Dr. Anjali

Biography

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.

• A. Anjali, Vrijendra Singh and Jitendra Kumar, " GSSX: Golden Section-Based Symbolic Representation for Reducing Time Series Dimensionality," International Journal of Data Science and Analytics, 2025 (Accepted)
• Aditya Raj, A. Anjali, Vishal Krishna Singh, and Vijay Bhaskar Semwal, "Mapping Urban Heat Islands in Pune, India: Ecological Impacts and Environmental Challenges," Remote Sensing Letters, Taylor and Francis, 2025 (Accepted).
• Jitendra Kumar, Deepika Saxena, Jatinder Kumar, Abhilash Bhadoria, A. Anjali,  and Ashutosh Kumar Singh, "A hybrid neural network and cooperative PSO model for dynamic cloud workloads prediction," Computing 107, 72 (2025).
• Anjali, H. -N. Dai, J. Kumar and O. J. Pandey, "AERed: An Autoencoder–Decoder Dimensionality Reduction Method for Wearable-Based Human Activity Recognition," in IEEE Sensors Journal, vol. 23, no. 23, pp. 29804-29814, 1 Dec.1, 2023
• Anjali, D. Singh, O. J. Pandey and H. -N. Dai, "STCNN: Combining SMOTE-TOMEK With CNN for Imbalanced Classification of Alzheimer's Disease," in IEEE Sensors Letters, vol. 8, no. 3, pp. 1-4, March 2024.
• 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.
• 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.
• 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.
• Vaidya Sunil, A. Anjali, and Deepak Dewangan, "Enhanced BiLSTM for Traffic Police Gesture Recognition in Autonomous Vehicles,"  IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, ABV-IIITM Gwalior, Dec 2024.
• ES Thejas, Harshith Mente, P Yushmanth, Pullapati Harshith, and A. Anjali, "Machine Learning Solutions for Early and Accurate Breast Cancer Detection,"  IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, ABV-IIITM Gwalior, Dec 2024.
• CH Sai Surya, GLVS Kirti, K Satya Saketh, P Sri Charan and A. Anjali, "Optimizing Job Matching Through Automated Resume Screening with NLP and Machine Learning,"  IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, ABV-IIITM Gwalior, Dec 2024.
• Kumar Lakshya, Alok Kamal and A. Anjali, "Dual-Stage Inpainting Approach for Character Reconstruction in Ancient Hindi Texts," 3rd International Conference on Computer Vision and Machine Intelligence, 2024. IIIT-Allahabad, Oct, 2024.
• 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. 
• 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.
• 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)