Fully Funded by Ministry of Education, Govt. of India

शिक्षा मंत्रालय, भारत सरकार द्वारा वित्त पोषित

Dr. Anjali

Dr. Anjali

Designation: Assistant Professor

Department: Information Technology

Honour: Ph.D. (IIIT Allahabad)

Area of Interest: Time Series Data Mining, Time Series Analysis, Machine Learning, Deep Learning.

Address: Room No. A-118, Department of IT, A Block, ABV-IIITM Gwalior

Email: anjali@iiitm.ac.in


Anjali completed her B. Tech (Computer Science Engineering) from U.I.E.T. CSJM University, Kanpur. She did her Masters in Information Technology and also Ph.D. in Information Technology from Indian Institute of Information Technology, Allahabad. She has worked in organizations such as GLA University, Mathura, Vellore Institute of Technology, Amaravati, and JK Lakshmipat University, Jaipur. She was awarded for Central Sector Scheme Scholarship by the Central Board of Secondary Education and Ministry of Human Resource Development, 2008-2012. Her research interests include time series analysis, time series data mining, machine learning, and deep learning.

  • Anjali, Hong-Ning Dai, Jitendra Kumar, and Om Jee Pandey, “AERed: An Autoencoder-decoder Dimensionality Reduction Method for Wearable-Based Human Activity Recognition”, IEEE Sensors Journal, 2023. (SCI) DOI: 10.1109/JSEN.2023.3323328.
  • Anjali and Vrijendra Singh, “CLR-based deep convolutional spiking neural network with validation based stopping for time series classification," Applied Intelligence, Springer, 50, 830–848, Oct. 2019, https://doi.org/10.1007/s10489-019-01552-y. (SCI) Electronic ISSN: 1573-7497 Print ISSN: 0924-669X 
  • Anjali and Vrijendra Singh, “CNN-VSR: A deep learning architecture with validation based stopping rule for time series classification," Applied Artificial Intelligence, Taylor and Francis,  Vol. 34, Issue 2, Pages 101-124  18 Jan. 2020, https://doi.org/10.1080/08839514.2020.1713454. (SCI) Print ISSN: 0883-9514 Online ISSN: 1087-6545.
  • Anjali and Vrijendra Singh, “Parametric versus non-parametric time series forecasting methods: a review" Journal of Engineering Science and Technology Review, Vol. 13, Issue 3, pp. 165 – 171, 2020. (Scopus) ISSN: 1791-2377.
  • Hrishikesh Jaiswal, Anjali, and K.V.Arya, “Stock Price Prediction using Fuzzy-RNN and Portfolio Management with Genetic Algorithm,” 8th International Conference on Intelligent Technologies (ICIT– 2023), University of Matana, Jakarta, Indonesia, Dec 2023. (Scopus).
  • Mohammad Okasha Anjum, Anjali and K.V.Arya, “Leveraging Computational Techniques for Accurate Diagnosis of Early-Onset Alzheimer’s Disease,” 8th International Conference on Intelligent Technologies (ICIT – 2023), University of Matana, Jakarta, Indonesia, Dec 2023. (Scopus).
  • Anjali and Vrijendra Singh, “A novel approach for decomposition of financial time series," IEEE International Conference on Recent Innovations in Signal Processing and Embedded Systems (RISE), MANIT Bhopal, India, Oct. 2017, pp. 537-542. 
  • Anjali and Vrijendra Singh, “Comparison of different NN training functions of NARX architecture for financial time series," IEEE International Conference on Industrial and Information Systems (ICIIS), University of Peradeniya, Sri-Lanka, Dec. 2017, pp. 1-6. 
  • Karthika Natarajan, Anjali, Ramya Venigalla and Veeramachaneni Jhansi Lekha, “Medical Information Modeling for Diabetes Based on Logistic Regression,” Handbook of Research on Mathematical Modeling for Smart Healthcare Systems, IGI Global, 2022, pp. 279-305. DOI:10.4018/978-1-6684-4580-8.ch015.
  • Payal Mahajan, Anjali, and Lisna P C, “Prediction of Human Emotions by Neural Oscillations”, “International Journal of Modern Developments in Engineering and Science” vol. 1, no. 10, pp. 23–27, Oct. 2022. 
  • Koteswara Rao Makkena, Anjali and Karthika Natarajan Singh, “Machine Learning and Future Directions,” Data Science with Semantic Technologies: A New Trend and Future Development’,CRC, Taylor and Francis. (ISBN: 9781032316666)

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