San Francisco Bay Area
"Hi, I'm Dhruv Kumar, an AI Engineer and Researcher passionate about integrating AI into diverse domains to solve real-world problems. I'm a DST Inspire Awardee, 3x research paper author, and currently working as an AI Engineer at AI Planet. My expertise spans computational biology, retrieval-augmented generation (RAG), AI agents, robotics, and web-based AI applications. Through my research and innovations, I aim to push the boundaries of technology and create impactful solutions."
Conducted research on urban heat wave planning with a focus on Delhi, analyzing climate patterns and mitigation strategies Studied and evaluated the Delhi Heat Action Plan across multiple years to identify gaps and improvements Built an algorithm to map individual user data with potential heatwave impact for personalized risk assessment Developed a consumer-friendly mobile web application for heatwave insights and recommendations Implemented a RAG (Retrieval-Augmented Generation) pipeline for multi-year heat action plan data Integrated LLM APIs for context-aware responses on heatwave risks and safety guidance Designed a system to store disease history and predict health risks during heatwaves on specific days Worked with satellite imagery to analyze environmental factors contributing to urban heat patterns
Project: myhair.ai, Palmador.ai, samwell.ai Led development of advanced AI algorithms for in-depth hair analysis, contributing to ongoing research in innovative hair diagnostics and care technologies. Designed and implemented multiple computer vision models for hair assessment and analysis. Built and productionized end-to-end AI systems using a scalable microservices architecture. Managed and maintained backend systems serving 3M+ users, ensuring high availability and reliability. Identified and resolved latency issues across multiple microservices, improving performance for concurrent requests. Developed and deployed distributed backend infrastructure to support large-scale AI workloads. Worked extensively with cloud platforms including AWS and GCP for scalable system design and deployment. Built realistic video generation pipelines for advertising purposes using advanced video models. Collaborated across teams to integrate AI models into production systems and optimize performance.
Conceptualized a Retrieval-Augmented Generation (RAG) system, reducing inference latency and improving response efficiency Enhanced a FastAPI backend to optimize API performance and scalability Developed a RAG-based knowledge base chat system for efficient information retrieval and interaction Conducted research on self-learning systems and explored use cases of DSPy for adaptive AI workflows Researched and conceptualized advanced frameworks such as Atomic design patterns and DSPy for building modular and scalable AI systems
Served as Lead for the Intel AI Student Community, driving initiatives to promote AI learning and innovation among students Led and mentored a growing community of young AI learners, fostering collaboration and hands-on development Organized and scaled multiple AI-focused sessions, impacting 5,000+ students across diverse backgrounds Delivered 4+ in-depth sessions on AI technologies, covering practical applications and emerging trends Played a key role in organizing the India AI Impact Festival, coordinating efforts across teams and stakeholders Contributed to designing learning strategies and engagement models to make AI education more accessible and effective Collaborated with peers and leadership to build structured programs, workshops, and knowledge-sharing platforms for the community