He is having more than twenty nine years of Teaching and twenty five years of Research experience. He has to his credit, 47 Research Papers in reputed National and International Commerce and Management Journals and also published four books one is Research, another text book and other two are Edited Books. He has been recognized as research supervisor by the Mohan Babu University and JNTU Anathapuramu, five Ph.D. Research Scholars are pursuing their Ph.D. under his guidance two of them awarded with Ph.D another Ph.D. Scholar submitted his thesis for the award of the Degree of Doctor of Philosophy. Degree by the Jawharlal Technological University, Ananthapuramu. He is Ph.D. thesis adjudicator and also a Reviewer of National and International Journals. He appointed as external examiner to Ph.D. viva-voce by the state universities. He has participated and presented more than 85 papers in both National and International Seminars / Conferences and has been invited as a Chairman to lea
EDUCATION
M.Com., (Accountancy / Cost Accountancy)
M.B.A., (Finance)
Ph.D. (Finance
RESEARCH, TEACHING, or OTHER INTERESTS
Finance, Multidisciplinary, Advanced and Specialized Nursing
Envision Future Prices of Select Power Sector Equities : An Application of an AI Model D. Sudarsana Murthy, T. Deva Prasad, J. Katyayani, B. Gangaiah Indian Journal of Finance, 2025 Purpose : This study aimed to predict impending power sector equity prices listed on the National Stock Exchange (NSE) by applying an AI Model. In a dynamic market, investors want quick and reliable information on trade trends and expected price movements. The demand for power in India has increased significantly in recent years. A research-based approach has been developed to assess and predict equity prices in order to address this paradigm, incorporating underlying market risks into the analytical framework. Methodology : To predict future stock values for four power-sector stocks with significant price volatility, the study employed sophisticated machine learning (ML) methods, such as Linear Regression, k-nearest neighbors (KNN), and long short-term memory (LSTM) neural networks. A five-year dataset, covering July 15, 2020, to July 14, 2024, was obtained for the empirical study from reliable and authoritative sources. Original Value : The study evidently demonstrated the effectiveness of cutting-edge machine learning approaches in forecasting equity values, an undertaking that has historically presented significant analytical hurdles, with the aim of improving well-informed investing strategies and sensible risk management. Findings : The consistently negative Sharpe ratios suggested that investors contemplating these stocks should take caution, since the projected returns fell short of the risk-free benchmark. Despite its ease of use and interpretability, the linear regression model found it difficult to account for the intricate, non-linear dynamics present in changes in stock prices. On the other hand, the LSTM model, a sophisticated version of recurrent neural networks, produced encouraging outcomes, giving investors more assurance to put their money into stocks.
MENTAL ILLNESS - AN ILLNESS TO WELL-BEING TOWARDS CHILDREN: REFERENCE TO SOCIO-POLITICAL VIOLENCE IN LITERATURE Sri Sakuntala S, Sarakanam Srinivas, D. Sudarsana Murthy, Monika Gadre, Jolly Masih Asia Pacific Journal of Health Management, 2024 This research paper explores the adverse impact of socio-political turmoil that has long been in existence in Assam society on the psyche of children with reference to Aruni Kashyap's The House with a Thousand Stories. This research aims to identify and understand the various psychological issues that children are subject to in a society when it is afflicted with socio-political turmoil and its consequent violence unleashed on people due to the armed struggle of the ULFA and the repressive administration of the state. The objectives of this research are (i) to study the characterization of Mamoni and Mridul, (ii) to understand and analyse the impact of socio-political turmoil on the psyche of children with reference to the above-chosen characters, (iii) to explore the connectivity between the narrative and the author’s political inclination in the novel, and (iv) to understand how objectively the historical incidents were reflected in the novel. The research is carried out by studying the chosen primary source against the pragmatic concepts of psychologists, journalists, social activists, and significant historical facts that appeared in reliable data sources such as journals, web studies, newspapers, and other publications. In conclusion, this research sheds light on the profound psychological repercussions experienced by children in Assam society amidst socio-political turmoil, as exemplified in Aruni Kashyap's "The House with a Thousand Stories." By delving into the characters of Mamoni and Mridul, analyzing the intricate interplay between narrative and political inclinations, and objectively examining historical incidents reflected in the novel, this study not only enhances our comprehension of the multifaceted impact on the psyche of children but also contributes valuable insights for policymakers, educators, and communities striving to address and mitigate the enduring consequences of such tumultuous environments on the younger generation.
Integrating Marginalized Communities into Financial Systems: The Promise of Blockchain Technology Arya Kumar, Anuj Kumar, Sweta Leena Hota, Sudarsana Murthy, Isac Gunday 2024 4th International Conference on Advancement in Electronics and Communication Engineering Aece 2024, 2024 The emergence of blockchain technology has generated considerable interest because of its ability to transform financial transactions and improve access to banking services. Industry and regulators specialists have also researched the possible of using blockchain technology to replace or even upgrade international payment systems, including correspondent banking. Blockchain’s decentralized ledger technology permits for the documentation of transactions and secure authentication. The research aims to assess the effect of blockchain on bringing marginalized people into the mainstream of financial inclusion. Its objective is to emphasize the most effective methods and knowledge gained from sustainable development endeavours. The research employs a methodical examination of existing literature to identify how blockchain technology might enhance the progress of digital financial inclusion. These applications include financial transactions, savings augmentation, credit supply, and insurance service facilitation. The results suggest that even if the many global development goals do not explicitly emphasize financial inclusion, achieving quite a few of these goals will be necessary. Therefore, using blockchain technology to enhance financial inclusion could significantly contribute to sustainable development. Hence, it is imperative for governments, especially in developing nations, to give utmost importance to investing in blockchain technology in direction to improve the availability of financial services for their population.
AI & Lean Management Principles Based Pharmaceutical Manufacturing Processes Arvinder Kour Mehta, Pritam Lanjewar, D.Sudarsana Murthy, Pallavi Ghildiyal, Rajesh Faldu, Natrayan L 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical Electronics and Computer Engineering Upcon 2023, 2023 Pharmaceutical manufacturing is a critical industry that demands high precision and efficiency while adhering to stringent quality standards. This is where artificial intelligence (AI) integration comes in and lean management principles has emerged as a powerful approach to optimizing pharmaceutical manufacturing processes. One crucial aspect of this integration is predictive maintenance, which aims to prevent equipment failures and downtime, ultimately enhancing productivity and product quality. This abstract presents a novel approach to predictive maintenance in pharmaceutical manufacturing using models based on long-term memory and recurrent neural networks. Lean management principles, known for eliminating waste and maximizing value, are applied to pharmaceutical manufacturing processes to streamline operations and improve resource utilization. AI, particularly RNN and LSTM, is employed to enhance lean principles by predicting when maintenance activities are needed and ensuring that maintenance is performed only when necessary, thus reducing unnecessary downtime and costs. RNN and LSTM models are well-suited for predictive maintenance due to their ability to analyze time-series data effectively. In this approach, data from various sensors and equipment within the manufacturing environment is collected and used as input to the models. The RNN and LSTM models learn patterns and correlations in this data to forecast potential equipment failures or maintenance requirements. By continuously monitoring equipment health and predicting maintenance needs, this system enables pharmaceutical manufacturers to proactively address issues, preventing unexpected breakdowns that can disrupt production and compromise product quality. This AI-driven predictive maintenance approach offers several advantages, including increased equipment reliability, reduced downtime, minimized maintenance costs, and improved product quality. Moreover, it aligns with lean management principles by promoting a culture of continuous improvement and resource optimization. By implementing this system, pharmaceutical manufacturers can enhance their competitiveness, meet regulatory requirements more effectively, and ensure the consistent supply of high-quality medications to patients. In conclusion, the integration of AI and lean management principles into pharmaceutical manufacturing processes, with a focus on predictive maintenance using RNN and LSTM models, offers a transformative solution to optimize operations, reduce costs, and ensure product quality. This approach represents a significant advancement in the pharmaceutical industry, aligning with the industry's commitment to innovation and excellence.
An Investigative Study of Shallow, Deep and Dense Learning Models for Breast Cancer Detection based on Microcalcifications D. Sudarsana Murthy, V. Siva Prasad, K. Aman, Madduru Poojith Kumar Reddy, K.Reddy Madhavi, Gurram Sunitha 2022 International Conference on Data Science Agents and Artificial Intelligence Icdsaai 2022, 2022 Early cancer diagnosis, detection and treatment continues to be a mammoth task in because of many challenges such as socio and cultural myths, economic conditions, access to healthcare services, healthcare practices, availability of expert oncologists etc. Mammography is a successful screening method for the breast cancer detection. Mammography captures multiple features like masses, microcalcifications etc. Microcalcifications may indicate breast cancer in its early stages and are considered to play a crucial role in early breast cancer diagnosis. In this paper, we have undertaken an investigative study for breast cancer classification by automated learning from mammography images with microcalcifications. Three types of convolutional neural architectures – shallow (ResNet101), deep (VGG101) and dense (DenseNet101) learning models are employed in this investigative study towards contributing to the objective of rapid and early breast cancer diagnosis. To improve the accuracies of the learning models, the features extracted from microcalcifications have been fed to the learning models. We have experimented with varying hyperparameter setup and have recorded the optimal performances of the three models. It has been observed that among the three models, ResNet101 model demonstrated best performance of 94.2% in benign and malicious cancer classification and also demonstrated best performance in terms of time complexity. The dense model DenseNet101 was more sensitive and specific towards the classification of breast cancer using the microcalcifications. VGG101 performed well and has worked with nearly optimal results as that of ResNet 101 with a value of 93.6%.
Demonetization effect on agriculture sector-problems and prospects Dr.D.Sudarsana Murthy, , Dr.P.V. Narasaiah, Roma Chavan, , and International Journal of Recent Technology and Engineering, 2019 Agriculture in Indian, economy shares around 50 per cent of the workforce. Farmers, who are considered as the backbone of our national economy, were sternly affected by the currency note demonetization of Indian economy. Most of the farmers who are availing loans from cooperative banks have no cash reserves to supply them. With this effect farmers were not able to buy seeds, fertilizers and other required things for farming on time. It took almost 8 weeks to resolve this issue. Till that time, farmers found it very difficult, they normally deal their transactions in cash. The cash transactions in our economy are extremely high when compared with the total number of electronic transactions carried on a daily basis. Most of the earlier studies emphasizes more about cashless payments and its advantages, Debit and Credit Cards using in retail sector, e-payments and their problems faced by the public in using plastic cards for payments etc., all these could not solve the shortage of currency in the country at a time. Eventhough there is no much difference in value and volume of currency i.e., the calculated values for the hypotheses formulated are 0.148 and 0.075 respectively, but the people were much more suffered due to the demonetization of currency by the Government due to that agriculture sector severely affected. The previous studies could not much focused on agriculture sector. Hence, this kind of specific study is highly needed in the context of demonetization. By using multi-stage random sampling technique 330 sample respondents were selected.
FinTech for a sustainable future : Bridging financial inclusion and economic progress PSR K.Balaji, D.Sudarsana Murthy, Sathyanarayana Gardasu Journal of Information & Optimization Sciences 46 (8), 2519–2528, DOI : 10 … , 2025 2025
Envision future prices of select power sector equities: An application of an AI model DS Murthy, TD Prasad, J Katyayani, B Gangaiah Indian Journal of Finance, 8-36 , 2025 2025 Citations: 1
Performance Assessment of State Bank of India During Post Merger for Sustainability – An Application of CAMEL & LSTM Models MTR D.Sudarsana Murthy, B.Gangaiah, Ravi Chand Mandalapu, P.Hari Prasad, D ... International Journal of Environmental Sciences 11 (3S), 84-102 , 2025 2025
Utilization of Financial Technologies of Banking Services Among the Selected Customers of Axis Bank, Hyderabad Region: Using Structural Equation Modeling RSC Murthy Chodisetty, D Sudarsana Murthy, Y Suryanarayana Murthy, ... International Conference on Leveraging Emerging Technologies and Analytics … , 2024 2024
A Comprehensive Study of the Elements of Organizational Healing and Their Impact on Employee Well-Being RSC Murthy Chodisetty, Y Suryanarayana Murthy, SS Prasada Rao, ... International Conference on Leveraging Emerging Technologies and Analytics … , 2024 2024
Integrating Marginalized Communities into Financial Systems: The Promise of Blockchain Technology A Kumar, A Kumar, SL Hota, S Murthy, I Gunday 2024 4th International Conference on Advancement in Electronics … , 2024 2024 Citations: 1
Stock Market Forecast with a Hybrid Model with Genetic Algorithms Assistance B Swathi, D Sudarsana Murthy, MLA Reddy, AG Shankar, Y Satyam, ... International Conference on Computer & Communication Technologies, 503-513 , 2024 2024 Citations: 1
Mental illness-an illness to well-being towards children: Reference to socio-political violence in literature SS Sakuntala, S Srinivas, DS Murthy, M Gadre, J Masih Asia Pacific Journal of Health Management 19 (1), 12-19 , 2024 2024
Original Research Article Impact of rights issue on stock price fluctuations: An analysis of select scripts DS Murthy, T Rajashekar Journal of Autonomous Intelligence 7 (5) , 2024 2024
PRESIDENT MESSAGE S Sri Sakuntala, S Srinivas, DS Murthy, M Gadre, J Masih Asia Pacific Journal of Health Management 19 (1) , 2024 2024
An Efficient License Plate Number Recognition System for Traffic Surveillance Using Deep Neural Networks A Daveedu Raju, D Valluru, D Sudarsana Murthy, P Jagadeeswara Rao, ... International Conference on Data Science, Machine Learning and Applications … , 2023 2023
A Drone Navigation system and Method to Supply Medicine to Remote Areas DDS Murthy 2023
AI & Lean management principles based pharmaceutical manufacturing processes AK Mehta, P Lanjewar, DS Murthy, P Ghildiyal, R Faldu 2023 10th IEEE Uttar Pradesh section international conference on electrical … , 2023 2023 Citations: 15
Assessing Investor Perception to Improve Effectiveness of Corporate Actions: A Study on Measures for Enhancing Corporate Action DSMTNR Rajashekar INTERNATIONAL JOURNAL OF RESEARCH IN ACADEMIC WORLD 2 (5), 1-7 , 2023 2023
An investigative study of shallow, deep and dense learning models for breast cancer detection based on microcalcifications DS Murthy, VS Prasad, K Aman, MPK Reddy, KR Madhavi, G Sunitha 2022 International conference on data science, agents & artificial … , 2022 2022 Citations: 10
Focusing on the Fintech Revolution in the financial sector research on how digitization affects financial inclusion” DDS Murthy 2022
A Method for Employees Satisfaction that reduces turnover intention of employees and Leadership DDS Murthy SK Patent South Africa Patent: 2022/04,837 , 2022 2022
Implementation of Innovational Research Model to Boost-Up Innovation among School Children DGNGN D.Sudarsana Murthy International Journal of Early Childhood Special Education (INT-JECSE) 14 (5 … , 2022 2022
Implementation of AI Pop Bots and its allied Applications for Designing Efficient Curriculum in Early Childhood Education DSM D Ganesh, M Sunil Kumar, Mr P Venkateswarlu Reddy, S Kavitha International Journal of Early Childhood Special Education (INT-JECSE) 14 (3 … , 2022 2022 Citations: 43
Digital Entrepreneurship: An Aisle For Success Of Business Enterprises A Tirupati NeuroQuantology 20 (8), 3224-3239 , 2022 2022 Citations: 3
MOST CITED SCHOLAR PUBLICATIONS
Implementation of AI Pop Bots and its allied Applications for Designing Efficient Curriculum in Early Childhood Education DSM D Ganesh, M Sunil Kumar, Mr P Venkateswarlu Reddy, S Kavitha International Journal of Early Childhood Special Education (INT-JECSE) 14 (3 … , 2022 2022.0 Citations: 43
WORK & FAMILY STRESS ON WORK LIFE BALANCE OF CORPORATE HOSPITAL DOCTORS TNR Roma Chavan, D Sudarsana Murthy Journal of Management (IJM) 12 (4), 138-149 , 2021 2021.0 Citations: 18
AI & Lean management principles based pharmaceutical manufacturing processes AK Mehta, P Lanjewar, DS Murthy, P Ghildiyal, R Faldu 2023 10th IEEE Uttar Pradesh section international conference on electrical … , 2023 2023.0 Citations: 15
An investigative study of shallow, deep and dense learning models for breast cancer detection based on microcalcifications DS Murthy, VS Prasad, K Aman, MPK Reddy, KR Madhavi, G Sunitha 2022 International conference on data science, agents & artificial … , 2022 2022.0 Citations: 10
Demonetization Effect on Agriculture Sector – Problems and Prospects PVNRC D.Sudarsana Murthy International Journal of Recent Technology and Engineering 8 (3), 288-296 , 2019 2019.0 Citations: 7
Performance of Consumer Forums: An Empirical Study of Kadapa District Consumer Forum DS Murthy, PV Narasaiah, B Mohan Prabandhan: Indian Journal of Management 6 (2), 40-47 , 2013 2013.0 Citations: 4
SSI sector in post reforms: A critical review PV Narasaiah, SD Murthy Monthly Commentary on Indian Economic Conditions 69 (591/3), 17-21 , 2009 2009.0 Citations: 4
Digital Entrepreneurship: An Aisle For Success Of Business Enterprises A Tirupati NeuroQuantology 20 (8), 3224-3239 , 2022 2022.0 Citations: 3
Performance Evaluation of MSMEs–An Empirical Study DS Murthy International Journal on Research and Development-A Management Review … , 2015 2015.0 Citations: 3
Regional Rural Banks – The Current Scenario DSM PV Narasaiah Banking Finance 18 (10), 14-17 , 2005 2005.0 Citations: 3
Operational Efficacy of State Bank of India during pre merger – An analysis by using CAMEL Model DS Murthy Journal of Critical Reviews 7 (19), 5375-5387 , 2020 2020.0 Citations: 2
Micro, Small, and Medium Enterprises (MSMEs): The Current Scenario DS Murthy, PV Narasaiah Arthshastra Indian Journal of Economics & Research 6 (5), 32-41 , 2017 2017.0 Citations: 2
Current Status of Silk Industry in India-An Evaluation NV Rathnam, PV Narasaiah, DS Murthy SEDME (Small Enterprises Development, Management & Extension Journal) 40 (4 … , 2013 2013.0 Citations: 2
AGRICULTURAL CREDIT BY REGIONAL RURAL BANKS: AN EMPIRICAL STUDY DS Murthy, PV Narasaiah, B Mohan Journal of Commerce & Accounting Research 1 (3) , 2012 2012.0 Citations: 2
MEASURING BURNOUT LEVELS & ITS RELATIONSHIP ON WORK LIFE BALANCE AMONG CORPORATE HOSPITAL DOCTORS R CHAVAN, DS MURTHY, TN REDDY Citations: 2
Envision future prices of select power sector equities: An application of an AI model DS Murthy, TD Prasad, J Katyayani, B Gangaiah Indian Journal of Finance, 8-36 , 2025 2025.0 Citations: 1
Integrating Marginalized Communities into Financial Systems: The Promise of Blockchain Technology A Kumar, A Kumar, SL Hota, S Murthy, I Gunday 2024 4th International Conference on Advancement in Electronics … , 2024 2024.0 Citations: 1
Stock Market Forecast with a Hybrid Model with Genetic Algorithms Assistance B Swathi, D Sudarsana Murthy, MLA Reddy, AG Shankar, Y Satyam, ... International Conference on Computer & Communication Technologies, 503-513 , 2024 2024.0 Citations: 1
Profitability Analysis – A Special Focus on ICICI Bank Ltd., DS Murthy International Journal of Management Studies 6 (6), 23-33 , 2019 2019.0 Citations: 1
