I am an AI researcher and practitioner with over a decade of experience in artificial intelligence, specializing in large language models (LLMs), generative AI, and their transformative real-world applications. I have extensive experience architecting and deploying sophisticated AI solutions across various sectors, including Finance, Healthcare, and Robotics.
Most recently, as Principal AI Scientist at In-Parallel, I led the design and implementation of advanced agentic AI systems utilizing graph-based Retrieval-Augmented Generation (Graph-RAG) and multi-agent systems to enhance strategic decision-making and planning, monitoring execution, and knowledge extraction capabilities.
Previously, as CIO/CAIO at Resoniks, I spearheaded the development of an AI-driven anomaly detection and quality control system utilizing acoustic data. I also played a key role in securing $2.65 million in seed funding.
My research has been published in top journals and conferences, including Frontiers in Robotics and AI (MACRPO), IEEE Transactions on Intelligent Vehicles (Multi-Task Representation Learning), and IEEE Intelligent Vehicles Symposium (Vision Transformers for Driving Policies). With a passion for innovation, I mentor aspiring AI professionals and have authored over 100 blog posts to make complex AI topics accessible.
Sharing insights on AI, machine learning, and technology
Recently, I have started to play around and learn more about DSPy and decided to write several blog posts as I learn more. And as the medical domain is one of my interests, I thought we could do a simple project there...
Read more →As someone with a background in reinforcement learning (RL) and having witnessed its rising prominence in the large language model (LLM) domain, I have been thinking a lot over the last few weeks about how RL is used to refine LLM behavior. From fine-tuning policies ...
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