With 9+ years in AI/ML research, I specialize in scalable, data-driven solutions that tackle complex business challenges. As Manager - AI Research and Innovation at ZS, I lead a team of 10+ researchers and data scientists, driving innovations in time series forecasting, synthetic data, classical ML, and data privacy. Expertise: Time series forecasting, synthetic data, ML, data privacy Client Impact using AI/ML: Revenue Management for a Major US Airline: Improved demand forecast accuracy by 40% using ML/AI leading to significant improvement in topline revenue. Fraud Detection in Clinical Trials: Built an AI driven fault detection system, for the internal Audit team of a top pharmaceutical company. Phase 3 Trial Optimization: Discovered key drivers of super responders to improve treatment outcomes. Patient Retention in Clinical Trials: Identified patient burden factors leading to dropouts. De-Identification & Data Privacy: Developed pseudonymization solutions with quantifiable risk mitigation. Synthetic Data & Digital Twins: Led initiatives to create privacy-preserving synthetic datasets for sensitive data. Academic & Research Impact: Published in NeurIPS, Nature, IEEE, and Elsevier, contributing to cutting-edge AI advancements. I thrive on solving high-impact AI challenges, scaling innovation, and bridging research with real-world applications. Let’s connect and discuss the future of AI! 🚀