Human-in-the-loop Reinforcement Learning to Train Pilots Using Trained Agents• Algorithm Implementation: Contributed to the implementation of advanced reinforcement learning algorithms in a cross-functional team to develop AI agents for aircraft piloting simulations.• Innovation and Efficiency: Developed novel strategies in reward shaping and curriculum learning for complex flight scenarios, significantly improving the efficiency and performance of AI pilot training.• Impactful Application: Enhanced pilot training programs by integrating AI-driven techniques, resulting in measurable improvements in training outcomes and operational readiness.

Predicting Time to Recurrence of Prostate Cancer• Collaborative Research: Worked with a multidisciplinary team to predict the time to Biochemical Recurrence (BCR) of prostate cancer post-surgery using cutting-edge survival analysis techniques.• Data-Driven Insights: Leveraged a combination of histopathology images and clinical data to develop machine learning models, uncovering critical insights that enhanced predictive accuracy.• Strategic Advancements: Demonstrated the potential for integrating diverse data sources to improve prognostic models, contributing to more effective patient care strategies and decision-making processes.

1. Zoning the department.2. Rotating stock and checking for expired products.3. Ensuring the merchandise is properly signed and priced.4. Adhering to standards and policies for cold chain compliance.5. Adhering to food safety and handling procedures and following sanitation and cleaning procedures.6. Following proper procedures for inventory management.7. Maintaining features on end-caps.8. Keeping the area clean of hazards.