Special Session Theme: Artificial Intelligence in Software Reliability & Resilience Engineering , and in FinTech Business
>> Description
This special session invites papers exploring AI's role in advancing software reliability and resilience engineering within FinTech. We welcome research on AI-driven failure prediction, automated recovery, and robust financial systems. Submit your work to shape the future of resilient FinTech!
>> Session organizer
Jayanna Hallur, Capital One, USA
>> The topics of interest include, but are not limited to:
▪ AI-Driven Anomaly Detection and Incident Response:
Utilizing machine learning algorithms to proactively
identify, classify, and mitigate software failures in
real-time financial systems.
▪ Self-Healing Architectures in FinTech: Research on
autonomous recovery mechanisms, intelligent fault
tolerance, and self-remediating architectures for
uninterrupted financial services
▪ Predictive Reliability Modeling: Applying advanced
predictive analytics and deep learning to forecast
system degradation, manage capacity, and schedule
maintenance in critical banking infrastructure.
▪ Intelligent Chaos Engineering: The application of AI
to design, execute, and analyze chaos experiments,
proactively uncovering hidden vulnerabilities in complex
FinTech microservices.
▪ AIOps and the Automation of SRE Workflows: Leveraging
Large Language Models (LLMs) and generative AI to
automate root cause analysis, intelligent log parsing,
and everyday site reliability engineering tasks.
▪ Explainable AI (XAI) for Resilient Risk Management:
Balancing high-availability technical resilience with
regulatory compliance, auditability, and transparency in
AI-driven financial software.
▪ AI-Enhanced Security and Resilience Convergence:
Strategies using artificial intelligence to protect
high-frequency trading and payment gateways from the
cascading effects of both system failures and malicious
cyber-attacks.
▪ The Business Impact of AI-Driven Resilience: Empirical
studies quantifying the ROI, business continuity
improvements, and scalability benefits of implementing
intelligent SRE practices within FinTech organizations.
>> Submission method
Submit your Full Paper or your paper abstract-without
publication (200-400 words) via
Online Submission System,
then choose Special Session 2 (Artificial Intelligence in Software Reliability & Resilience Engineering , and in FinTech Business)
>> Template
Introduction of session organizer
Jayanna Hallur
Capital One, USA
Bio:
Jayanna Hallur is a Senior Manager of Software
Engineering at Capital One, bringing over two decades of
experience in information technology. Based in Richmond,
VA, he specializes in Site Reliability Engineering
(SRE), observability, and enterprise data architecture.
Jayanna has a proven track record of designing scalable
solutions that proactively reduce Mean Time to Detect
(MTTD) and Mean Time to Restore (MTTR) for critical
financial applications.
To further advance these efforts, his technical strategy
heavily integrates Artificial Intelligence to solve
complex reliability and resiliency engineering
challenges. By leveraging AI-driven anomaly detection
and predictive machine learning alongside modern
cloud-native infrastructures, he works to enhance system
fault tolerance and preempt outages before they impact
the business. His custom observability solutions
increase application resiliency and reduce downtime,
significantly contributing to business growth and
customer satisfaction.
An active leader in the tech community, Jayanna serves
as the General Secretary for the IEEE Richmond Section
and frequently contributes as a conference peer
reviewer. He holds a Master of Science in
Telecommunication and Software Engineering from BITS
Pilani. In 2024 and 2025, he filed three patent
applications, underscoring his commitment to continuous
engineering innovation.