neeraj

Neeraj

Assistant Professor
neeraj.choudhary@mahindrauniversity.edu.in

Dr. Neeraj is an Assistant Professor in the Computer Science & Engineering Department at Mahindra University École Centrale School of Engineering. He holds a Ph.D. in Computer Science and Engineering from Indian Institute of Technology Patna (March 2022). His research primarily focuses on Time Series Analysis and Data Science.

2022 - 2017

  • Indian Institute of Technology (IIT) Patna, Bihar, India, Ph.D. in Time Series Analysis, IIT Patna, 2017 – 2022

2016 - 2014

  • National Institute of Technology (NIT), Durgapur, India, Masters in Technology, Cellular Automata, NIT Durgapur, 2014 – 2016

2022 - 2017

  • Assistant Professor in GITAM University, Hyderabad from Feb- 2022 to Aug-2022
  • Research cum Teaching Assistant, Indian Institute of Technology Patna (July 2017 to February 2022)
  • FDP session at AICTE-ATAL Online FDP (Faculty Development Programme) on Signal Processing and Machine Learning for AI-Driven Healthcare Systems, Jun 2021
  • AICTE FDP-2020 Department of Computer Science and Engineering, JNTUA College of Engineering, Anantapur, Dec 2020
  • FDP session at DIT, RSET, Oct 2020
  • THE PROCESSING OF ONLINE FDP AT IGIT SARANG, Jun 2020
  • TA-ship in IITP-BSE PGCDABI course, Jun 2020 – Aug 2020

2016 - 2104

  • Teaching Assistant, National Institute of Technology Durgapur (July 2014 to June 2016)

2021

  • Neeraj, U. Satija, and J. Mathew, R.K. Behera (2021): “A Unified Attentive Cycle-Generative Adversarial Framework for Deriving Electrocardiogram from Seismocardiogram Signal”, In IEEE Signal Processing Letters (SPL).
  • Neeraj, V. Singhal, J. Mathew, and R.K. Behera (2021): “Detection of Alcoholism Using EEG Signals and a CNN-LSTM-ATTN Network”, In Elsevier Computers in Biology and Medicine (CIBM).
  • Neeraj, J. Mathew, R. K. Behera (2021): “EMD-Att-LSTM: A Data- Driven strategy Combined with Deep Learning Framework for Short Term Power Load Forecasting”, In IEEE (SGEPRI) Journal of Modern Power System and Clean Energy (MPCE).
  • Neeraj, V. Singhal, and J. Mathew (2021): “A Deep Learning Architecture for Spatio-Temporal Feature Extraction and Alcoholism Detection”, 17th IEEE-EMBS International Conference on Biomedical and Health Informatics (IEEE BHI’21).

2020

  • Neeraj, J. Mathew, M. Agarwal, R. K. Behera (2020): “Long Short Term Memory-Singular Spectrum Analysis based model for electric load forecasting”, In Springer Electrical Engineering.
  • Neeraj, J. Mathew, and R. K. Behera (2020): “Power Load Forecasting Based on Long Short Term Memory-Singular Spectrum Analysis”, In Springer Energy Systems.

Current research interests in the areas of Data Science, Time Series Analysis, Data Visualization, Time Series Forecasting, Classification and generation, Adversarial Machine Learning.

  • Developed an IoT based mobile app and website to capture the electric load consumption data using raspberry pi and serial modbus connection.
  • Developed expertise in recording EEG signals for familiarity/non- familiarity detection of signals.
  • Developed expertise in recording EEG signals for lie detection of signals.
  • Studied the impact of attention in alcoholism detection network. Introduced two intelligent models for detecting alcoholism using time series classification.