Dr Shruti Garg holds PHD degree in Computer Engineering from BIT, Mesra, Ranchi. Her area of competence and interest includes Brain Computer Interface (BCI), Machine Learning, Deep Learning and Natural Language processing. She is Assistant Professor in Department of Computer Science and Engineering at BIT, Mesra from last 16 years. She has 29 International journal and 27 International conference/book chapter publications. She has taught courses like Algorithm, Artificial Intelligence, Machine learning, Optimization and Distributed Systems in last five years. She is professional member of IEEE member (membership id 97875106) and ACM member (membership id 2149374).
A Software-defined Wrapper Discriminant Federated learning-Reinforcement Attention Adversarial Regression Approach for Privacy and Task Management in Cloud Edge Computing K Thangaraj, KS Rao, K Saikumar, S Garg Knowledge-Based Systems, 115430 , 2026 2026 Citations: 1
Unravelling emotions: exploring deep learning approaches for EEG-based emotion recognition with current challenges and future recommendations A Abgeena, S Garg Cognitive Neurodynamics 19 (1), 1-32 , 2025 2025 Citations: 2
Artificial intelligence algorithms for object detection and recognition in video and images P Dakshinamoorthy, G Rajaram, S garg, P Murugan, A Manimaran, ... Multimedia Tools and Applications 84 (29), 36089-36106 , 2025 2025 Citations: 8
NeuroEmo: A neuroimaging-based fMRI dataset to extract temporal affective brain dynamics for Indian movie video clips stimuli using dynamic functional connectivity approach … A Abgeena, S Garg, N Goyal, JR PC Computers in Biology and Medicine 194, 110439 , 2025 2025 Citations: 2
[Dataset] NeuroEmo: An fMRI Dataset for Emotion Recognition Abgeena, Garg S, Goyal N, Raj J. https://openneuro.org/datasets/ds005700/versions/1.2.0 , 2025 2025
Performance analysis of various classification algorithms for providing competency training to workplace risk prevention S Garg, P Murugan, A Manimaran, R Sundar, P Dakshinamoorthy, ... Multimedia Tools and Applications 84 (15), 15123-15149 , 2025 2025 Citations: 2
Gated Recurrent Unit for Diabetes Prediction in Voice Data PK Patidar, S Shiwani, S Garg 2025 6th International Conference on Recent Advances in Information … , 2025 2025
Human crowd behaviour analysis based on video segmentation and classification using expectation–maximization with deep learning architectures S Garg, S Sharma, S Dhariwal, WD Priya, M Singh, S Ramesh Multimedia Tools and Applications 84 (8), 4139-4161 , 2025 2025 Citations: 28
Unraveling diabetes mellitus incidence post-COVID-19: A comprehensive review of risk factors and implications PK Patidar, DK Bandil, S Garg AIP Conference Proceedings 3253 (1), 030002 , 2025 2025
An overlapping sliding window and combined features based emotion recognition system for EEG signals S Garg, RK Patro, S Behera, NP Tigga, R Pandey Applied Computing and Informatics 21 (1-2), 114-130 , 2025 2025 Citations: 40
Prediction of diabetes using machine learning classifiers with Polar Bear Optimization PK Patidar, S Shiwani, S Garg Procedia Computer Science 258, 1338-1347 , 2025 2025 Citations: 3
Brain-region specific autism prediction from electroencephalogram signals using graph convolution neural network NP Tigga, S Garg, N Goyal, J Raj, B Das Technology and Health Care 33 (1), 77-101 , 2025 2025 Citations: 13
Autism Spectrum Disorder Classification with EEG Signals Using Dense Graph Neha Prerna Tigga, Shruti Garg, Alnajjar, Fady Converging Clinical and Engineering Research on Neurorehabilitation V … , 2024 2024 Citations: 1
Autism Spectrum Disorder Classification with EEG Signals Using Dense Graph Convolution Neural Network Based on Brain Regions NP Tigga, S Garg, F Alnajjar International Conference on NeuroRehabilitation, 350-354 , 2024 2024 Citations: 1
A recurrent neural network architecture for android mobile data analysis for detecting malware infected data: P. Murugan et al. P Murugan, A Manimaran, R Sundar, P Dakshinamoorthy, G Rajaram, ... Soft Computing 28 (21), 12917-12928 , 2024 2024 Citations: 2
Role of big data analytics and the internet of things in Indian agricultural supply chain SV Singh, J Singh, S Garg, S Trivedi, S Negi International Journal of Business Information Systems 45 (2), 206-227 , 2024 2024 Citations: 3
An Efficient Summarisation and Search Tool for Research Articles S Garg, P Anand, PK Chanda, SR Payyavula Procedia Computer Science 235, 2215-2226 , 2024 2024 Citations: 1
PV-based DC-DC buck-boost converter for LED driver KAM Junaid, Y Sukhi, N Anjum, Y Jeyashree, AF Ahamed, S Debbarma, ... e-Prime-Advances in Electrical Engineering, Electronics and Energy 5, 100271 , 2023 2023 Citations: 33
S-LSTM-ATT: a hybrid deep learning approach with optimized features for emotion recognition in electroencephalogram A Abgeena, S Garg Health Information Science and Systems 11 (1), 40 , 2023 2023 Citations: 29
Speech Emotion Recognition for multiclass classification using Hybrid CNN-LSTM Neha Prerna Tigga, Shruti Garg International Journal of Microsystems and IOT 1 (1), https://doi.org/10.5281 … , 2023 2023 Citations: 8
MOST CITED SCHOLAR PUBLICATIONS
Predicting anxiety, depression and stress in modern life using machine learning algorithms A Priya, S Garg, NP Tigga Procedia Computer Science 167, 1258-1267 , 2020 2020 Citations: 606
Prediction of type 2 diabetes using machine learning classification methods NP Tigga, S Garg Procedia Computer Science 167, 706-716 , 2020 2020 Citations: 510
Breast cancer prediction using varying parameters of machine learning models P Gupta, S Garg Procedia Computer Science 171, 593-601 , 2020 2020 Citations: 191
Assessment of anxiety, depression and stress using machine learning models P Kumar, S Garg, A Garg Procedia Computer Science 171, 1989-1998 , 2020 2020 Citations: 155
Ai-based resource allocation techniques in wireless sensor internet of things networks in energy efficiency with data optimization QW Ahmed, S Garg, A Rai, M Ramachandran, NZ Jhanjhi, M Masud, ... Electronics 11 (13), 2071 , 2022 2022 Citations: 142
Optimizing cellulase production from Aspergillus flavus using response surface methodology and machine learning models A Singhal, N Kumari, P Ghosh, Y Singh, S Garg, MP Shah, PK Jha, ... Environmental Technology & Innovation 27, 102805 , 2022 2022 Citations: 66
Multilevel medical image fusion using segmented image by level set evolution with region competition S Garg, KU Kiran, R Mohan, US Tiwary 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, 7680-7683 , 2006 2006 Citations: 49
Comparison of machine learning algorithms for content based personality resolution of tweets S Garg, A Garg Social Sciences & Humanities Open 4 (1), 100178 , 2021 2021 Citations: 41
An overlapping sliding window and combined features based emotion recognition system for EEG signals S Garg, RK Patro, S Behera, NP Tigga, R Pandey Applied Computing and Informatics 21 (1-2), 114-130 , 2025 2025 Citations: 40
Efficacy of novel attention-based gated recurrent units transformer for depression detection using electroencephalogram signals NP Tigga, S Garg Health Information Science and Systems 11 (1), 1 , 2022 2022 Citations: 38
Autoregressive integrated moving average model based prediction of bitcoin close price S Garg 2018 international conference on smart systems and inventive technology … , 2018 2018 Citations: 34
Comparison of content based image retrieval systems using wavelet and curvelet transform S Das, S Garg, G Sahoo The International Journal of Multimedia & Its Applications 4 (4), 137 , 2012 2012 Citations: 34
PV-based DC-DC buck-boost converter for LED driver KAM Junaid, Y Sukhi, N Anjum, Y Jeyashree, AF Ahamed, S Debbarma, ... e-Prime-Advances in Electrical Engineering, Electronics and Energy 5, 100271 , 2023 2023 Citations: 33
S-LSTM-ATT: a hybrid deep learning approach with optimized features for emotion recognition in electroencephalogram A Abgeena, S Garg Health Information Science and Systems 11 (1), 40 , 2023 2023 Citations: 29
Human crowd behaviour analysis based on video segmentation and classification using expectation–maximization with deep learning architectures S Garg, S Sharma, S Dhariwal, WD Priya, M Singh, S Ramesh Multimedia Tools and Applications 84 (8), 4139-4161 , 2025 2025 Citations: 28
Predicting type 2 diabetes using logistic regression NP Tigga, S Garg Proceedings of the Fourth International Conference on Microelectronics … , 2020 2020 Citations: 28
A novel convolution bi-directional gated recurrent unit neural network for emotion recognition in multichannel electroencephalogram signals A Abgeena, S Garg Technology and Health Care 31 (4), 1215-1234 , 2023 2023 Citations: 18
Brain-region specific autism prediction from electroencephalogram signals using graph convolution neural network NP Tigga, S Garg, N Goyal, J Raj, B Das Technology and Health Care 33 (1), 77-101 , 2025 2025 Citations: 13
Identification of internet of things (IoT) attacks using gradient boosting: A cross dataset approach S Garg, V Kumar, SR Payyavula Telematique 21 (1), 6982-7012 , 2022 2022 Citations: 12
A comparison of prediction capabilities of Bayesian regularization and Levenberg–Marquardt training algorithms for cryptocurrencies A Priya, S Garg Smart Intelligent Computing and Applications: Proceedings of the Third … , 2019 2019 Citations: 12
Industry, Institute, or Organisation Collaboration
Dr Ashwani Garg, Faculty of Health, Biomedical Science and Medical Science, Griffith University, Queensland, 4122, Australia [International Collaborator]
Dr Ranjita Pandey, Professor, Department of Statistics, University of Delhi, Delhi [Inter University Collaborator]
Dr Neeta Kumari, Assistant Professor, Department of Civil and Environment Engineering, BIT, Mesra, Ranchi [Other Department Collaborator]
Dr Nishant Goyal, Professor, Central Institute of Psychiatry, Kanke, Ranchi [Research Data Collaborator]
Srinivasa P Rao, Head of Part, Samsung R&D Bangalore [Industry Collaborator]
