About

Work Experience

• Senior Staff AI Engineer, GE Aerospace

  Sep, 2024 - Present

  Lead development of advanced ML systems for mission-critical aerospace applications.

  • Developed advanced computer vision pipelines for aerospace applications, deploying ML models for real-time document understanding and robotic perception systems

  • Built production ML infrastructure using PyTorch and cloud-based deployment (AWS), implementing scalable pipelines for training and inference

  • Utilized PaddleOCR vision models to extract structured data from technical drawings, integrating multimodal approaches combining visual and textual information

  • Collaborated with cross-functional engineering teams to design and optimize ML algorithms for autonomous system applications

  • Mentored junior engineers on ML best practices, model deployment strategies, and production system architecture

• Senior Data Scientist, John Deere Financial

  Jul, 2023 - Aug, 20241 year 1 month

  Architected and deployed ML solutions for financial analytics and predictive modeling.

  • Architected Next-Gen Market Insight Platform using ML/AI to enable predictive analytics and data-driven decision making

  • Designed and deployed ML models using Python, scikit-learn, and AWS services for scalable financial analytics applications

  • Built robust data processing pipelines integrating real-time data for production ML systems

  • Served as technical lead collaborating with product and engineering teams to identify high-impact ML solutions

  • Implemented responsible AI practices including model evaluation, fairness testing, and deployment optimization

• Data Scientist, Lambda3

  Aug, 2022 - Jun, 202310 months

  Designed and implemented computer vision systems for industrial automation and compliance monitoring.

  • Designed and implemented computer vision algorithms for automated compliance monitoring with real-time video processing

  • Developed intelligent automation system demonstrating autonomous behavior for safety applications in industrial environments

  • Built ML pipelines for business intelligence solutions using Python and modern ML frameworks

  • Optimized model performance for real-time inference in production environments

• Data Scientist, Shopee

  Oct, 2020 - Jan, 20213 months

  Developed ML models for e-commerce optimization and marketplace intelligence.

  • Developed machine learning models for SKU matching and pricing optimization in high-volume e-commerce marketplace

  • Implemented intelligent automation solutions (RPA) to optimize operational workflows and system efficiency

  • Deployed production ML models at scale serving millions of users

• Partner | Data Scientist, Norte Asset Management

  Jan, 2021 - Mar, 20221 year 2 months

  Led data science team and built ML-powered analytics platform for investment decision-making.

  • Led data science team of 5+ engineers building ML-powered analytics platform for financial decision-making

  • Established data infrastructure integrating multi-source data feeds for intelligent system development

  • Developed automated insight generation system demonstrating early intelligent agent design principles

  • Architected real-time data products leveraging ML for actionable intelligence delivery

• Senior Systems Analyst, Credit Suisse

  Jul, 2011 - Jul, 20187 years

  Developed and maintained critical financial systems in regulated banking environment.

  • Developed and maintained critical financial systems for 7 years in regulated banking environment

  • Led solution delivery using modern software engineering practices for production systems

  • Collaborated with cross-functional teams to implement scalable software solutions using C#, .NET, and SQL

  • Ensured system reliability, security, and compliance with financial industry regulations

Projects Experience

• PhD Research - Multi-Agent Reinforcement Learning

  Mar, 2024 - Present

  Conducting advanced research in Reinforcement Learning with focus on agent coordination, learned policies, and intelligent behavior. Designing and implementing simulation environments for training RL agents. Exploring policy gradient methods, reward shaping, and curriculum learning techniques. Investigating applications of RL to autonomous systems and intelligent robotics.

  • Multi-Agent RL algorithm development

  • Simulation environment design

  • Policy optimization and learning dynamics

  • Research for top-tier ML/AI conferences

Skills

Education