching