Surjeet Dalal

2.2k total citations
84 papers, 995 citations indexed

About

Surjeet Dalal is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Surjeet Dalal has authored 84 papers receiving a total of 995 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 19 papers in Computer Networks and Communications and 18 papers in Information Systems. Recurrent topics in Surjeet Dalal's work include Network Security and Intrusion Detection (10 papers), Artificial Intelligence in Healthcare (9 papers) and Cloud Data Security Solutions (8 papers). Surjeet Dalal is often cited by papers focused on Network Security and Intrusion Detection (10 papers), Artificial Intelligence in Healthcare (9 papers) and Cloud Data Security Solutions (8 papers). Surjeet Dalal collaborates with scholars based in India, Saudi Arabia and Nigeria. Surjeet Dalal's co-authors include Umesh Kumar Lilhore, Sarita Simaiya, Edeh Michael Onyema, Bijeta Seth, Dac‐Nhuong Le, Vivek Jaglan, Magdalena Rãdulescu, Senthilkumar Mohan, Gautam Srivastava and Osamah Ibrahim Khalaf and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Sensors.

In The Last Decade

Surjeet Dalal

81 papers receiving 941 citations

Peers

Surjeet Dalal

CNC

CVPR

HIM

Muhammad Saleem Pakistan

Sarita Simaiya India

J. Anuradha India

Daphne Lopez India

K. Vijayakumar India

Subhendu Kumar Pani India

Ivan Izonin Ukraine

Satvik Vats India

S. Vimal India

Revathi Sundarasekar India

Muhammad Saleem Pakistan

Surjeet Dalal

245 ×0.7

217 ×0.9

CNC

208 ×1.1

135 ×1.1

CVPR

94 ×0.8

HIM

Citations per year, relative to Surjeet Dalal Surjeet Dalal (= 1×) peers Muhammad Saleem

Countries citing papers authored by Surjeet Dalal

Since Specialization

Citations

This map shows the geographic impact of Surjeet Dalal's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Surjeet Dalal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Surjeet Dalal more than expected).

Fields of papers citing papers by Surjeet Dalal

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Surjeet Dalal. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Surjeet Dalal. The network helps show where Surjeet Dalal may publish in the future.

Co-authorship network of co-authors of Surjeet Dalal

This figure shows the co-authorship network connecting the top 25 collaborators of Surjeet Dalal. A scholar is included among the top collaborators of Surjeet Dalal based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Surjeet Dalal. Surjeet Dalal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Lilhore, Umesh Kumar, Sarita Simaiya, Surjeet Dalal, Magdalena Rãdulescu, & Daniel Balsalobre‐Lorente. (2024). Intelligent waste sorting for sustainable environment: A hybrid deep learning and transfer learning model. Gondwana Research. 146. 252–266. 10 indexed citations

Dalal, Surjeet, Umesh Kumar Lilhore, Sarita Simaiya, Magdalena Rãdulescu, & Lucian Belaşcu. (2024). Improving efficiency and sustainability via supply chain optimization through CNNs and BiLSTM. Technological Forecasting and Social Change. 209. 123841–123841. 13 indexed citations

Lilhore, Umesh Kumar, et al.. (2024). Optimizing protein sequence classification: integrating deep learning models with Bayesian optimization for enhanced biological analysis. BMC Medical Informatics and Decision Making. 24(1). 236–236. 3 indexed citations

Dalal, Surjeet, Umesh Kumar Lilhore, Nidhi Sharma, et al.. (2024). Improving smart home surveillance through YOLO model with transfer learning and quantization for enhanced accuracy and efficiency. PeerJ Computer Science. 10. e1939–e1939. 9 indexed citations

Lilhore, Umesh Kumar, Sarita Simaiya, Musaed Alhussein, et al.. (2024). An Attention‐Driven Hybrid Deep Neural Network for Enhanced Heart Disease Classification. Expert Systems. 42(2). 3 indexed citations

Dalal, Surjeet, Umesh Kumar Lilhore, Neetu Faujdar, et al.. (2024). Enhancing thyroid disease prediction with improved XGBoost model and bias management techniques. Multimedia Tools and Applications. 84(16). 16757–16788. 3 indexed citations

Dalal, Surjeet, Amit Verma, Neetu Faujdar, et al.. (2024). A Deep Learning Framework with Learning without Forgetting for Intelligent Surveillance in IoT-enabled Home Environments in Smart Cities. Recent Advances in Computer Science and Communications. 19(3). 2 indexed citations

Lilhore, Umesh Kumar, Sarita Simaiya, Surjeet Dalal, et al.. (2024). Optimizing energy efficiency in MEC networks: a deep learning approach with Cybertwin-driven resource allocation. Journal of Cloud Computing Advances Systems and Applications. 13(1). 1 indexed citations

Dalal, Surjeet, et al.. (2024). Traffic forecasting using LSTM and SARIMA models: A comparative analysis. AIP conference proceedings. 3217. 20032–20032. 1 indexed citations

10.

Lilhore, Umesh Kumar, et al.. (2024). Unveiling the prevalence and risk factors of early stage postpartum depression: a hybrid deep learning approach. Multimedia Tools and Applications. 83(26). 68281–68315. 7 indexed citations

11.

Dalal, Surjeet, Umesh Kumar Lilhore, Neetu Faujdar, et al.. (2023). Next-generation cyber attack prediction for IoT systems: leveraging multi-class SVM and optimized CHAID decision tree. Journal of Cloud Computing Advances Systems and Applications. 12(1). 19 indexed citations

12.

Onyema, Edeh Michael, et al.. (2023). Evaluation of IoT-Enabled hybrid model for genome sequence analysis of patients in healthcare 4.0. Measurement Sensors. 26. 100679–100679. 13 indexed citations

13.

Dalal, Surjeet, M. Poongodi, Umesh Kumar Lilhore, et al.. (2023). OptimizedLightGBMmodel for security and privacy issues incyber‐physicalsystems. Transactions on Emerging Telecommunications Technologies. 34(6). 5 indexed citations

14.

Lilhore, Umesh Kumar, Surjeet Dalal, & Sarita Simaiya. (2023). A cognitive security framework for detecting intrusions in IoT and 5G utilizing deep learning. Computers & Security. 136. 103560–103560. 32 indexed citations

15.

Dalal, Surjeet, et al.. (2023). Application of Machine Learning for Cardiovascular Disease Risk Prediction. Computational Intelligence and Neuroscience. 2023(1). 33 indexed citations

16.

Sharma, Yogesh Kumar, et al.. (2022). Energy Efficient Routing Protocol in Novel Schemes for Performance Evaluation. Applied System Innovation. 5(5). 101–101. 4 indexed citations

17.

Dalal, Surjeet, et al.. (2017). An Enhanced Bat Algorithm for Data Clustering Problems. International Journal of Advanced Research in Computer Science. 8(3). 141–146. 1 indexed citations

18.

Dalal, Surjeet, et al.. (2017). Adaptive Model For Integrity Verification In Cloud Computing System. International Journal of Advanced Research in Computer Science. 8(1). 233–236. 1 indexed citations

19.

Dalal, Surjeet, Vivek Jaglan, & Kamal Kumar Sharma. (2014). Designing architecture of demand forecasting tool using multi-agent system. 3(1). 11–20. 2 indexed citations

20.

Dalal, Surjeet, et al.. (2011). Analysing Supply Chain Strategy Using Case-Based Reasoning. 1(3). 40–48. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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