Mr. Mohammed Shaik
Assistant Professor, Department of Management Studies
Profile
Mr. Mohammed Shaik
Assistant Professor, Department of Management Studies
Mr. Mohammed Shaik works at the intersection of AI/ML and management. His research focuses on churn prediction, credit card fraud detection, sentiment analysis of quick-commerce platforms, NLP, and AI solutions for MSMEs. He holds a B.Tech and an MBA, and has submitted his PhD in machine-learning–driven business research. He actively publishes in IEEE Conferences, Scopus, and ABDC outlets. His work is strongly application-oriented, emphasizing Indian contexts where AI and ML address operational, business, and institutional challenges. He is skilled in applying AI/ML to business problems, teaching advanced data analytics, and integrating tools such as Power BI, RPA, and Python into management education. He is passionate about mentoring future business leaders through a blend of academic rigor and industry relevance.
Area
Business Analytics, AI, ML
Qualification
B.Tech, MBA (PhD)
Experience
8 years
Publications
- Sucharitha, M. M., Kumar, J. P. S., Sateesha, G., Prasad, M. V. R., & Basha, M. S. A. (2025). A SHAP-enhanced PCA–DBSCAN framework for interpretable retail customer segmentation and strategic insight. International Journal of System Assurance Engineering and Management. Advance online publication.
- Basha, M. S. A., & Oveis, P. M. (2024). Predictive modeling and benchmarking for diamond price estimation: Integrating classification, regression, hyperparameter tuning and execution time analysis. International Journal of System Assurance Engineering and Management, 15(11), 5279–5313.
- Basha, M. S. A. ., & Oveis, P. M. . (2023). Harnessing Data-Driven Insights: Predictive Modeling for Diamond Price Forecasting using Regression and Classification Techniques. International Journal on Recent and Innovation Trends in Computing and Communication, 11(9), 290–301. https://doi.org/10.17762/ijritcc.v11i9.8355
- A Study on impact of stress on employee’s productivity and job performance: implications for stress measurement and management”, Ilkogretim Online – Elementary Education Online, 2020; 19 (4): pp. 823-831
Academic Conferences
- Enhancing Customer Personality Prediction using Advanced Machine Learning Techniques and Data Balancing Strategies: A Comprehensive Approach to Addressing Imbalanced Datasets in Marketing Analytics — International Conference on Intelligent Systems and Computational Networks (ICISCN 2025), 2025.
- The Role of Machine Learning in Shaping Virtual Reality Educational Experiences: A Multi-Model Analysis — 4th IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE 2025), 2025.
- Data-Driven Insights into Student Performance: Benchmarking Machine Learning Models for Grade Prediction using Regression and Classification Approaches — International Conference on Intelligent Systems and Computational Networks (ICISCN 2025), 2025.
- Development and Deployment of an IoT-Enabled Water Quality Monitoring System — 4th Wireless Antenna and Microwave Symposium (WAMS 2025), 2025.
- Deploying a Multi-Model Forecasting System for Bitcoin Prices: Bridging Statistical Forecasting and Deep Learning Innovations — 3rd International Conference on Data Science and Information System (ICDSIS 2025), 2025.
- User Behavior Prediction with Deep Learning: An Evaluation of CNN, LSTM, RNN, and Hybrid Models — 3rd International Conference on Integrated Circuits and Communication Systems (ICICACS 2025), 2025.
- Credit Card Fraud Detection with ADASYN Oversampling and SHAP-based Interpretability: A Comparative Ensemble Approach — 6th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV 2025), 2025.
- Obesity Health Risk Prediction using Random Forest and SVM Algorithms — 8th International Conference on Trends in Electronics and Informatics (ICOEI 2025), 2025.
- Machine Learning in HR Analytics: A Comparative Study on the Predictive Accuracy of Attrition Models — 2nd IEEE International Conference on Device Intelligence, Computing and Communication Technologies (DICCT 2024), 2024.
- Evaluating Sparkle and Beyond the Four Cs: Unveiling a New Frontier in Diamond Valuation with Advanced Machine Learning Algorithms — 2024 International Conference on Artificial Intelligence and Emerging Technology (Global AI Summit 2024), 2024.
- Machine Learning Insights into Mobile Phone Usage and Its Effects on Student Health and Academic Achievement — 3rd International Conference for Advancement in Technology (ICoNAT 2024), 2024.
- Gems of Prediction: From Clarity to Carats – Unveiling Diamond Prices with Machine Learning in Waikato Environment for Knowledge Analysis — International Conference on Distributed Computing and Optimization Techniques (ICDCOT 2024), 2024.
- Unveiling the Future: Exploring Stock Price Prediction in the Finance Sector through Machine Learning and Deep Learning – A Comprehensive Bibliometric Analysis — International Conference on Smart Systems for Applications in Electrical Sciences (ICSSES 2024), 2024.
- Towards an Improved Model for Stability Score Prediction: Harnessing Machine Learning in National Stability Forecasting — NKCON 2024: 3rd Edition of IEEE NKSS Flagship International Conference “Digital Transformation: Unleashing the Power of Information”, 2024.
- Quantifying the Impact and Growth of Smart Innovation, Systems and Technology: A Bibliometric Approach Mapping the Research Landscape Over 12 Years — Smart Innovation, Systems and Technologies (Scopus indexed conference series), 2024.
- Assessing Machine Learning Models for Predictive Analytics in Urban Rental Markets: Rent Price Forecasting in India — 2nd IEEE International Conference on Integrated Intelligence and Communication Systems (ICIICS 2024), 2024.
- Green Pioneers in the Maze of Sustainability: Machine Learning Insights into the Drivers of Eco-Entrepreneurship — International Conference on Distributed Computing and Optimization Techniques (ICDCOT 2024), 2024.
- Predictive Modeling of Solar Energy Production: A Comparative Analysis of Machine Learning and Time Series Approaches — IEEE International Conference for Women in Innovation, Technology and Entrepreneurship (ICWITE 2024), 2024.
- Leveraging Ensemble Methods for Accurate Prediction of Customer Spending Scores in Retail — 3rd International Conference for Advancement in Technology (ICoNAT 2024), 2024.
- Comparative Analysis of Machine Learning Models in Predicting Academic Outcomes: Insights and Implications for Educational Data Analytics — International Conference on Smart Systems for Applications in Electrical Sciences (ICSSES 2024), 2024.
Advancing Predictive Analytics in E-Learning Platform: The Dominance of Blended Models in Enrollment Forecasts — 2nd World Conference on Communication and Computing (WCONF 2024), 2024.
- Predicting Player Engagement in Online Gaming: A Machine Learning Approach — NKCON 2024: 3rd Edition of IEEE NKSS Flagship International Conference, 2024.
- Harnessing Machine Learning for Mental Health: A Study on Classifying Depression-Related Social Media Posts — NKCON 2024: 3rd Edition of IEEE NKSS Flagship International Conference, 2024.
- Artificial Intelligence in Fostering Sustainable Development — AIP Conference Proceedings, 2023.
- Artificial Intelligence Revolution in Supply Chain Management — AIP Conference Proceedings, 2023.
- Leveraging Robotic Process Automation (RPA) in Business Operations and its Future Perspective — AIP Conference Proceedings, 2023.
- Non-Fungible Token (NFT): Bubble or Future in the World of Block Chain Technology — AIP Conference Proceedings, 2023.
- Artificial Intelligence & Automation: Opportunities and Challenges — AIP Conference Proceedings, 2023.
- Can Artificial Intelligence Accelerate and Improve New Product Development — AIP Conference Proceedings, 2023.
- Talent Retention, Job Involvement Satisfaction, and Commitment Towards the Organization in the IT Sector — AIP Conference Proceedings, 2023.
- A LSTM-Based Model for Stock Price Analysis and Prediction — AIP Conference Proceedings, 2023.
- Unraveling Campus Placement Success: Integrating Exploratory Insights with Predictive Machine Learning Models — 7th IEEE International Conference on Computational Systems and Information Technology for Sustainable Solutions (CSITSS 2023), 2023.
- An Efficient Machine Learning Approach: Analysis of Supervised Machine Learning Methods to Forecast the Diamond Price — International Conference for Advancement in Technology (ICoNAT 2023), 2023.
- Predicting Graduate Admissions using Ensemble Machine Learning Techniques: A Comparative Study of Classifiers and Regressors — 2nd International Conference for Innovation in Technology (INOCON 2023), 2023.
- Mapping the Landscape of Business Intelligence Research: A Bibliometric Approach — 7th IEEE International Conference on Computational Systems and Information Technology for Sustainable Solutions (CSITSS 2023), 2023.
- Forecasting the Academic Horizon: Machine Learning Models Unraveling the Complex Web of Student Well-being Determinants — NKCON 2023: 2nd IEEE North Karnataka Subsection Flagship International Conference, 2023.
- Are Women Employees in Engineering Institutions Suffer from the Stress: An Investigation Approach — International Conference for Advancement in Technology (ICoNAT 2023), 2023.
- Exploring Machine Learning Models to Predict the Diamond Price: A Data Mining Utility Using WEKA — 9th International Conference on Advanced Computing and Communication Systems (ICACCS 2023), 2023.
- Enhancing Red Wine Quality Prediction through Machine Learning Approaches with Hyperparameters Optimization Technique — 2nd International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT 2023), 2023.
- A Data Mining Approach on the Performance of Machine Learning Methods for Share Price Forecasting using the WEKA Environment — 5th International Conference on Electrical, Computer and Communication Technologies (ICECCT 2023), 2023.
- Leveraging and Deployment of AI/ML to Simplify Business Operations among Diverse Sectors during Covid-19 Battle — AIP Conference Proceedings, 2022.
- The Impact of Covid-19 on Global Upstream and Downstream Supply Chain Management Activities — AIP Conference Proceedings, 2022.
- Implementation of Time-Series Analysis: Prediction of Stock Prices using Machine Learning and Deep Learning Models: A Hybrid Approach — IEEE North Karnataka Subsection Flagship International Conference (NKCON 2022), 2022.
- A Study on Student Cyber Safety Consciousness in the Light of Online Learning — INDICON 2022: IEEE 19th India Council International Conference, 2022.
- Prediction of Stock Prices using Prophet Model with Hyperparameters Tuning — IEEE North Karnataka Subsection Flagship International Conference (NKCON 2022), 2022.
FDP
ATAL AICTE Training and Learning (ATAL) Academy
- Faculty Development Program on Leadership and Excellence by “JNTUA – Anantapuram” from Feb 1st – Feb 5th 2021
- Faculty Development Program on Artificial Intelligence by “Aditya Institute of Management – Bangalore” from Jan 1st – Jan 5th 2021
- Faculty Development Program on Design Thinking by “AMITY UNIVERSITY – UP” from Dec 21st – Dec 25th 2020
- Faculty Development Program on Technology Management by “Acharya Bangalore Business School – ABBS” from Dec 14th – Dec 18th 2020
AICTE Sponsored Short Term Training Program
- “Role of Artificial Intelligence in Engineering Applications” from 02nd Nov 2020 to 07th Nov 2020 (Series-2). Organized by Sanskrithi School of Engineering, Puttaparthi, Anantapur (DT).
- “Role of Artificial Intelligence in Engineering Applications” from 23rd Nov 2020 to 28th Nov 2020 (Series-3).
Two Week Sponsored FDPs
- DST Sponsored Two Weeks Online (12 Days) Faculty Development Program on Entrepreneurship organized by Gates Institute of Technology from March 15th – 27th 2021
Workshops
Participated in hands-on workshop Organized by IIT, Bombay in June 2020.
Professional Affiliation
- IEEE Member
