"The rise of AI"

Result-oriented engineering manager, software architect, team lead and software engineer with 15 years of experience. Skilled in software architecture, distributed systems, Java platform and team management. Designed and built multiple fintech solutions for Europe and Asia.

"AI test validation"

With over 15+ years of experience in machine learning, data engineering, and data analytics, I am a Supervisor ADAS Machine learning Operations at Ford Motor Company, where I lead the development and management of the machine learning pipeline for ADAS workflow on Google Cloud Platform and on-premises infrastructure. I have a Master of Science degree in Analytics from Georgia Institute of Technology and multiple certifications in AWS,Kubernetes,Terraform,Azure, SAFe, and Databricks.

I have successfully spearheaded and delivered multiple projects across various domains and industries, such as insurance, banking, and consulting, demonstrating exceptional leadership skills, technical expertise, and business acumen. I have also actively contributed to the enhancement of ADAS capabilities by continuously improving the feature store pipeline and implementing best practices. I have collaborated with cross-functional teams to ensure alignment between ADAS requirements and the feature store pipeline. I am passionate about leveraging machine learning and data engineering to drive innovation and business value.

"Future of content marketing via Gen AI"

• IT Advisor
• Data Science
• Risk Management & Solutions
• Strategy
• Machine Learning/Gen AI
• Software Engineering Talent/Development & Recruitment
• Research & Development Pharma.

I'm about the practical application of STEM where data science is the core foundation. As a lifelong learner, I am fixated on a broader scope of knowledge to augment similar career experiences that begin in antiviral research, migrated in telecommunications, and has blossomed in risk management & risk solutions all rich in data.

"Building Scalable AI Systems: Infrastructure and Tools"

As AI continues to advance and integrate into diverse industries, scalability has become a critical requirement for AI systems. This speech will explore the key challenges and solutions involved in building scalable AI systems. The increasing demand for computational power, the importance of robust data management, and the necessity of efficient infrastructure will be discussed.

Ali Adibi, PhD, is a Principal Data Scientist at PortPro, specializing in AI/ML and optimization. With over 10 years of experience, he has developed innovative models across transportation, supply chain, and healthcare, enhancing efficiency and enabling data-driven strategic decision-making through AI applications.

"Securing AI: Navigating Privacy, Security, and Compliance"

Maria is a seasoned leader with extensive expertise spanning over 15 years in Cybersecurity, AI,/data, and software engineering. Her diverse background includes AI implementations, digital transformation (DevSecOps/SRE), technology management, cyber resilience, privacy, compliance, and risk across various industries, including government and commercial sectors such as finance, healthcare, technology, retail, transportation, and manufacturing. Renowned for her talent in devising and executing hyper-growth and transformative strategies, Maria remains people-focused throughout. While she spent greater time working for large enterprises, she also has a remarkable track record of scaling strategies for start-ups, SMBs, and Fortune 100 companies alike.

"Optimizing Microservices Testing in Agile"

Microservices architecture is key to building scalable, flexible applications, especially in Agile environments. However, testing these distributed services presents unique challenges. This presentation covers essential strategies for integration, functional, and non-functional testing, and highlights tools like Docker, Kubernetes, Postman, and Jenkins that support automated testing, continuous integration, and deployment. By using these techniques and tools, teams can ensure reliable microservices while keeping up with Agile's fast-paced workflow.

Dilruba is a Senior Engineering Manager at Palo Alto Networks, leading the IoT Security QA team. With extensive experience in hands-on, end-to-end software testing and managing engineering teams, she has worked at both large companies and startups, including Microsoft, Cisco, RetailNext, and Hitachi. Dilruba holds a BS in Electrical Engineering from the Georgia Institute of Technology and an MS in Engineering Management and Leadership from Santa Clara University. She is active in Women in Technology networks, frequently speaking at events to inspire others. In her free time, she enjoys acrylic painting and traveling.

"Test automation frameworks development that ensures the product's high qualities throughout its entire life cycle"

In this talk, I will elaborate on how my team ensures that our product has the highest quality throughout its life cycle - from the early development stage, to the release process, the automation testing, all the way to the manual QA testing, and finally the deployment of the solution at the customers

We will go through the various test automation frameworks which are used in each stage of the product's life-cycle, and I will share the ideas and decisions behind the selection of the framework we use.

Over 20 years' experience in software development - Throughout my careers, I did manual QA, test automation development, software development and (even) technical marketing engineering