Translating artificial intelligence into socio-economic insight: a hybrid deep learning approach to employee financial well-being Aakanksha Uppal, Anubha Srivastava, Yashmita Awasthi, Anjita Srivastava, Barkha Kakkar Discover Artificial Intelligence, 2026 This study aims to translate recent advancements in hybrid artificial intelligence (AI) modeling into a functional tool for assessing individual financial well-being. The objective is to develop a system that aids organizations in understanding employees’ financial stress, with broader implications for enhancing workplace productivity and societal economic resilience. A deep learning pipeline was developed to classify individuals into three financial well-being categories: Financially Secure, Moderately Stable, and Financially At-Risk. The approach utilizes a structured dataset of 20,000 Indian individuals and implements 15 advanced deep learning models, including Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Gated Recurrent Units (GRU), Bidirectional Long Short-Term Memory (BiLSTM), and Wide & Deep networks. Model performance was assessed using standard evaluation metrics, including validation accuracy and ROC-AUC scores. Among the tested models, the hybrid Wide & Deep + CNN configuration yielded the highest performance, achieving a validation accuracy of 99.44% and a perfect ROC-AUC score of 1.0000. These results validate the model’s capacity for robust classification and real-world applicability to financial profiling. This study demonstrates a practical application of AI in financial decision support systems and contributes to organizational research by offering a scalable solution to assess and mitigate employee financial stress.
Digital marketing effectiveness and success factors for small and medium enterprises Aakansha Uppal, Anubha Srivastava, Yashmita Awasthi, Vaijayanti Anand, Anjita Srivastava International Journal of Entrepreneurship and Small Business, 2026 Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.
Enhancing lymphoma cancer detection using deep transfer learning on histopathological images Aakanksha Uppal, Barkha Kakkar, Prashant Johri, Yogesh Kumar, Apeksha Koul Scientific Reports, 2025 Lymphoma histopathological diagnosis is complex due to rare subtypes, morphological overlaps, and poor tumor differentiation. In this paper, an AI-based system using deep transfer learning and simulated federated learning is developed to classify two lymphoma types i.e. Chronic Lymphocytic Leukemia (CLL) and Follicular Lymphoma (FL) from a dataset of 4500 histopathological images. Six models (VGG-16, VGG-19, MobileNetV2, ResNet50, DenseNet161, and Inception V3) were evaluated across four data thresholds (0.05 to 0.2). These models used fine-tuned convolutional layers to automatically extract high-level image features relevant to tissue morphology; the extracted features were processed internally through each model's classifier, forming an end-to-end classification pipeline. DenseNet161 achieved the best classification performance across thresholds, while Inception V3 showed the highest accuracy (97.5%) and lowest RMSE (0.393) in the testing phase using deep learning. A simulated federated learning setup was also explored, where Inception V3 again outperformed other models, indicating its robustness in decentralized learning scenarios. The reported evaluation metrics loss, accuracy, precision, RMSE, F1 score, and recall, are derived from the testing phase, ensuring an accurate assessment of generalization performance. The findings highlight the efficacy of deep transfer learning in early and accurate lymphoma detection, with Inception V3 and DenseNet161 demonstrating strong performance across both learning paradigms. However, since federated learning was not fully deployed in a real-world distributed environment, its broader applicability remains a subject for future exploration.
Machine learningbased approaches for enhancing human resource management using automated employee performance prediction systems Aakanksha Uppal, Yashmita Awasthi, Anubha Srivastava International Journal of Organizational Analysis, 2025 Purpose This study focuses on enhancing the accuracy and efficiency of employee performance prediction to enhance decision making and improve organisational productivity. By introducing advance machine learning (ML) techniques, this study aims to create a more reliable and data-driven approach to evaluate employee performance. Design/methodology/approach In this study, nine machine learning (ML) models were used for forecasting employee performance: Random Forest, AdaBoost, CatBoost, LGB Classifier, SVM, KNN, XGBoost, Decision Tree and one Hybrid model (SVM + XGBoost). Each ML model is trained on an HR data set covering various features such as employee demographics, job-related factors and past performance records, ensuring reliable performance predictions. Feature scaling techniques, namely, min-max scaling, Standard Scaler and PCA, have been used to enhance the effectiveness of employee performance prediction. The models are trained to classify data, predicting whether an employee’s performance meets expectations or needs improvement. Findings All proposed models used in the study can correctly categorize data with an average accuracy of 94%. Notably, the Random Forest model demonstrates the highest accuracy across all three scaling techniques, achieving optimise accuracy, respectively. The results presented have significant implications for HR procedures, providing businesses with the opportunity to make data-driven decisions, improve personnel management and foster a more effective and productive workforce. Research limitations/implications The scope of the used data set limits the study, despite our models delivering high accuracy. Further research could extend to different data sets or more diverse organisational settings to validate the model’s effectiveness across various contexts. Practical implications The proposed ML models in the study provide essential tools for HR departments, enabling them to make more informed data driven decisions with regard to employee performance. This approach can enhance personnel management, improve workforce productivity and fostering a more effective organisational environment. Social implications Although AI models have shown promising outcomes, it is crucial to recognise the constraints and difficulties involved in their use. To ensure the fair and responsible use of AI in employee performance prediction, ethical considerations, privacy problems and any biases in the data should be properly addressed. Future work will be required to improve and broaden the capabilities of AI models in predicting employee performance. Originality/value This study introduces an exclusive combination of ML models for accurately predicting employee performance. By employing these advanced techniques, the study offers novel insight into how organisations might transition from a conventional evaluation method to a more advanced and objective, data-backed approach.
Blockchain-Enabled IoMT and Deep Learning Framework for Accurate Lung Cancer Detection and Risk Factor Evaluation Aakanksha Uppal, Barkha Kakkar, Meenakshi Kaul, Prashant Johri, Anubha Srivastava Proceedings of the 2025 14th International Conference on System Modeling and Advancement in Research Trends Smart 2025, 2025 Cellular breakdown in the lungs advances quickly, so early identification is critical, initially utilizing the Internet of Things for the beginning phase of lung cancer determination (IoT). It is becoming increasingly essential to prepare for IoT devices to ensure global IoT availability and exceptional confidence in the accuracy of the model. Each year, early illness detection saves a significant number of lives by identifying potential disease-causing pathways. Threatening development was first seen with picture processing and learning frameworks. Typically, symptoms of lung cellular breakdown don't manifest until the disease has progressed. Here is where clinical consideration proves to be the most challenging. Your fingers might start to bend, your closures might start to rise, or you might have pain when trying to swallow. This could be followed by a whistling sound, a raspiness, weight growth in front of you, and/or a swelling of the upper chest. Key symptoms of several diseases include normal or worsening chest pain, bloody or rust-colored sputum, decreased appetite, and shortness of breath. A lung CT image can be used to categorize and classify lung nodules and assess their level of concern. Although CNN emphasizes limitations such as accuracy and temporal complexity, it is less sensitive to these factors than earlier models. They possess cells with unpredictable behavior that can lead to cancer. Uncontrolled lung obliteration and growth result in different cellular breakdown types emerging in the lungs; these proceed to increase until they form an expansion. When airborne toxins come into contact with lung cells, damage results. The novel strategy being suggested is CNN.
Student satisfaction as an antecedent to employee engagement among edupreneurs: a review and future research agenda Aakanksha Uppal, Ila Sharma, Rahul Dhiman World Review of Entrepreneurship Management and Sustainable Development, 2024 The purpose of this paper is to identify determinants that predict employee engagement and student satisfaction among the edupreneurs. This purpose is achieved by reviewing the literature of past two decades published in the subject field from 2000 to 2020. This paper also assesses the knowledge and information which may be of help in understanding the findings on the different aspect of employee engagement and satisfaction. The findings of review confirm that previous studies on establishing relationship of employee engagement with student satisfaction are rare. The major drivers of employee engagement found are work environment, leadership, team and co-workers, training and career development, compensation, organisational policies, and workplace well-being. We also present future research agenda that encourage researchers to carry forward comprehensive studies in the area of employee engagement and student satisfaction.
EFFICIENCY AND PRODUCTIVITY EVALUATION OF HEALTHCARE SYSTEMS OF NORTHERN EUROPE AND THE BALTIC REGION Singh SHAILENDER, Kaul MEENAKSHI, Uppal AAKANKSHA, J Rawandale CHANDRASHEKHAR Sovremennaya Evropa, 2024 The study estimates the efficiency of healthcare systems of Northern Europe and the Baltic region countries. The analytical tools of a two-stage Data Envelopment Analysis and Malmquist DEA are applied to assess the efficiency and changes in health systems’ productivity for the studied countries. The study data is extracted from the World Development Indicators from 2000 to 2020. Evidence reveals that only nine countries have an efficient healthcare system, and the healthcare systems of Germany and Lithuania were found to be inefficient. A reference between the inefficient and the efficient countries further demonstrates that the inefficient countries outperformed the reference group. Moreover, the estimates obtained by applying the Tobit regression model show that only the Gini coefficient significantly affects the inefficiency of the healthcare systems of the studied countries. Furthermore, it is found that the total factor productivity declined by 0,1% over the period of one decade, and the decay in healthcare systems’ productivity is driven purely by technical change not by technological change. Therefore, the policy implication of the findings suggests that pursuing sound economic policies that ensure fair income distribution in the studied countries has the potential to overcome the existing level of inefficiency in the healthcare systems and subsequently lead to improvement in health outcomes.
Corporate social responsibility of small business entrepreneurs: a critical review of stakeholder’s perspective Vimal Srivastava, Aakanksha Uppal, Rahul Dhiman World Review of Entrepreneurship Management and Sustainable Development, 2023 This paper has two purposes: (i) to access how small businesses entrepreneurs are involved in Corporate Social Responsibility (CSR) and (ii) to assess the knowledge and information which may be of help in understanding the current thinking and findings on the different aspect of CSR. This paper also takes into account perceptions of various stakeholders of small business enterprises. The findings of this paper reveal that entrepreneurs engaged in small business are still to find a way to move further in CSR. CSR practices of small business entrepreneurs in various nations differed in the managerial exercises. It is found that that there is more CSR doings in Northern as compared to Southern Europe. The study recommends that small businesses have to understand that CSR actions can correspond to public relations approach, predominantly in the present market surroundings in which stakeholders might have strong concern for the welfare of the society.
How to Plan and Write for Systematic Literature Review Papers in Management Domain Rahul Dhiman, Vimal Srivastava, Anubha Srivastava, Rajni, Aakanksha Uppal Review of Management Literature, 2023 Systematic literature review (SLR) papers have gained significant importance during the last years as many reputed journals have asked for literature review submissions from the authors. However, at the same time, authors are experiencing a high number of desk rejections because of a lack of quality and its contribution to the existing body of knowledge. Therefore, the purpose of this paper is to offer guidance to researchers who intend to communicate SLR papers in top-rated journals. We attempt to offer a guide to buddy researchers who plan to write SLR papers. This purpose is achieved by clearly stating how the traditional review method is different from SLR, when and how can each type of literature review method be used, writing effective motivation of a review paper and finally how to synthesize the available literature. We have also presented a few suggestions for writing an impactful SLR in the last. Overall, this chapter serves as a guide to various aspirants of SLR paper to understand the prerequisites of an SLR paper and offers deep insights to bring in more clarity before writing an SLR paper, thereby reducing the chances of desk rejection.
IP and IoT-Based Waterside Surveillance for Early Floods Alarming System Somesh M. Bachani, Prashant Johri, Aakanksha Uppal, Meenakshi Kaul, Nitin Gaur, Sujeet Kumar Proceedings of the 2023 12th International Conference on System Modeling and Advancement in Research Trends Smart 2023, 2023 Throughout this work, an apparatus that uses machine learning, image manufacturing, or Connectivity to track riverbed water levels is given. By using the processing of images, wherein boundary detection technology is used to analyze both pictures acquired using a television camera, such an approach is designed to determine the level of a shoreline and the level of the stream. The stream's water grade plus the shoreline rating are compared to calculate the flood intensity rating. The storm's intensity was then uploaded to an Internet of Things system. Once the water's intensity exceeded a specific critical level, a notice was delivered to the public via the popular social networking site Telegram. Within the aforementioned architecture gadget, a Banana Pi 3 B variant is employed as both a controlling device and a camera using the Banana Pi 5MP cameras package. Ubidots is an Internet of Things system that is employed, and it allows for user notification. Our work's major contributions focus on integrating image processing using Internet of things clouds to create an advanced flood tracking device in response to warming temperatures by identifying the flooding extent and warning individuals about the flooding harshness condition. According to experimental findings, combining machine vision using machine learning for image analysis using the Internet of Things Cloud infrastructure is a realistic strategy. In order to determine the liquid level versus bank straight, the paper compares the creepy-edge detection approach and reaching the point technique. To determine whether this device might function in the real world, it was additionally tested in both lab (indoor) as well as outdoor environments.
A study on quality of work life(QWL), organization commitment in educational institution International Journal of Advanced Science and Technology, 2020
GST: Awareness and perception of small business persons’ (SBPS) International Journal of Innovative Technology and Exploring Engineering, 2019
A study on behavior and preferences of individual investors towards investments with special reference to Delhi NCR International Journal of Innovative Technology and Exploring Engineering, 2019
Mediating factors impacting financial inclusion index (FII) - A step towards sustainable development of bottom of pyramid (BoP) International Journal of Economic Research, 2017
RECENT SCHOLAR PUBLICATIONS
Translating artificial intelligence into socio-economic insight: a hybrid deep learning approach to employee financial well-being A Uppal, A Srivastava, Y Awasthi, A Srivastava, B Kakkar Discover Artificial Intelligence , 2026 2026
Digital marketing effectiveness and success factors for small and medium enterprises Y Awasthi, A Srivastava, A Uppal, V Anand, A Srivastava International Journal of Entrepreneurship and Small Business 58 (1), 85-109 , 2026 2026
Blockchain-Enabled IoMT and Deep Learning Framework for Accurate Lung Cancer Detection and Risk Factor Evaluation A Uppal, B Kakkar, M Kaul, P Johri, A Srivastava 2025 14th International Conference on System Modeling & Advancement in … , 2025 2025
Enhancing lymphoma cancer detection using deep transfer learning on histopathological images A Uppal, B Kakkar, P Johri, Y Kumar, A Koul Scientific Reports 15 (1), 38042 , 2025 2025 Citations: 3
Machine learningbased approaches for enhancing human resource management using automated employee performance prediction systems A Uppal, Y Awasthi, A Srivastava International Journal of Organizational Analysis 33 (8), 2307-2346 , 2025 2025 Citations: 11
Efficiency and Productivity Evaluation of Healthcare Systems of Northern Europe and the Baltic Region S Singh, M Kaul, A Uppal, CJ Rawandale Современная Европа, 176-188 , 2024 2024 Citations: 1
Student satisfaction as an antecedent to employee engagement among edupreneurs: a review and future research agenda A Uppal, I Sharma, R Dhiman World Review of Entrepreneurship, Management and Sustainable Development 20 … , 2024 2024 Citations: 11
Corporate social responsibility of small business entrepreneurs: a critical review of stakeholder's perspective V Srivastava, A Uppal, R Dhiman World Review of Entrepreneurship, Management and Sustainable Development 20 … , 2024 2024 Citations: 4
IP and IoT-Based Waterside Surveillance for Early Floods Alarming System SM Bachani, P Johri, A Uppal, M Kaul, N Gaur, S Kumar 2023 12th International Conference on System Modeling & Advancement in … , 2023 2023 Citations: 2
How to plan and write for systematic literature review papers in management domain R Dhiman, V Srivastava, A Srivastava, A Uppal 2023 Citations: 37
Role of power distance phenomena in blended learning in higher education post-COVID-19 B Wadhwa, P Grover, S Dasgupta, A Uppal Cardiometry, 343-350 , 2022 2022 Citations: 4
An Examination of green HR practices and its impact on environmental sustainability A Uppal, B Kakkar, Y Awasthi International Journal of Recent Technology and Engineering 8, 100-105 , 2022 2022 Citations: 4
The Effects of the Stakeholders Relationship Management on Organization Performance MS Aslami, A Uppal REVISTA GEINTEC-GESTAO INOVACAO E TECNOLOGIAS 11 (4), 5454-5467 , 2021 2021 Citations: 1
JOB SATISFACTION AND MOTIVATION: PREDICTORS OF EMPLOYEE PERFORMANCE S Altekar International Journal of Modern Agriculture 10 (2), 27-36 , 2021 2021
BIOLOGICAL AND PARENTAL PREDICTORS: IMPACT ON ADOLESCENT BEHAVIOR AU Davinder Kaur Sohi Shrirang Dattatraya Altekar,Bharti Wadhwa International Journal of Modern Agriculture 10 (Issue No.2, 2021), Pages 37-49 , 2021 2021
A STUDY ON QUALITY OF WORK LIFE(QWL), ORGANIZATION COMMITMENT IN EDUCATIONAL INSTITUTION DAU Ms. Davinder Kaur Dr. Bharti Wadhwa Journal International Journal of Advanced Science and Technology 29 (4 … , 2020 2020 Citations: 3
Ethics of advertisement and marketing policies: an Indian perspective Y Awasthi Rupkatha Journal on Interdisciplinary Studies in Humanities 12 (1) , 2020 2020 Citations: 6
Women’s Work Life Balance and CSR D Singh, D Awasthi, D Uppal Int. J. Adv. Sci. Technol 29 (9), 3953-3958 , 2020 2020 Citations: 2
GST: awareness and perception of small business persons (SBPs A Uppal, B Wadhwa, A Vashisht, D Kaur International Journal of Innovative Technology and Exploring Engineering 8 … , 2019 2019 Citations: 16
A study on behavior and preferences of individual investors towards investments with special reference to Delhi NCR B Wadhwa, A Uppal, A Vashisht, D Kaur International Journal of Innovative technology and exploring engineering … , 2019 2019 Citations: 14
MOST CITED SCHOLAR PUBLICATIONS
How to plan and write for systematic literature review papers in management domain R Dhiman, V Srivastava, A Srivastava, A Uppal 2023 Citations: 37
GST: awareness and perception of small business persons (SBPs A Uppal, B Wadhwa, A Vashisht, D Kaur International Journal of Innovative Technology and Exploring Engineering 8 … , 2019 2019 Citations: 16
Magnitudes of attractiveness in employer branding: generation Z A Uppal, B Wadhwa, A Vashisht International Journal of Applied Business and Economic Research 15 (23), 1-7 , 2017 2017 Citations: 16
A study on behavior and preferences of individual investors towards investments with special reference to Delhi NCR B Wadhwa, A Uppal, A Vashisht, D Kaur International Journal of Innovative technology and exploring engineering … , 2019 2019 Citations: 14
Machine learningbased approaches for enhancing human resource management using automated employee performance prediction systems A Uppal, Y Awasthi, A Srivastava International Journal of Organizational Analysis 33 (8), 2307-2346 , 2025 2025 Citations: 11
Student satisfaction as an antecedent to employee engagement among edupreneurs: a review and future research agenda A Uppal, I Sharma, R Dhiman World Review of Entrepreneurship, Management and Sustainable Development 20 … , 2024 2024 Citations: 11
Stydy of Attitude of Delhi Shoppers Towards Mall Shopping Experience A Vashisht, B Wadhwa, A Uppal Journal of Research in Commerce and Management 3 (10), 42-50 , 2014 2014 Citations: 9
Attitude towards green marketing AK Anubha Vashisht, Bharti Wadhwa National Conference on Emerging Challenges for Sustainable Business held at … , 2012 2012 Citations: 7
Ethics of advertisement and marketing policies: an Indian perspective Y Awasthi Rupkatha Journal on Interdisciplinary Studies in Humanities 12 (1) , 2020 2020 Citations: 6
Corporate social responsibility of small business entrepreneurs: a critical review of stakeholder's perspective V Srivastava, A Uppal, R Dhiman World Review of Entrepreneurship, Management and Sustainable Development 20 … , 2024 2024 Citations: 4
Role of power distance phenomena in blended learning in higher education post-COVID-19 B Wadhwa, P Grover, S Dasgupta, A Uppal Cardiometry, 343-350 , 2022 2022 Citations: 4
An Examination of green HR practices and its impact on environmental sustainability A Uppal, B Kakkar, Y Awasthi International Journal of Recent Technology and Engineering 8, 100-105 , 2022 2022 Citations: 4
Turbulent Times in The Indian Aviation Sector: Case of Jet Airways A Uppal Globus An International Journal of Management & IT 10 (1), 16-19 , 2018 2018 Citations: 4
Enhancing lymphoma cancer detection using deep transfer learning on histopathological images A Uppal, B Kakkar, P Johri, Y Kumar, A Koul Scientific Reports 15 (1), 38042 , 2025 2025 Citations: 3
A STUDY ON QUALITY OF WORK LIFE(QWL), ORGANIZATION COMMITMENT IN EDUCATIONAL INSTITUTION DAU Ms. Davinder Kaur Dr. Bharti Wadhwa Journal International Journal of Advanced Science and Technology 29 (4 … , 2020 2020 Citations: 3
IP and IoT-Based Waterside Surveillance for Early Floods Alarming System SM Bachani, P Johri, A Uppal, M Kaul, N Gaur, S Kumar 2023 12th International Conference on System Modeling & Advancement in … , 2023 2023 Citations: 2
Women’s Work Life Balance and CSR D Singh, D Awasthi, D Uppal Int. J. Adv. Sci. Technol 29 (9), 3953-3958 , 2020 2020 Citations: 2
Efficiency and Productivity Evaluation of Healthcare Systems of Northern Europe and the Baltic Region S Singh, M Kaul, A Uppal, CJ Rawandale Современная Европа, 176-188 , 2024 2024 Citations: 1
The Effects of the Stakeholders Relationship Management on Organization Performance MS Aslami, A Uppal REVISTA GEINTEC-GESTAO INOVACAO E TECNOLOGIAS 11 (4), 5454-5467 , 2021 2021 Citations: 1
Translating artificial intelligence into socio-economic insight: a hybrid deep learning approach to employee financial well-being A Uppal, A Srivastava, Y Awasthi, A Srivastava, B Kakkar Discover Artificial Intelligence , 2026 2026
