Workshops

Smart Dev Assistant: AI Agent Mode in VS Code

Udaya Veeramreddygari
Lead Software Engineer, USA & IEEE member USA
Short Bio
Experienced software engineering leader with over two decades of proven expertise in architecting, developing, and managing enterprise-scale applications across domains like automotive, finance, and telecommunications. Specialized in Java, Spring Boot, Microservices, and AWS. Udaya has led cross-functional teams across global locations, delivering high-performance, cloud-native solutions aligned with business strategy. His current role as Lead Software Engineer at Cox Automotive highlights his strengths in system modernization, ML/AI integration, and GenAI enablement, fostering automation and innovation across the SDLC. Beyond engineering, Udaya is deeply engaged in the technology community through conference speaking, peer reviews, and judging for global tech awards. He is an active member of IEEE and serves on technical program committees for multiple international conferences. With certifications in AWS, Scrum, ITIL, and architecture, along with scholarly contributions on LLMs, AI productivity, and sustainability, Udaya brings a unique combination of technical depth, leadership acumen, and thought leadership to every engagement.
 
Abstract
This workshop highlights the incredible capabilities of AI Agent Mode in Visual Studio Code. Here, a smart coding assistant works independently to support developers as they write, debug, and refactor code in real-time. By using natural language prompts, the agent can understand tasks, offer suggestions for improvements, and even take actions directly within the code editor. This creates a smooth, context-aware development experience that’s perfect for enhancing productivity, minimizing context-switching, and optimizing workflows.
 
 
 

AI Across Industries: Driving Innovation, Efficiency, and Sustainable Growth -Transforming Manufacturing, Agriculture, Real Estate, Governance, Cybersecurity, and Entertainment

Mr. Harshavardhan Yedla
Principal Architect Practitioner Data, AI & Digital Products, Wipro LLC, USA

Mr. Venkat Sharma Gaddala
Software Engineer, Google, USA

Short Bio

Mr. Harshavardhan Yedla is a seasoned IT professional with 18 years of experience in implementing and architecting digital technologies, having made significant contributions at renowned organizations like Wipro, Persistent & Genpact. His expertise encompasses a broad spectrum of areas including Data Engineering, AI/ML, Cloud Solutions & Business Transformation. Mr. Yedla has successfully led cross-functional teams, managed complex data transformation projects & driven innovative solutions across various domains such as finance, healthcare, and manufacturing & Supply Chain. He has published scholarly articles on advanced forecasting techniques and environmental sustainability and actively contributes as a reviewer for numerous international conferences and journals. His role as a Principal Architect Practitioner has seen him leading transformative projects at prominent companies like Disney+, Zelle, Walmart, GE where he has shaped technology roadmaps and enhanced business processes. Yedla is a Senior Member of IEEE and a Fellow of the IETE & SAS Society, Mr. Yedla continues to drive strategic initiatives and provide thought leadership in the realms of data analytics and digital transformations & AI.
 
Mr. Venkat Sharma Gaddala is a seasoned IT professional with over 19 years of experience in architecting and implementing enterprise solutions across leading organizations such as Google, Anaya Technologies, and Infosys. His expertise spans Enterprise Generative AI, LLM applications, supply chain transformation, Google Cloud integration, and SAP solutions. Known for his ability to lead complex implementations and design data-driven, efficient architectures, Mr. Gaddala has consistently delivered impactful results. He has authored seven research papers on the application of Generative AI in supply chain management. He actively contributes to the academic community as a paper reviewer and editorial board member for an international journal. In his current role as Engineering Lead at Google, he spearheads innovation and drives supply chain transformation through advanced Enterprise Generative AI and LLM technologies. Recognized for his contributions, he holds distinguished affiliations, including Senior Member of IEEE, Fellow of IETE, Eminent Fellow of the SAS Society, and Distinguished Fellow of SCRS. Mr. Gaddala continues to provide thought leadership and guide strategic initiatives in enterprise AI and digital transformation.
 
Abstract
Artificial Intelligence (AI) is revolutionizing industries by enhancing efficiency, innovation, and decision-making. In manufacturing, AI powers predictive maintenance and autonomous operations, boosting productivity and reducing downtime. Digital agriculture enables smarter crop management and resource use, promoting sustainable practices. Real estate leverages AI for accurate property valuation and smart building systems, improving energy efficiency and tenant experiences. Governments and public sectors use AI for predictive modeling and policy simulation, supporting better governance. In cybersecurity, AI strengthens encryption, threat detection, and authentication systems. Meanwhile, in media and entertainment, it drives content creation, personalized streaming, and immersive virtual experiences. Across sectors, AI delivers measurable ROI, advances sustainability, and empowers more informed decisions. 

AI and ML Driven Customer Analytics to Operational Optimization in Retail Industry

Abhi Desai
Research Scholar — AI, ML, Data Science & Analytics
Former Lead Data Analyst at Saks Fifth Avenue, NY, USA
Short Bio
Abhi Desai is a Data Science and AI professional with over 10 years of experience delivering analytics, machine learning, and data-driven solutions. He holds a dual M.S. in Data Science and Analytics and a B.E. in Computer Science and Engineering. He has contributed to AI initiatives at leading organizations including Saks Fifth Avenue, Target, and IPG Media Brands in New York, USA, delivering AI-driven solutions that improved operational efficiency and decision-making in retail and logistics.
He has authored and published multiple peer-reviewed papers in AI, machine learning, explainable AI, and retail analytics. Abhi actively contributes to the global research community as a session chair, workshop organizer, hackathon judge, review panelist, and invited speaker, and serves as an ethics and technical paper reviewer for international conferences and journals across multiple industries and international contexts. He is a Senior Member of IEEE and holds fellowships in leading professional societies. He bridges academia and industry to deliver transformative AI and analytics solutions with global impact.
 
Abstract
This workshop demonstrates how analytics and data science can transform retail operations by connecting customer insights to operational decision-making. Participants will explore how AI and ML techniques are applied to customer segmentation, lifetime value (LTV), lifetime revenue (LTR), and customer acquisition cost (CAC), and how these insights inform labor planning, shipping optimization, and inventory management. Real-world retail examples illustrate the end-to-end workflow, highlighting measurable improvements in efficiency, accuracy, and strategic decision-making. Attendees will gain practical guidance on leveraging AI and ML to bridge customer analytics and operational optimization, enabling them to drive tangible business impact in retail and beyond.

The k-Proportional t-Value in Big Boss Games: Bridging Game Theory, Artificial Intelligence, and Operational Research

İsmail Özcan

Department of Engineering for Industrial Systems and Technologies, University of Parma, Parma/Italy

Short Bio
Dr. İsmail Özcan is a Postdoctoral Research Fellow at the Department of Engineering for Industrial Systems and Technologies, University of Parma, Italy. Prior to this appointment, he held a postdoctoral position at the Operations Research Center, Universidad Miguel Hernández, Spain.

He obtained his Ph.D. in Mathematics from Süleyman Demirel University, Turkey, and later received official Ph.D. equivalence recognition in Spain, confirming the international academic standing of his degree. His research explores the intersection of cooperative game theory, fuzzy and grey systems, artificial intelligence (AI), and operational research (OR), with a focus on developing quantitative models for decision-making under uncertainty and hierarchical collaboration in industrial and economic systems.

Dr. Özcan has authored and co-authored several distinguished contributions in international journals and academic volumes, advancing both theoretical foundations and applied dimensions of game theory, optimization, and intelligent systems. His scholarly agenda bridges mathematical abstraction with real-world analytics, contributing to the integration of AI and OR methodologies in modern research.

He actively serves as a reviewer for leading SCI-Expanded journals in optimization, operations research, and fuzzy systems, and is a member of EURO, INFORMS, SEIO, and the American Mathematical Society.

 
Abstract

This workshop explores the k-proportional t-value, a fresh perspective on how collaboration and influence can be modeled in complex organizations. Building on ideas from game theory, Artificial Intelligence (AI), and Operational Research (OR), this approach helps us understand how leaders and teams share value and make balanced decisions in hierarchical settings.

Rather than focusing purely on mathematical details, the session will emphasize how the k parameter introduces flexibility in distributing payoffs and maintaining fairness among players — especially in big boss games, where one dominant actor significantly shapes the group’s success.

To make the discussion more engaging, participants will form small coalitions to simulate “big boss” decision-making scenarios and observe how different k values affect cooperation outcomes. An interactive visualization will illustrate how changes in proportionality impact fairness and stability, while a real-world case inspired by Amazon’s AI teams developing personalized recommendation systems will show how data-driven cooperation can be analyzed through this framework.

By blending theory with practical examples and interactive exercises, the workshop demonstrates how the k-proportional t-value can inform smarter, fairer, and more adaptive decision-making in industrial operations, logistics, and AI-based organizations. Participants will leave with both conceptual insights and an intuitive sense of how hierarchical collaboration can be optimized.