Academic Background:
Ph.D. in Decision Support Systems and Applied Machine Learning
MBA (Quantitative Finance)
Bachelor of Technology (Electronics and Communications Engineering)
Research & Work Experience:
20+ years of experience designing, developing, and implementing advanced embedded systems, railway product engineering solutions, and intelligent automation across safety-critical industrial domains, with a parallel track of expertise in financial engineering.
Specialized in Decision Support Systems, applying AI/ML, IoT, and advanced engineering principles to both industrial systems and financial decision-making.
Developed solutions in Rail systems, predictive maintenance, and AI/ML-enabled industrial IoT — as well as predictive analytics, financial modeling, and AI-driven investment decision tools.
Principal Architect for technology solutions that leverage AI, IoT, and predictive modeling to drive innovation in railway and industrial systems, while applying the same rigor to create cutting-edge financial market decision platforms.
Presented and published high-quality papers in international journals and conferences on topics such as Decision Support Systems, AI in engineering, and Financial Analytics.
Research Interests:
Safety Critical Embedded Systems
Rail Signaling and Train Control Systems
Financial Decision Support Systems
Predictive Analytics for Financial Markets
Application of AI/ML in Financial Modelling
Quantitative Finance and Algorithmic Trading
AI/ML for Risk Management and Portfolio Optimization
International Journals:
Patalay, S., & Bandlamudi, M. R. (2021). Decision Support System for Stock Portfolio Selection Using Artificial Intelligence and Machine Learning. Ingénierie Des Systèmes d’Information, 26(1), 87–93. https://doi.org/https://doi.org/10.18280/isi.260109
Patalay, S., & Bandlamudi, M. R. (2020). Stock price prediction and portfolio selection using artificial intelligence. Asia Pacific Journal of Information Systems, 30(1), 31–52. https://doi.org/10.14329/apjis.2020.30.1.31
Patalay, S., & Bandlamudi, M. R. (2019). Design of a Financial Decision Support System based on Artificial Neural Networks for Stock Price Prediction. Journal of Mechanics of Continua and Mathematical Sciences, 14(5), 757–766. https://doi.org/10.26782/jmcms.2019.10.00060
Patalay, S., & Bandlamudi, M. R. (2018). Artificial Intelligence Based System for Financial Decision Support. Journal of Emerging Technologies and Innovative Research (JETIR), 5(9), 80–87. https://doi.org/10.6084/m9.jetir.JETIRA006335
International Conferences:
Patalay, S. (2021). Predicting Bull and Bear Phases of Stock Markets Using Machine Learning Classification Techniques. In 8th International Conference on Business Analytics and Intelligence (ICBAI), 2021. IISC Bangalore
Patalay, S., & Bandlamudi, M. R. (2021). Gold Price Prediction Using Machine Learning Model Trees. In International Conference on Changing Business Paradigm, (ICCBP) 2021, MDI Murshidabad (pp. 1–12).
Patalay, S., & Bandlamudi, M. R. (2019). Stock Price Prediction and Portfolio Selection Using Artificial Intelligence. In 2nd International Conference on Digital Economy, IIM Raipur, India 2019 (ICDE-2019). Raipur.
Patalay, S., & Bandlamudi, M. R. (2019). Design of a Financial Decision Support System based on Artificial Neural Networks for Stock Price Prediction. In National Conference on Management Perspectives 2019, Vignan’s University. Guntur
Patalay, S., & Bandlamudi, M. R. (2018). Design of a Decision Support System for Stock Price Prediction Using Artificial Neural Networks. In 6th International Conference on Business Analytics and Intelligence 2018 (ICBAI-2018), IISC Bangalore (pp. 756–763). Bangalore.
Patalay, S., & Bandlamudi, M. R. (2018). Artificial Intelligence Based System for Financial Decision Support. In 2nd International Conference on Research Trends in Engineering, Applied Science and Management (ICRTESM-2018), Osmania University (pp. 13–20). Hyderabad