I'm Swayam Singh, an AI/ML researcher with a passion for building scalable AI systems, optimizing deep learning models and contributing to cutting-edge open-source projects. My journey includes impactful work at Microsoft Research, where I developed and fine-tuned Large Language Models (LLMs) using state-of-the-art techniques like Reinforcement Learning with Human Feedback (RLHF) and Direct Preference Optimization (DPO) I’ve authored publications in NeurIPS, ICLR, and TMLR, with a focus on generative AI, model optimization, and applying AI to specialized domains. My projects have gained significant attention, including my open-source Virtual Clothing Assistant, a trending project on GitHub with 300+ stars, showcasing the potential of AI-powered virtual try-ons Previously, as an SDE Intern @ NumPy (Quansight Labs), I contributed to expanding the library’s capabilities by implementing custom data types and ensuring cross-platform compatibility. My entrepreneurial spirit has led me to develop projects like Enigma, a C/C++ tensor framework for dynamic neural networks, and TuneX, a CLI toolkit for fine-tuning LLMs, both at the intersection of research and real-world application. Beyond research and development, I engage with the community as a Kaggle Competition Expert and actively mentor aspiring AI/ML enthusiasts. If you're passionate about AI research, open source, or collaborating on bold ideas, let's connect!