Dr. D. Srinivasa Kumar

EDUCATION

M.B.A., Ph.D

RESEARCH, TEACHING, or OTHER INTERESTS

Finance, Business, Management and Accounting, Marketing, Multidisciplinary

Scopus Publications

Flood damage in India: A deep convolutional neural network approach to assessing the loss of livelihoods, economic conditions and infrastructure
K. V. Satyanarayana, S. Prasada Rao, D. Srinivasa Kumar
Aip Conference Proceedings, 2025
Floods cause severe damage and loss of life globally.Traditional drainage systems struggle with increased rainfall due to urban development.This paper proposes a new flood detection method that combines satellite imagery with computer vision and deep learning.Our approach analyzes various satellite data to identify flood markers and pinpoint flooded areas.Assessed against existing methods, our approach shows high accuracy across diverse flood scenarios.Our study introduces a new method that combines satellite images with computer vision and deep learning to spot floods better.It is on the grounds that the dangers to the livelihood techniques end up in pay decrease.By analyzing different types of satellite data, we identify important flood signs and use advanced computer programs to pinpoint flooded areas.We evaluate our method with real flood data and compare it to other detection methods.Results show that our approach is highly dependable across various flood situations and locations.
Sustainable Brand Positioning in Indian FMCG Sector: A Multi-Criteria Decision-Making Approach
Srinivasa Kumar D, Jikku Susan Kurian, Bindu Madhavi N, Devanna H, Parveen Sharma, Manoj Kumar Nellore
Asian Journal of Interdisciplinary Research, 2025
Sustainable brand positioning has emerged as a strategic imperative in the Indian fast-moving consumer goods (FMCG) sector, driven by evolving consumer values, regulatory shifts, and environmental challenges. This study adopts a structured Multi-Criteria Decision-Making (MCDM) approach, employing Interpretive Structural Modeling (ISM) and MICMAC analysis to identify and analyze the interrelationships among eight key enablers of sustainable brand positioning. The findings reveal a clear hierarchical structure, with environmental concern and innovation capability identified as foundational drivers, while consumer trust and cost considerations serve as sensitive linkage variables. Digital influence and stakeholder engagement emerge as outcome factors, largely shaped by upstream strategic actions. The MICMAC classification further confirms these dynamics by categorizing variables into driver, linkage, dependent, and autonomous groups. These insights provide actionable guidance for brand managers and policymakers seeking to embed sustainability into brand strategy. The study contributes to the sustainability and marketing literature by offering a systems-based framework tailored to the Indian FMCG context, with implications for strategic planning, stakeholder engagement, and long-term brand equity development.
Artificial Intelligence in Financial Management: Automating Risk Assessment and Investment Strategies
Mohammed Faez Hasan, Vibha Suraj Bhusari, Laxmana Rao Goranta, Dharmaraj A, Srinivasa Kumar, Joshuva Arockia Dhanraj
3rd International Conference on Advances in Computing Communication and Materials Icaccm 2024, 2024
The following research paper aims to highlight the idea of the use of AI in financial management and particularly in risk analysis and management of investment portfolios. The study also shows how the Kaggle real-world datasets can be used to perform a regression analysis and sentiment analysis, to process vast amount of financial data to determine the market trends and risks with high accuracy. It also emphasizes the ability of AI in improving the performance in the decision making and the reduction of the human error that is key in risk and return management in investment. The paper also outlines possibilities for the further development of AI in managing the finances, with the focus on the employment of deep learning approaches and the real-time data processing to advance the financial sustainability and create novelties. Still, this study provides the foundation for future rich studies of AI’s applied impacts on the sophistication of financial management practices in the industry.
Design and Development of Data-Driven Product Recommender Model for E-Commerce using Behavioral Analytics
International Journal of Intelligent Systems and Applications in Engineering, 2024
A stochastic process of software fault detection and correction for business operations
D. Srinivasa Kumar, Akuthota Sankar Rao, Nellore Manoj Kumar, N. Jeebaratnam, M. Kalyan Chakravarthi, S. Bhargavi Latha
Journal of High Technology Management Research, 2023
Attributes influencing home loan borrowers in selecting housing finance companies in India
International Journal of Scientific and Technology Research, 2020
Demographic characteristics as cognitive elements to measure the service quality of housing finance companies in India
International Journal of Scientific and Technology Research, 2019
A few demographic factors affecting the decline of total fertility rate: An empirical evidence
International Journal of Mechanical Engineering and Technology, 2019
The business philosophies for extended enterprise in manufacturing automobile sectors
D. Srinivas Kumar et al., D. Srinivas Kumar et al., and
International Journal of Mechanical and Production Engineering Research and Development, 2018
them, but customized to its own conditions, in one shape or the other, to guarantee its success.
A logical investigation of demographic characteristics of human population in selected area of Srikakulam district
International Journal of Mechanical Engineering and Technology, 2018
Housing finance snags faced by Indian home loan mortgagors: A matter-of-fact study
D. Srinivasa Kumar
Indian Journal of Finance, 2017