Subramanya Bharathvamsi Koneti’s new open-access volume on AI-powered finance arrives alongside a string of 2025 IEEE papers spanning agriculture, satellite networks, and cybersecurity.
ILLINOIS — Subramanya Bharathvamsi Koneti, a software developer at Globalsoft Consultants and a researcher affiliated with Governors State University, has published a wide-ranging new book on artificial intelligence in finance — the latest in an unusually broad body of 2025 work that also reaches into precision agriculture, satellite communications, network optimization, and cybersecurity.
The book, Artificial Intelligence-Powered Finance: Algorithms, Analytics, and Automation for the Next Financial Revolution, was released in 2025 by Deep Science Publishing. It is available under a fully open-access license, meaning anyone can read and redistribute it with attribution.
A practitioner’s map of AI in finance
Organized into ten chapters, the book traces how machine learning, natural language processing, reinforcement learning, and generative models are reshaping banking, insurance, wealth management, and regulatory compliance. It opens with the digital transformation of financial systems and moves through algorithmic and high-frequency trading, credit scoring and probability-of-default modeling, and AI-driven fraud detection and behavioral biometrics.
Later chapters turn to retail and investment banking, robo-advisory and behavioral analytics, financial forecasting and macroeconomic simulation, and the fast-moving fintech startup ecosystem. The closing chapters take up the harder questions: governance, fairness, explainability, and bias mitigation, before ending on the practical plumbing of deployment, including MLOps and cloud architectures.
According to its preface, the volume is pitched at both professionals and students, and leans on real-world use cases, code examples, and architectural blueprints to connect theory with implementation rather than dwelling on concepts alone.
A year of papers across very different fields
The book lands in the middle of a busy year. Across 2025, Koneti appears as author or co-author on a series of IEEE conference papers whose subjects have little in common on the surface but share a recurring thread: applying modern AI methods to hard, real-world problems.
The 2025 IEEE conference record includes:
- AI-Driven Optimization Frameworks for Next-Generation Satellite Communication Systems, presented at the 6th International Conference on Smart Electronics and Communication (ICOSEC), with co-authors Mohanraju Muppala and Shashipurna Kurapati.
- A Hybrid Graph Neural Network and Deep Reinforcement Learning Framework for Adaptive Network Optimization, also at ICOSEC, co-authored with Shashipurna Kurapati and Mohanraju Muppala.
- Weed and Crop Detection Using YOLOv7: A Step Toward Smarter Precision Agriculture, a single-author paper at the iTech SECOM conference, applying real-time computer vision to distinguish crops from weeds in the field.
- Fostering Entrepreneurial Growth: A Study of Critical Management Capabilities, presented at the 4th International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), with co-author Mohanraju Muppala.
- Decentralized Malware Propagation: A Proof-of-Concept Study on Self-Spreading Botnets, a single-author security paper at the 3rd International Conference on Sustainable Computing and Smart Systems (ICSCSS), examining how threats move through decentralized systems.
Beyond the conference circuit, his recent writing has also touched on explainable AI in healthcare and the role of AI in climate modeling and sustainable decision-making, and his name appears among contributors to a public image dataset built to tackle weed problems in potato crops. Alongside authoring and co-authoring, he has also served as a technical reviewer for academic work in the field.
One thread through the breadth
Taken together, the output sketches a researcher less defined by a single subject than by a method. Whether the setting is a trading desk, a wheat field, a satellite link, or a compromised network, the underlying question tends to be the same: how to make a system act well under uncertainty when the stakes are real. The new finance book is, in that sense, the most fully developed statement so far of an approach Koneti has been applying field by field throughout the year.
Artificial Intelligence-Powered Finance is available online through Deep Science Publishing (ISBN 978-93-7185-281-4; e-ISBN 978-93-7185-613-3). The IEEE papers are indexed in IEEE Xplore.
