Email this article Computational Psychometrics: Leveraging Machine Learning for Educational Assessment
Abstract
Psychometric evaluations have traditionally relied on static tests to assess learner abilities. This paper introduces computational psychometrics, a novel approach that integrates machine learning techniques to analyze educational behavior dynamically. Using data from online learning platforms, the proposed models predict student performance, identify knowledge gaps, and provide personalized learning recommendations. Comparative analysis with traditional methods shows that machine learning-based psychometric models offer superior accuracy and scalability, paving the way for more effective and inclusive educational assessment systems.
References
Davuluri, M. (2024). An Overview of Natural Language Processing in Analyzing Clinical Text Data for Patient Health Insights. Research-gate journal, 10(10).
Davuluri, M., & Yarlagadda, V. S. T. (2024). NOVEL DEVICE FOR ENHANCING TUBERCULOSIS DIAGNOSIS FOR FASTER, MORE ACCURATE SCREENING RESULTS. International Journal of Innovations in Engineering Research and Technology, 11(11).
Davuluri, M. (2022). Comparative Study of Machine Learning Algorithms in Predicting Diabetes Onset Using Electronic Health Records. Research-gate journal, 8(8).
Davuluri, M. (2020). AI-Driven Predictive Analytics in Patient Outcome Forecasting for Critical Care. Research-gate journal, 6(6).
Davuluri, M. (2018). Revolutionizing Healthcare: The Role of AI in Diagnostics, Treatment, and Patient Care Integration. International Transactions in Artificial Intelligence, 2(2).
Davuluri, M. (2018). Navigating AI-Driven Data Management in the Cloud: Exploring Limitations and Opportunities. Transactions on Latest Trends in IoT, 1(1), 106-112.
Vattikuti, M. C. (2024). Improving Drug Discovery and Development Using AI: Opportunities and Challenges. Research-gate journal, 10(10).
Vattikuti, M. C. (2022). Comparative Analysis of Deep Learning Models for Tumor Detection in Medical Imaging. Research-gate journal, 8(8).
Vattikuti, M. C. (2020). A Comprehensive Review of AI-Based Diagnostic Tools for Early Disease Detection in Healthcare. Research-gate journal, 6(6).
Vattikuti, M. C. (2018). Leveraging Edge Computing for Real-Time Analytics in Smart City Healthcare Systems. International Transactions in Artificial Intelligence, 2(2).
Vattikuti, M. C. (2018). Leveraging AI for Sustainable Growth in AgTech: Business Models in the Digital Age. Transactions on Latest Trends in IoT, 1(1), 100-105.
Vattikuti, M. C. (2017). Ethical Framework for Integrating IoT in Urban Healthcare Systems. International Transactions in Artificial Intelligence, 1(1).
Kolla, V. R. K. (2020). Forecasting the Future of Crypto currency: A Machine Learning Approach for Price Prediction. International Research Journal of Mathematics, Engineering and IT, 7(12).
Kolla, V. R. K. (2018). Forecasting the Future: A Deep Learning Approach for Accurate Weather Prediction. International Journal in IT & Engineering (IJITE).
Kolla, V. R. K. (2016). Analyzing the Pulse of Twitter: Sentiment Analysis using Natural Language Processing Techniques. International Journal of Creative Research Thoughts.
Kolla, V. R. K. (2015). Heart Disease Diagnosis Using Machine Learning Techniques In Python: A Comparative Study of Classification Algorithms For Predictive Modeling. International Journal of Electronics and Communication Engineering & Technology.
Kolla, V. R. K. (2020). Paws And Reflect: A Comparative Study of Deep Learning Techniques For Cat Vs Dog Image Classification. International Journal of Computer Engineering and Technology.
Kolla, V. R. K. (2016). Forecasting Laptop Prices: A Comparative Study of Machine Learning Algorithms for Predictive Modeling. International Journal of Information Technology & Management Information System.
Kolla, V. R. K. (2021). Cyber security operations centre ML framework for the needs of the users. International Journal of Machine Learning for Sustainable Development, 3(3), 11-20.
Velaga, S. P. (2014). DESIGNING SCALABLE AND MAINTAINABLE APPLICATION PROGRAMS. IEJRD-International Multidisciplinary Journal, 1(2), 10.
Velaga, S. P. (2016). LOW-CODE AND NO-CODE PLATFORMS: DEMOCRATIZING APPLICATION DEVELOPMENT AND EMPOWERING NON-TECHNICAL USERS. IEJRD-International Multidisciplinary Journal, 2(4), 10.
Velaga, S. P. (2017). “ROBOTIC PROCESS AUTOMATION (RPA) IN IT: AUTOMATING REPETITIVE TASKS AND IMPROVING EFFICIENCY. IEJRD-International Multidisciplinary Journal, 2(6), 9.
Velaga, S. P. (2018). AUTOMATED TESTING FRAMEWORKS: ENSURING SOFTWARE QUALITY AND REDUCING MANUAL TESTING EFFORTS. International Journal of Innovations in Engineering Research and Technology, 5(2), 78-85.
Velaga, S. P. (2020). AIASSISTED CODE GENERATION AND OPTIMIZATION: LEVERAGING MACHINE LEARNING TO ENHANCE SOFTWARE DEVELOPMENT PROCESSES. International Journal of Innovations in Engineering Research and Technology, 7(09), 177-186.
Gatla, T. R. An innovative study exploring revolutionizing healthcare with ai: personalized medicine: predictive diagnostic techniques and individualized treatment. International Journal of Creative Research Thoughts (IJCRT), ISSN, 2320-2882.
Gatla, T. R. ENHANCING CUSTOMER SERVICE IN BANKS WITH AI CHATBOTS: THE EFFECTIVENESS AND CHALLENGES OF USING AI-POWERED CHATBOTS FOR CUSTOMER SERVICE IN THE BANKING SECTOR (Vol. 8, No. 5). TIJER–TIJER–INTERNATIONAL RESEARCH JOURNAL (www. TIJER. org), ISSN: 2349-9249.
Gatla, T. R. (2017). A SYSTEMATIC REVIEW OF PRESERVING PRIVACY IN FEDERATED LEARNING: A REFLECTIVE REPORT-A COMPREHENSIVE ANALYSIS. IEJRD-International Multidisciplinary Journal, 2(6), 8.
Gatla, T. R. (2019). A CUTTING-EDGE RESEARCH ON AI COMBATING CLIMATE CHANGE: INNOVATIONS AND ITS IMPACTS. INNOVATIONS, 6(09).
Gatla, T. R. “A GROUNDBREAKING RESEARCH IN BREAKING LANGUAGE BARRIERS: NLP AND LINGUISTICS DEVELOPMENT. International Journal of Creative Research Thoughts (IJCRT), ISSN, 2320-2882.
Gatla, T. R. (2018). AN EXPLORATIVE STUDY INTO QUANTUM MACHINE LEARNING: ANALYZING THE POWER OF ALGORITHMS IN QUANTUM COMPUTING. International Journal of Emerging Technologies and Innovative Research (www. jetir. org), ISSN, 2349-5162.
Gatla, T. R. MACHINE LEARNING IN DETECTING MONEY LAUNDERING ACTIVITIES: INVESTIGATING THE USE OF MACHINE LEARNING ALGORITHMS IN IDENTIFYING AND PREVENTING MONEY LAUNDERING SCHEMES (Vol. 6, No. 7, pp. 4-8). TIJER–TIJER–INTERNATIONAL RESEARCH JOURNAL (www. TIJER. org), ISSN: 2349-9249.
Gatla, T. R. (2020). AN IN-DEPTH ANALYSIS OF TOWARDS TRULY AUTONOMOUS SYSTEMS: AI AND ROBOTICS: THE FUNCTIONS. IEJRD-International Multidisciplinary Journal, 5(5), 9.
Pindi, V. (2018). NATURAL LANGUAGE PROCESSING(NLP) APPLICATIONS IN HEALTHCARE: EXTRACTING VALUABLE INSIGHTS FROM UNSTRUCTURED MEDICAL DATA. International Journal of Innovations in Engineering Research and Technology, 5(3), 1-10.
Pindi, V. (2019). A AI-ASSISTED CLINICAL DECISION SUPPORT SYSTEMS: ENHANCING DIAGNOSTIC ACCURACY AND TREATMENT RECOMMENDATIONS. International Journal of Innovations in Engineering Research and Technology, 6(10), 1-10.
PINDI, V. (2022). ETHICAL CONSIDERATIONS AND REGULATORY COMPLIANCE IN IMPLEMENTING AI SOLUTIONS FOR HEALTHCARE APPLICATIONS. IEJRD-International Multidisciplinary Journal, 5(5), 11.
Deekshith, A. (2019). Integrating AI and Data Engineering: Building Robust Pipelines for Real-Time Data Analytics. International Journal of Sustainable Development in Computing Science, 1(3), 1-35.
Deekshith, A. (2020). AI-Enhanced Data Science: Techniques for Improved Data Visualization and Interpretation. International Journal of Creative Research In Computer Technology and Design, 2(2).
Deekshith, A. (2021). Data engineering for AI: Optimizing data quality and accessibility for machine learning models. International Journal of Management Education for Sustainable Development, 4(4), 1-33.
Deekshith, A. (2022). Cross-Disciplinary Approaches: The Role of Data Science in Developing AI-Driven Solutions for Business Intelligence. International Machine learning journal and Computer Engineering, 5(5).
Deekshith, A. (2023). Scalable Machine Learning: Techniques for Managing Data Volume and Velocity in AI Applications. International Scientific Journal for Research, 5(5).
DEEKSHITH, A. (2018). Seeding the Future: Exploring Innovation and Absorptive Capacity in Healthcare 4.0 and HealthTech. Transactions on Latest Trends in IoT, 1(1), 90-99.
DEEKSHITH, A. (2017). Evaluating the Impact of Wearable Health Devices on Lifestyle Modifications. International Transactions in Artificial Intelligence, 1(1).
DEEKSHITH, A. (2016). Revolutionizing Business Operations with Artificial Intelligence, Machine Learning, and Cybersecurity. International Journal of Sustainable Development in computer Science Engineering, 2(2).
DEEKSHITH, A. (2015). Exploring the Foundations, Applications, and Future Prospects of Artificial Intelligence. International Journal of Sustainable Development in computer Science Engineering, 1(1).
DEEKSHITH, A. (2014). Neural Networks and Fuzzy Systems: A Synergistic Approach. Transactions on Latest Trends in Health Sector, 6(6).
Deekshith, A. (2023). Transfer Learning for Multilingual Speech Recognition in Low-Resource Languages. International Transactions in Machine Learning, 5(5).
Deekshith, A. (2021). AI-Driven Sentiment Analysis for Enhancing Customer Experience in E-Commerce. International Journal of Machine Learning for Sustainable Development, 3(2).
DEEKSHITH, A. (2019). From Clinics to Care: A Technological Odyssey in Healthcare and Medical Manufacturing. Transactions on Latest Trends in IoT, 2(2).
DEEKSHITH, A. (2018). Integrating IoT into Smart Cities: Advancing Urban Health Monitoring and Management. International Transactions in Artificial Intelligence, 2(2).
DEEKSHITH, A. (2016). Revolutionizing Business Operations with Artificial Intelligence, Machine Learning, and Cybersecurity. International Journal of Sustainable Development in computer Science Engineering, 2(2).
Boppiniti, S. T. (2020). Big Data Meets Machine Learning: Strategies for Efficient Data Processing and Analysis in Large Datasets. International Journal of Creative Research In Computer Technology and Design, 2(2).
Boppiniti, S. T. (2023). Data Ethics in AI: Addressing Challenges in Machine Learning and Data Governance for Responsible Data Science. International Scientific Journal for Research, 5(5).
BOPPINITI, S. T. (2018). Human-Centric Design for IoT-Enabled Urban Health Solutions: Beyond Data Collection. International Transactions in Artificial Intelligence, 2(2).
BOPPINITI, S. T. (2018). Unraveling the Complexities of Healthcare Data Governance: Strategies, Challenges, and Future Directions. Transactions on Latest Trends in IoT, 1(1), 73-89.
BOPPINITI, S. T. (2017). Privacy-Preserving Techniques for IoT-Enabled Urban Health Monitoring: A Comparative Analysis. International Transactions in Artificial Intelligence, 1(1).
BOPPINITI, S. T. (2016). Core Standards and Applications of Big Data Analytics. International Journal of Sustainable Development in computer Science Engineering, 2(2).
BOPPINITI, S. T. (2015). Revolutionizing Industries with Machine Learning: A Global Insight. International Journal of Sustainable Development in computer Science Engineering, 1(1).
BOPPINITI, S. T. (2014). Emerging Paradigms in Robotics: Fundamentals and Future Applications. Transactions on Latest Trends in Health Sector, 6(6).
Boppiniti, S. T. (2023). AI-Powered Disease Outbreak Prediction Using Environmental and Social Data. International Transactions in Machine Learning, 5(5).
Danda, R. R. (2024). Financial Services in the Capital Goods Sector: Analyzing Financing Solutions for Equipment Acquisition. Library Progress International, 44(3), 25066-25075.
Danda, R. R., & Dileep, V. (2024). Leveraging AI and Machine Learning for Enhanced Preventive Care and Chronic Disease Management in Health Insurance Plans. Frontiers in Health Informatics, 13(3), 6878-6891.
Danda, R. R., Nishanth, A., Yasmeen, Z., & Kumar, K. (2024). AI and Deep Learning Techniques for Health Plan Satisfaction Analysis and Utilization Patterns in Group Policies. International Journal of Medical Toxicology & Legal Medicine, 27(2).
Danda, R. R. (2024). AI and ML Applications in Supplemental Health Plans: Reducing Out-of-Pocket Costs through Predictive Insights. Journal of Material Sciences & Manufacturing Research. SRC/JMSMR-227. DOI: doi. org/10.47363/JMSMR/2024 (5), 189, 1-7.
Danda, R. R. (2024). Generative AI in Designing Family Health Plans: Balancing Personalized Coverage and Affordability. Utilitas Mathematica, 121, 316-332.
Reddy, R. (2024). Generative AI for Enhanced Engagement in Digital Wellness Programs: A Predictive Approach to Health Outcomes. Available at SSRN 5022990.
Danda, R. R. (2022). Innovations in Agricultural Machinery: Assessing the Impact of Advanced Technologies on Farm Efficiency. Journal of Artificial Intelligence and Big Data, 2(1), 64-83.
Reddy, R. (2020). Predictive Modeling with AI and ML for Small Business Health Plans: Improving Employee Health Outcomes and Reducing Costs. Available at SSRN 5018069.
Reddy, R. (2022). Telehealth In Medicare Plans: Leveraging AI For Improved Accessibility And Senior Care Quality. Available at SSRN 5032655.
Danda, R. R., Yasmeen, Z., & Maguluri, K. K. AI-Driven Healthcare Transformation: Machine Learning, Deep Learning, and Neural Networks in Insurance and Wellness Programs. JEC PUBLICATION.
Reddy, R. (2022). Application of Neural Networks in Optimizing Health Outcomes in Medicare Advantage and Supplement Plans. Available at SSRN 5031287.
Danda, R. R. (2022). Deep Learning Approaches For Cost-Benefit Analysis Of Vision And Dental Coverage In Comprehensive Health Plans. Migration Letters, 19(6), 1103-1118.
Krutthika, H., & Rajashekara, K. (2019). Network on chip: A survey on router design and algorithms. Int. J. Recent Technol. Eng., 7(6), 1687-1691.
Krutthika, H. K. (2019, October). Modeling of Data Delivery Modes of Next Generation SOC-NOC Router. In 2019 Global Conference for Advancement in Technology (GCAT) (pp. 1-6). IEEE.
Pavitha, U. S., Nikhila, S., & Krutthika, H. K. (2012). Design and implementation of image dithering engine on a spartan 3AN FPGA. International Journal of Future Computer and Communication, 1(4), 361.
Nikhila, S., Pavitha, U. S., & Krutthika, H. K. (2014). Face recognition using wavelet transforms. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 3(1), 6740-6746.
Krishnappa, K. H., & Gowda, N. V. N. (2023, August). Dictionary-Based PLS Approach to Pharmacokinetic Mapping in DCE-MRI Using Tofts Model. In International Conference on ICT for Sustainable Development (pp. 219-226). Singapore: Springer Nature Singapore.
Shashidhar, R., Balivada, D., Shalini, D. N., Krishnappa, K. H., & Roopa, M. (2023, November). Music Emotion Recognition using Convolutional Neural Networks for Regional Languages. In 2023 International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE) (pp. 1-7). IEEE.
Nair, T. R., & Krutthika, H. K. (2010). An Architectural Approach for Decoding and Distributing Functions in FPUs in a Functional Processor System. arXiv preprint arXiv:1001.3781.
Shashidhar, R., Aprameya, C. V., Bharadwaj, R. R., Gontamar, S. M., & Krishnappa, K. H. (2023, November). Seismic Signal Processing and Aftershock Analysis using Machine Learning. In 2023 International Conference on Recent Advances in Science and Engineering Technology (ICRASET) (pp. 1-9). IEEE.
Krishnappa, K. H., Shashidhar, R., Shashank, M. P., & Roopa, M. (2023, November). Detecting Parkinson's Disease with Prediction: A Novel SVM Approach. In 2023 International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics (AIKIIE) (pp. 1-7). IEEE.
Shashidhar, R., Kadakol, P., Sreeniketh, D., Patil, P., Krishnappa, K. H., & Madhura, R. (2023, November). EEG Data Analysis for Stress Detection using K-Nearest Neighbor. In 2023 International Conference on Integrated Intelligence and Communication Systems (ICIICS) (pp. 1-7). IEEE.
Ajay, S., Satya Sai Krishna Mohan G, Rao, S. S., Shaunak, S. B., Krutthika, H. K., Ananda, Y. R., & Jose, J. (2018). Source Hotspot Management in a Mesh Network on Chip. In VDAT (pp. 619-630).
Patra, G. K., Kuraku, C., Konkimalla, S., Boddapati, V. N., Sarisa, M., & Reddy, M. S. (2024). An Analysis and Prediction of Health Insurance Costs Using Machine Learning-Based Regressor Techniques. Journal of Data Analysis and Information Processing, 12(4), 581-596.
Boddapati, V. N., Sarisa, M., Reddy, M. S., Sunkara, J. R., Rajaram, S. K., Bauskar, S. R., & Polimetla, K. (2022). Data migration in the cloud database: A review of vendor solutions and challenges. Available at SSRN 4977121.
Sarisa, M., Patra, G. K., Kuraku, C., Konkimalla, S., & Boddapati, V. N. (2024). Stock Market Prediction Through AI: Analyzing Market Trends With Big Data Integration. Manikanth Sarisa, Gagan Kumar Patra, Chandrababu Kuraku, Siddharth Konkimalla, Venkata Nagesh Boddapati.(2024). Stock Market Prediction Through AI: Analyzing Market Trends With Big Data Integration. Migration Letters, 21(4), 1846-1859.
Sarisa, M., Boddapati, V. N., Patra, G. K., Kuraku, C., & Konkimalla, S. (2022). Deep Learning Approaches To Image Classification: Exploring The Future Of Visual Data Analysis. Educational Administration: Theory and Practice, 28(4), 331-345.
Patra, G. K., Rajaram, S. K., Boddapati, V. N., Kuraku, C., & Gollangi, H. K. (2022). Advancing Digital Payment Systems: Combining AI, Big Data, and Biometric Authentication for Enhanced Security. International Journal of Engineering and Computer Science, 11(08), 10-18535.
Sarisa, M., Boddapati, V. N., Patra, G. K., Kuraku, C., Konkimalla, S., & Rajaram, S. K. (2020). An Effective Predicting E-Commerce Sales & Management System Based on Machine Learning Methods. Journal of Artificial Intelligence and Big Data, 1(1), 75-85.
Kuraku, C., Rajaram, S. K., Gollangi, H. K., Boddapati, V. N., & Patra, G. K. (2024). Advanced Encryption Techniques in Biometric Payment Systems: A Big Data and AI Perspective. Library Progress International, 44(3), 2447-2458.
Patra, G. K., Kuraku, C., Konkimalla, S., Boddapati, V. N., & Sarisa, M. (2023). Sentiment Analysis of Customer Product Review Based on Machine Learning Techniques in E-Commerce. Journal of Artificial Intelligence & Cloud Computing. SRC/JAICC-408. DOI: doi. org/10.47363/JAICC/2023 (2), 389(1), 7211-7224.
Sarisa, M., Boddapati, V. N., Patra, G. K., Kuraku, C., Konkimalla, S., & Rajaram, S. K. (2020). Navigating the Complexities of Cyber Threats, Sentiment, and Health with AI/ML. JOURNAL OF RECENT TRENDS IN COMPUTER SCIENCE AND ENGINEERING (JRTCSE), 8(2), 22-40.
Sarisa, M., Boddapati, V. N., Patra, G. K., Kuraku, C., Konkimalla, S., & Rajaram, S. K. The power of sentiment: big data analytics meets machine learning for emotional insights. International Journal of Development Research, 10(10), 41565-41573.
Boddapati, V. N., Sarisa, M., Reddy, M. S., Sunkara, J. R., Rajaram, S. K., Bauskar, S. R., & Polimetla, K. (2022). Data migration in the cloud database: A review of vendor solutions and challenges. Available at SSRN 4977121.
Patra, G. K., Kuraku, C., Konkimalla, S., Boddapati, V. N., Sarisa, M., & Reddy, M. S. (2024). An Analysis and Prediction of Health Insurance Costs Using Machine Learning-Based Regressor Techniques. Journal of Data Analysis and Information Processing, 12(4), 581-596.
Gollangi, H. K., Bauskar, S. R., Madhavaram, C. R., Galla, E. P., Sunkara, J. R., & Reddy, M. S. (2020). Echoes in Pixels: The intersection of Image Processing and Sound detection through the lens of AI and Ml. International Journal of Development Research, 10(08), 39735-39743.
Reddy, M. S., Sarisa, M., Konkimalla, S., Bauskar, S. R., Gollangi, H. K., Galla, E. P., & Rajaram, S. K. (2021). Predicting tomorrow’s Ailments: How AI/ML Is Transforming Disease Forecasting. ESP Journal of Engineering & Technology Advancements, 1(2), 188-200.
Patra, G. K., Kuraku, C., Konkimalla, S., Boddapati, V. N., & Sarisa, M. (2023). Sentiment Analysis of Customer Product Review Based on Machine Learning Techniques in E-Commerce. Journal of Artificial Intelligence & Cloud Computing. SRC/JAICC-408. DOI: doi. org/10.47363/JAICC/2023 (2), 389(1), 7211-7224.
Rajaram, S. K., Konkimalla, S., Sarisa, M., Gollangi, H. K., Madhavaram, C. R., & Reddy, M. S. (2023). AI/ML-Powered Phishing Detection: Building an Impenetrable Email Security System. ISAR Journal of Science and Technology, 1(2), 10-19.
Gollangi, H. K., Bauskar, S. R., Madhavaram, C. R., Galla, E. P., Sunkara, J. R., & Reddy, M. S. (2020). Unveiling the Hidden Patterns: AI-Driven Innovations in Image Processing and Acoustic Signal Detection. JOURNAL OF RECENT TRENDS IN COMPUTER SCIENCE AND ENGINEERING (JRTCSE), 8(1), 25-45.
Gollangi, H. K., Bauskar, S. R., Madhavaram, C. R., Galla, E. P., Sunkara, J. R., & Reddy, M. S. (2020). Exploring AI Algorithms for Cancer Classification and Prediction Using Electronic Health Records. Journal of Artificial Intelligence and Big Data, 1(1), 65-74.
Mahida, A., Mandala, V., Bauskar, S. R., Konkimalla, S., & Reddy, M. S. (2024). Real-Time Fraud Mitigation in Digital Payments: Big Data and AI-Driven Biometric Authentication. Nanotechnology Perceptions, 1176-183.
Sunkara, J. R., Bauskar, S. R., Madhavaram, C. R., Galla, E. P., & Gollangi, H. K. (2023). An Evaluation of Medical Image Analysis Using Image Segmentation and Deep Learning Techniques. Journal of Artificial Intelligence & Cloud Computing. SRC/JAICC-407. DOI: doi. org/10.47363/JAICC/2023 (2), 388, 2-8.
Adusumilli, S., Damancharla, H., & Metta, A. (2021). Deep Learning Techniques for Image Recognition in Autonomous Vehicles. (2021). International Meridian Journal, 3(3). https://meridianjournal.in/index.php/IMJ/article/view/94
Adusumilli, S., Damancharla, H., & Metta, A. (2021). Integrating Machine Learning and Blockchain for Decentralized Identity Management Systems. (2021). International Journal of Machine Learning and Artificial Intelligence, 2(2). https://jmlai.in/index.php/ijmlai/article/view/46
Adusumilli, S., Damancharla, H., & Metta, A. (2022). Blockchain-Based Secure Framework for IoT Data Management. International Journal of Sustainable Development in Computing Science, 4(1). Retrieved from https://www.ijsdcs.com/index.php/ijsdcs/article/view/640
Adusumilli, S., Damancharla, H., & Metta, A. (2022). Optimizing Supply Chain Efficiency Through Blockchain and Smart Contracts. (2022). International Numeric Journal of Machine Learning and Robots, 6(6). https://injmr.com/index.php/fewfewf/article/view/183
Adusumilli, S., Damancharla, H., & Metta, A. (2023). Enhancing Data Privacy in Healthcare Systems Using Blockchain Technology. Transactions on Latest Trends in Artificial Intelligence, 4(4). Retrieved from https://www.ijsdcs.com/index.php/TLAI/article/view/637
Dhaiya, S., Pandey, B. K., Adusumilli, S. B. K., & Avacharmal, R. (2021). Optimizing API Security in FinTech Through Genetic Algorithm based Machine Learning Model.
Manoharan, G., Mishra, A. B., Adusumilli, S. B. K., Chavva, M., Damancharla, H., & Lenin, D. S. (2024, May). Supervised Learning for Personalized Marketing Strategies. In 2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (pp. 1-6). IEEE.
Adusumilli, S. B. K. (2024). SCALABLE SOFTWARE ARCHITECTURE FOR DYNAMIC THREAT DETECTION AND MITIGATION IN IOT. Machine Intelligence Research, 18(1), 468-481.
Adusumilli, S. B. K. (2023). TOWARDS ENERGY-EFFICIENT AIML INFERENCE ON EDGE DEVICES SOFTWARE SOLUTIONS AND CHALLENGES. Journal of Engineering Sciences, 14(11).
Adusumilli, S. B. K. Mitigating Cybersecurity Risks in Embedded Systems A Software-First Approach.
Sarkar, R., Malini, T. N., Adusumilli, S. B. K., Jena, M. S., & Patra, J. P. AI-INFUSED BLOCKCHAIN INNOVATIONS IN MANUFACTURING SUPPLY CHAINS FOR ECO-FRIENDLY PRACTICES TOWARDS A SUSTAINABLE FUTURE.
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