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Anuragi Arti Narayandas

Assistant Professor , School of Computing, Coimbatore

Qualification: BE, M.Tech
n_anuragiarti@cb.amrita.edu
Google Scholar Profile
Research Interest: Bio-medical Signal Processing, Artificial intelligence, Machine Learning, Deep Learning, and Image Processing

Bio Publications Work Reviewer of the journals
Bio

Arti Anuragi currently serves as an Assistant Professor in School of Computing, Amrita Vishwa Vidyapeetham, Coimbatore Campus. Her educational journey includes earning a B.E. Degree in Electronics and Communication from Parul Institute of Technology, Vadodara, Gujarat, India, in 2015, and M.Tech. Degree in Information Technology from the National Institute of Technology (NIT), Raipur, India, in 2018, and pursuing Ph.D. in the Discipline of Computer Science and Engineering from the National Institute of Technology (NIT), Raipur, India. Her academic excellence shines through as she qualified in Gate ECE in 2016. Throughout her academic career, Arti Anuragi has maintained an impressive academic record, showcasing her dedication to research and knowledge. Her research focus on various areas, including Bio-Medical Signal Processing, Non-Stationary Signal Processing, Machine Learning, Deep Learning and Image Processing. She also serves as a respected reviewer for several prestigious international journals.

Publications

Journal Article

Year : 2022

Epileptic-seizure classification using phase-space representation of FBSE-EWT based EEG sub-band signals and ensemble learners

Cite this Research Publication : Arti Anuragi, Dilip Singh Sisodia, and Ram Bilas Pachori . " Epileptic-seizure classification using phase-space representation of FBSE-EWT based EEG sub-band signals and ensemble learners. " Biomedical Signal Processing and Control,. (2022), 71, 103138. (SCIE, Impact Factor-5.076)

Publisher : Elsevier

Year : 2022

EEG-based cross-subject emotion recognition using Fourier-Bessel series expansion based empirical wavelet transform and NCA feature selection method

Cite this Research Publication : Arti Anuragi, Dilip Singh Sisodia, and Ram Bilas Pachori . " EEG-based cross-subject emotion recognition using Fourier-Bessel series expansion based empirical wavelet transform and NCA feature selection method. " Information Sciences, 610 (2022): 508-524. (SCI, Impact Factor-8.233).

Publisher : Elsevier

Year : 2021

Automated FBSEEWT based learning framework for detection of epileptic seizures using time-segmented EEG signals

Cite this Research Publication : Arti Anuragi, Dilip Singh Sisodia, and Ram Bilas Pachori . " Automated FBSEEWT based learning framework for detection of epileptic seizures using time-segmented EEG signals ". Computers in Biology and Medicine,( 2021), 136, 104708. (SCI, Impact Factor-6.698).

Publisher : Elsevier

Year : 2020

Empirical wavelet transform based automated alcoholism detecting using EEG signal features.

Cite this Research Publication : Arti Anuragi, and Dilip Singh Sisodia. " Empirical wavelet transform based automated alcoholism detecting using EEG signal features. " Biomedical Signal Processing and Control, (2020), 57, 101777. (SCIE, Impact Factor-5.076)

Publisher : Elsevier

Year : 2020

Automated alcoholism detection using Fourier-Bessel series expansion based empirical wavelet transform.

Cite this Research Publication : Arti Anuragi, Dilip Singh Sisodia, and Ram Bilas Pachori . " Automated alcoholism detection using Fourier-Bessel series expansion based empirical wavelet transform. " IEEE Sensors Journal,( 2020), 20(9), 4914-4924. (SCIE, Impact Factor-4.325)

Publisher : IEEE

Year : 2019

Alcohol use disorder detection using EEG Signal features and flexible analytical wavelet transform

Cite this Research Publication : Arti Anuragi, and Dilip Singh Sisodia. Alcohol use disorder detection using EEG Signal features and flexible analytical wavelet transform. “Biomedical Signal Processing and Control ”,( 2019), 52, 384-393. (SCIE, Impact Factor-5.076).

Publisher : Elsevier

Conference Paper

Year : 2023

Performance Evaluation of TQWT and EMD for Automated Major Depressive Disorder Detection Using EEG Signals.

Cite this Research Publication : Arti Anuragi, Dilip Singh Sisodia, Ram Bilas Pachori , and Deepak Singh. " Performance Evaluation of TQWT and EMD for Automated Major Depressive Disorder Detection Using EEG Signals. " In Machine Intelligence Techniques for Data Analysis and Signal Processing: Proceedings of the 4th International Conference MISP 2022, Volume 1, pp. 825-839. Singapore: Springer Nature Singapore, 2023.

Publisher : SpringerLink

Year : 2023

Autoencoder-Based iEEG Signal Classification for Accurate Focal and Non-focal Epilepsy Detection

Cite this Research Publication : Anjali Sagar Jangde , Arti Anuragi, and Dilip Singh Sisodia, " Autoencoder-based iEEG Signal Classification for Accurate Focal and Non-focal Epilepsy Detection ", In 4th International Conference on Electronics and Sustainable Communication Systems (ICESC - 2023), IEEE, 2023. ( Accepted ).

Publisher : Elsevier

Year : 2023

Balancing Techniques for Improving Automated Detection of Hate Speech and Offensive Language on Social Media

Cite this Research Publication : Reddy, B. Ajay Chandrasekhar, Girish Kumar Chandra, Dilip Singh Sisodia, and Arti Anuragi. " Balancing Techniques for Improving Automated Detection of Hate Speech and Offensive Language on Social Media. " In 2023 2nd International Conference for Innovation in Technology (INOCON), pp. 1-8. IEEE, 2023.

Publisher : IEEE

Year : 2018

Categorization Performance of Unsupervised Learning Techniques for Web Robots Sessions

Cite this Research Publication : Dilip Singh Sisodia, Radhika Khandelwal, Arti Anuragi. " Categorization performance of unsupervised learning techniques for web robots sessions. " International Conference on Inventive Research in Computing Applications (ICIRCA), pp. 1370-1374, IEEE, 2018.

Publisher : IEEE

Year : 2017

Sleep order detection model using support vector machines and features extracted from brain ECG signals

Cite this Research Publication : Dilip Singh Sisodia, Kunal Sachdeva, and Arti Anuragi. " Sleep order detection model using support vector machines and features extracted from brain ECG signals. " In 2017 International conference on inventive computing and informatics (ICICI), pp. 1011-1015. IEEE, 2017.

Publisher : IEEE

Year : 2017

Alcoholism detection using support vector machines and centred Correntropy features of brain EEG signals

Cite this Research Publication : Arti Anuragi, and Dilip Singh Sisodia. " Alcoholism detection using support vector machines and centred Correntropy features of brain EEG signals. " In 2017 International Conference on Inventive Computing and Informatics (ICICI) 2017 Nov 23 (pp. 1021-1026). IEEE.

Publisher : IEEE

Research

Year : 2023

Classification of focal and non-focal EEG signals using optimal geometrical features derived from a second-order difference plot of FBSE-EWT rhythms

Cite this Research Publication : Arti Anuragi, Dilip Singh Sisodia, and Ram Bilas Pachori . " Classification of focal and non-focal EEG signals using optimal geometrical features derived from a second-order difference plot of FBSE-EWT rhythms ." Artificial Intelligence in Medicine (2023): 102542. (SCI, Impact Factor-7.011).

Publisher : Elsevier

Work

Worked as Technical Program Committee member in conferences.

  1. ATCON-1-ICAIA-2023: Alliance Technology Conference-1 International Conference on Artificial Intelligence and Application -2023 Alliance University Central Campus Bengaluru, India, April 21-22, 2023.
  2. 4th International Conference on Machine Intelligence and Signal Processing (MISP-2022), March 12th-14th, 2022, National Institute of Technology Raipur, India.
  3. 4th International Conference on Information Systems and Management Science (ISMS-2021), December 14th-15th, 2022, University of Malta, Msida, Malta.
  4. 4th International Conference on Information Systems and Management Science (ISMS-2021), December 14th-15th, 2021, University of Malta, Msida, Malta.
Reviewer of the journals
  1. Biomedical Signal Processing & Control
  2. Cluster Computing
  3. IEEE Transactions on Artificial Intelligence
  4. Computers in Biology and Medicine
  5. Information Science
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