Shadab Hussain
Lead Engineer, MathCo & Co-Founder, Quantum Computing India
Chicago, Illinois, United States
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Shadab Hussain is a global technology leader at the forefront of Artificial Intelligence , Blockchain, and Quantum Computing. As a Lead Engineer at MathCo, he spearheads innovations in Engineering and Generative AI, delivering transformative solutions that shape the future of enterprise technology.
He is the Co-founder of Quantum Computing India and previously served as a Developer Advocate at the London Stock Exchange Group, where he bridged advanced engineering with real-world application across global developer ecosystems. Recognized as a Google Developer Expert for AI/ML (GenAI) and an AWS Community Builder, Shadab also holds certifications in AWS Machine Learning Specialty and Google Cloud Machine Learning Engineering.
A TEDx speaker and active contributor to the Davos Digital Council, Shadab operates at the intersection of emerging technologies, policy, and innovation strategy. He has presented at premier global platforms including the Data Engineering Summit, Quantum Innovation Summit, Google Developer Groups (GDG), and AWS events, where he actively champions AI governance, workforce development, and national innovation ecosystems.
An accomplished author and researcher, Shadab is the co-author of a book on Quantum Computing in Finance, merging academic insight with practical execution. Through ongoing mentorship, technical workshops, and hackathon leadership, he plays a pivotal role in addressing the global AI & Quantum talent gap—particularly in the United States—and advancing the responsible deployment of frontier technologies.
Area of Expertise
Topics
Unveiling the Quantum Leap in Financial Modeling using AWS Braket
As classical computing reaches its limits, the financial landscape stands poised for a revolutionary transformation with the advent of quantum computing. This workshop unveils the hidden potential of quantum algorithms, empowering attendees to navigate this emerging frontier. Demystify core quantum concepts and their financial applications, exploring game-changers like portfolio optimization with superhuman speed, risk analysis beyond classical limitations, and AI-powered fraud detection. We equip them with hands-on experience using practical tools and frameworks to prototype quantum finance strategies. Attendees will not emerge just informed but prepared to leverage the quantum leap on AWS Braket and shape the future of finance.
MLOps using VertexAI: Beyond Model Training
This session covers the steps to implement a reliable, reproducible, and automated machine learning pipeline with Google Vertex AI. Participants will learn how to use Vertex AI–Google Cloud’s newly announced managed ML platform–to build end-to-end ML workflows. They’ll know how to go from raw data to deployed model, leaving this session ready to develop and productionize their own ML projects with Vertex AI.
Demystifying MLOps on AWS - Propelling Models from Prototype to Production
In this workshop, we will build an MLOps pipeline that leverages Amazon SageMaker, a service that supports the entire pipeline for ML model development, and is the heart of this solution. Around it, we will add different AWS DevOps tools and services to create an automated CI/CD pipeline for the ML model. This pipeline will prepare the data, build our docker images, train and test the ML model, and then integrate the model into a production workload.
Building Intelligent Applications: Harnessing Neo4j with Google Cloud's Generative AI
In today’s rapidly evolving tech landscape, the ability to craft intelligent applications that leverage the power of generative AI is crucial. This session will explore the integration of Neo4j’s graph database capabilities with Google Cloud’s cutting-edge generative AI tools, providing a powerful ecosystem for developing advanced applications.
We will dive deep into how Neo4j’s graph-based data models can be combined with the generative AI capabilities of Google Cloud to create applications that not only understand and reason about complex relationships but also generate insightful content and predictions. Through practical demos and code walkthroughs, you’ll learn how to deploy this integrated solution to solve real-world problems in various domains such as personalized recommendations, intelligent search, and more.
This talk is designed to showcase the integration of Neo4j’s graph database with Google Cloud’s generative AI tools, providing attendees with a comprehensive understanding of how to build intelligent, next-gen applications. The session will be highly technical, including live demos and code walkthroughs to ensure participants gain practical knowledge they can apply directly to their projects.
Technical Requirements:
- A reliable internet connection for live demos
- Access to Google Cloud and Neo4j instances for demonstration purposes
- Projector setup with HDMI input for the presentation
- Optionally, hands-on participants should have pre-configured access to Google Cloud and Neo4j to follow along
Session Duration- 30-60 mins talk/workshop
This session promises to be highly informative, engaging, and relevant to professionals seeking to leverage advanced AI tools in their work.
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