Keynotes ETLTC & ICETM 2027

Ravi Teja Reddy Mandala 

Senior Site Reliability Engineer, Oracle Cloud Infrastructure

IEEE Senior Member | ACM Member, 

Cloud Reliability, AI Systems, and Large-Scale Infrastructure Engineering, USA

LinkedIn: https://www.linkedin.com/in/ravi-teja-reddy-mandala/

Trustworthy AI Systems at Scale: Governance, Decision Intelligence, and Reliable Cloud Infrastructure 

Abstract: Artificial intelligence is rapidly moving from experimental pilots to real-world decision-making systems across education, healthcare, finance, public services, and enterprise operations. As adoption increases, the central question is no longer only how powerful AI can become but how trustworthy, governable, reliable, and human-aligned these systems can be when deployed at scale. This keynote will discuss the practical foundations for building trustworthy AI systems, focusing on responsible AI adoption, governance frameworks, decision accountability, and the critical role of reliable cloud infrastructure. 

The session will examine how organizations can move beyond model accuracy and evaluate AI systems through broader dimensions such as transparency, fairness, privacy, explainability, security, resilience, observability, and operational reliability. It will also highlight the importance of human-in-the-loop decision-making, auditability, risk controls, and policy alignment in ensuring that AI supports rather than replaces responsible judgment. We'll pay special attention to the infrastructure layer, including scalable cloud platforms, monitoring, incident response, deployment governance, and reliability engineering practices that enable AI applications to operate safely in production environments. 

Drawing from industry experience in cloud infrastructure, site reliability engineering, AI-enabled systems, and large-scale operational governance, the keynote will provide a practical roadmap for institutions and enterprises seeking to adopt AI responsibly. The talk will also connect technical reliability with institutional trust by showing how governance policies, engineering controls, and continuous monitoring must work together. The talk will conclude with future directions for trustworthy AI, including AI governance maturity, continuous validation, ethical automation, and the need for collaboration among educators, researchers, engineers, policymakers, and industry leaders.

Prof. Dr. Evgeny Pyshkin 

Professor, Department of Computer Science & Engineering, 

University of Aizu, Japan 

Between the passion for the arts and the pragmatism of computing: Enhancing the agenda of contemporary computer science and software engineering education with art studies

Abstract—Embracing uncertainty, abolishing the fear of not knowing, and acknowledging gaps in knowledge are key aspects of the contemporary educational paradigm that shifts the primary purpose of education from knowledge transfer to knowledge discovery, favoring the exploration of the unknown through a mutually immersive learning process involving both tutors and students. The arts transform technocratic societies by promoting humanized technologies, emphasizing both the importance of computer education for non-engineers and the necessity of arts literacy for IT professionals. Standard computer technology curricula are strongly focused on professional pragmatism and prioritize the development of professional skills over serving students’ needs across all aspects of their lives. Few courses introduce the arts to students, although developing students' appreciation for art would significantly extend their creative and critical thinking horizons. This talk is an effort to share an experience of introducing arts in the scope of traditional ICT classes offered to computer- and AI-literate students, where the essential topics from the domains of data management, programming, information retrieval, linguistics, and natural language processing are illustrated with the help of art metaphors and masterpieces of art; thus, as we hope, provoking the further interest and more active engagement of our students in understanding the serious arts, the latter including both traditional and, paradoxically, those appealing to the contemporary vision and involving generative AI.

Prof. Dr. Wolfgang Ziegler 

Professor,  Department of Information Management & Media, 

Karlsruhe University of Applied Sciences, Germany

AI-Powered Analytics in Technical Communication: Advancing Information Management toward Content Data Science

Abstract - Technical Communication (TC), as an interdisciplinary field within information management, is shaped by applied linguistics, computer science, and user-centered media design. Its primary goal is to create, manage, and deliver concise information tailored to the needs of its recipients. In modern settings, this is typically supported by topic-based content enriched with semantic metadata, such as PI classifications. 

So far, analytics in TC has received limited academic attention and has been applied in industry mainly through a few specialized tools. These tools focus on metrics and KPIs, such as linguistic content quality parameters or content reuse performance within content management processes. On the delivery side, user experience has been explored mainly through usability studies and web analytics of user behavior, often with an emphasis on sales-oriented contexts. 

In our recent approach, we aim to expand analytics in TC by leveraging AI—particularly language models—within an interactive environment called the PIAI-Lab. In collaborative business–academic projects, our goal is to provide easier access to analytical insights derived from content ensembles originating in content management systems (CMS) and used in various delivery scenarios. More broadly, our research focuses on three use cases: Content engineering in the pre-CMS phase, Content analytics within content management processes, and KPIs for content delivery in AI-driven environments such as chat systems and retrieval-augmented generation (RAG). 

We present typical approaches for these use cases in academic studies and derive characteristic properties of topic ensembles explored within the PIAI-Lab.

Mr. Rahul Autade

Sr. Manager – Payments Implementation, 3Itek

Pittsburgh, Pennsylvania, USA

Transforming Financial Services through AI and Blockchain: A Roadmap for Smart, Inclusive Payment Systems

Abstract - As financial services evolve to meet the demands of a hyper-digital and inclusive economy, the integration of emerging technologies such as artificial intelligence and blockchain is becoming foundational. This talk explores how these technologies are being deployed to build smarter, more secure, and highly scalable payment systems. Drawing from over two decades of experience in fintech and digital infrastructure implementation across major U.S. banks, I will present real-world use cases highlighting intelligent fraud detection, blockchain-based settlements, and AI-driven customer personalization. The session will also explore the challenges and opportunities of deploying such technologies in emerging markets and smart environments. Attendees will gain a practical understanding of how to architect ethical, efficient, and resilient financial platforms that not only improve user experience but also advance financial inclusion and regulatory transparency.

Prof. Dr. Peter Ilic

Center for Language Research, School of Computer Science and Engineering, 

The University of Aizu, Japan

Dialogic Education and Artificial Intelligence: Exploring Synergies in Learning 

Abstract - This keynote examines synergies between dialogic education and artificial intelligence in education amid advancements in large language models that reshape learning paradigms. The address covers three areas: how artificial intelligence facilitates dialogic interactions by simulating conversational partners and supporting shared meaning construction; how artificial intelligence expands dialogic spaces through access to diverse perspectives and global connections; and how artificial intelligence fosters creativity, empathy, and ongoing inquiry while requiring attention to risks such as limited viewpoint diversity. Where relevant, aspects related to language learning will be discussed to illustrate these correlations, including how artificial intelligence enables immersive conversational practice that promotes reciprocity and perspective switching, and how it supports engagement with cultural and linguistic diversity in ways that align with dialogic principles. 

The presentation aims to prompt attendees to explore correlations between dialogic principles and artificial intelligence tools, reconsider teaching approaches in technology-mediated environments, and stimulate broader discussion on emerging learning paradigms. It offers conceptual frameworks for human artificial intelligence collaborative dialogues while encouraging reflection through a forward-looking perspective. 

The address highlights the value of continued exploration of these synergies to shape the future of education and urges commitment to educational excellence and impact.