Prabakaran Chandran is a Senior Machine Learning Engineer with six years of experience in designing and deploying AI/ML solutions across diverse domains, including CPG, Oil & Gas, Power, Sustainable Aquaculture, and Data Observability. His expertise spans deep learning, causal inference, and graph machine learning, with a strong focus on advancing decision-making systems and causal reasoning for complex enterprise and social challenges.

Currently, at Informatica LLC, he is leading research on enterprise data observability, implementing multi-agent AI systems, anomaly detection, and predictive analytics to enhance ITOps performance. His work involves optimizing Large Language Models (LLMs) through adapter layers and PEFT techniques, enabling real-world AI applications that are more efficient and scalable.

Previously, as a Data Scientist at Captain Fresh, Prabakaran played a key role in developing computer vision models for aquaculture monitoring, applying YOLOv8 and Segment Anything Model (SAM) to analyze satellite imagery and optimize global shrimp trade operations. His work has significantly improved data-driven decision-making for farmers and seafood traders, making AI more impactful in underrepresented industries.

During his tenure at Mu Sigma, he tackled high-impact projects for Fortune 500 companies, including supply chain transformation, demand sensing, and agent-based modeling for major global brands. His work on Bayesian network simulations for consumer behavior analysis laid the foundation for his ongoing research in causal AI and decision engineering.

Beyond his professional work, Prabakaran is deeply committed to AI education and community building. He has:
✅ Taught 300+ hours of AI and analytics courses on platforms like Guvi and Unacademy
✅ Trained government employees at Keltron on AI-based office automation
✅ Led AI Bootcamps for engineering students, mentoring international students on machine learning
✅ Founded 'AI TamilNadu', a non-profit that fosters AI education for rural students
✅ Presented at Google Developer communities, TensorFlow user groups, and AI conferences

Prabakaran’s thought leadership extends to AI research and innovation, with publications on NLP, sentiment analysis, and causal AI applications. He is currently working on curating reasoning datasets and training domain-specific LLMs for legal and insurance applications.

At the heart of his work is a passion for leveraging AI to solve real-world problems, bridging the gap between research and industry. With his systems thinking approach, he is redefining how businesses and communities can harness AI for better decision-making, automation, and impact at scale.