I am Deep Mehta, a data scientist and AI researcher passionate about building machine learning, natural language processing (NLP), and computer vision solutions. I am currently pursuing a Master’s in Data Science and actively developing AI-driven projects, including real-time chatbots, AI agents, and intelligent automation tools. I specialize in Python, SQL, LangChain, OpenAI models, and vector databases like ChromaDB, using these technologies to create web content interaction tools, skill development trackers, and automated job application systems. I enjoy participating in hackathons, collaborating with industry experts, and pushing the boundaries of AI innovation. I continuously explore retrieval-augmented generation (RAG), autonomous agents, and real-time AI processing to develop transformative AI solutions. My goal is to enhance efficiency, decision-making, and automation across industries through cutting-edge AI applications.

I am currently interested in learning more about advanced machine learning techniques, especially in the areas of natural language processing (NLP) and computer vision. I'm particularly drawn to the application of deep learning models like transformers for NLP and object detection for computer vision tasks. I'm also exploring AI ethics, fairness, and explainability in machine learning models. In terms of potential collaborators, I'm looking to connect with professionals or researchers who specialize in: AI and ML research, particularly in developing cutting-edge models Data science and analytics, with a focus on solving real-world business problems Software engineers with expertise in deploying machine learning models to production AI ethics and policy experts, especially those with experience in ensuring fairness, transparency, and accountability…

I’m currently working on building an AI-powered chatbot that interacts with websites in real-time, extracting and analyzing relevant content dynamically. The project leverages LangChain, OpenAI embeddings, and ChromaDB to enable contextual responses based on website content. Additionally, I’m exploring AI agent development for various applications, including automated job applications (Job Bot) and document-based Q&A systems that help users interact with educational materials more effectively. Given my experience, retrieval-augmented generation (RAG), and real-time AI processing, I’m excited to push the boundaries of real-time voice and reasoning AI at this hackathon, integrating cutting-edge architectures for sub-second interactions.

I’m an AI/ML Engineer & Data Scientist with hands-on experience building predictive models, end-to-end ML pipelines, and LLM-powered applications. My work spans across industry, research, and hackathons — centered on using AI to drive real-world impact. At DF Young, I’m currently leading efforts to extract hidden business value from logistics data for enterprise clients. From developing predictive reorder models to prototyping Graph Neural Networks (GNNs) for uncovering complex relationships, I focus on delivering actionable insights that improve supply chain decision-making. At DSM-Firmenich, I built machine learning and deep learning models that enhanced flavor formulation accuracy by 20%.

I'm passionate about leveraging cutting-edge AI, including Generative AI, LLMs, and Graph Neural Networks, to solve complex business problems, particularly in supply chain and logistics. I am eager to connect with engineers, researchers, and founders who are building innovative, data-driven products. I'm currently seeking full-time AI/ML Engineer or Data Scientist roles where I can contribute to developing impactful, end-to-end machine learning solutions.